2010-03-08 18:16:50 +01:00
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#
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2011-01-14 15:36:03 +01:00
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# spec file for package opencv
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2010-03-08 18:16:50 +01:00
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#
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Accepting request 1114642 from home:StefanBruens:branches:science
- update to 4.8.1
* WebP security update for CVE-2023-4863
* Depthwise convolution 5x5 performance regression fix
- update to 4.8.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version480
Highlights of this release:
* DNN module patches:
+ TFLite models support, including int8 quantized models.
+ Enabled DNN module build without Protobuf dependency.
+ Improved layers => supported more models:
- ONNX: Layer normalization, GELU and QLinearSoftmax.
- Fixes in CANN backend:
* support ONNX Split, Slice, Clip (Relu6) and
Conv with auto_pad.
* support ONNX Sub, PRelu, ConvTranspose.
- Reduce Refactor for robustness and potential
follow-up improvements.
- Fixes for Segment Anything Model by Meta.
- Fixes in nary element wise layer about broadcast:
* Fixes in CPU.
* and Fixes in CUDA backend.
- Further increased DNN speed on ARM and X86 by improving
convolution, covering 1D and 3D cases, supporting
convolution+element-wise op fusion.
- Added full FP16 computation branch on ARMv8 platform, 1.5x
faster than FP32 (FP16 Winograd is still pending).
- Vulkan backend refactor for better performance and
robustness. It runs 4X faster than before.
- Added API blobFromImageParam to build network inputs
with pre-processings.
- Modern OpenVINO support.
* G-API module:
+ Intel® OpenVINO™ inference backend:
- Streamlined preprocessing in OpenVINO
Inference Engine (ie) API 1.0 backend. Note: this backend
will be deprecated after OpenVINO removes the API 1.0
support in its subsequent releases.
- Aligned OpenVINO IE API 1.0 backend with the latest
OpenVINO 2023.0 (as some features were removed there).
- Introduced a brand new OpenVINO API 2.0 backend.
- Implemented the required inference operations for
the OpenVINO API 2.0 backend.
+ Python bindings:
- Exposed varions normalization options for ONNX RT
backend in Python bindings.
- Exposed Fluid kernels and kernel package manipulation
functions (combine()) in Python.
- Fixed issues in Stateful Python kernel state
handling; also fixed various issues in Python tests.
- Fixed issue with opaque kernel output information
handling which broke Python custom kernels.
+ Samples:
- Introduced a new Segmentation demo with desync() to enable
slow-running networks in the real-time.
- Updated stats calculation in the G-API-based pipeline
modelling tool.
+ Other changes and fixes:
- Fixed tolerance in Fluid resize tests to avoid issues
on ARM.
- Fluid backend: extended Merge3 kernel with more
supported data types.
- Fixed standalone mode compilation issues.
* Objdetect module:
+ FaceDetectorYN upgrade for better performance,
accuracy and facial landmarks support.
+ New QR code detection algorithm based on ArUco code.
+ Bar code detector and decoder moved from Contrib to
main repository.
+ Introduced common API for all graphical codes like bar
codes and QR codes.
+ Added flag for legacy pre-4.6.0 ChAruco boards support.
+ Multiple bug fixes and improvements in QR code detection
and decoding pipelines.
+ Multiple bug fixes and improvements in ArUco based pipelines.
* Calibration module:
+ USAC framework improvements.
+ Fixed stddev estimation in camera calibration pipelines.
+ Fixed incorrect pixel grid generation in icvGetRectangles
that improves accuracy of getOptimalNewCameraMatrix,
stereoRectify and some other calibration functions.
Charuco board support in patterns generator, interactive
calibration tool and calibration samples.
* Image processing module:
+ Various fixes in line segments detector.
+ Fixed even input dimensions for INTER_NEAREST_EXACT
in resize.
+ Optimise local cost computation in
IntelligentScissorsMB::buildMap.
+ Keep inliers for linear remap with BORDER_TRANSPARENT
+ Fix distransform to work with large images.
* Features2d module:
+ SIFT accuracy improvements.
* Core module:
+ Added REDUCE_SUM2 option to cv::reduce.
+ Introduced cv::hasNonZero function.
+ Update IPP binaries update to version 20230330.
+ Improved RISC-V RVV vector extensions support.
- Support RVV v0.11 intrinsics available in LLVM 16
and GCC 13
- Support build with T-Head RISC-V toolchain
(RVV 0.7.1 and 1.0)
+ Several OpenCL vendor and version handling improvements.
* Multimedia:
+ Added AVIF support through libavif.
+ Orbbec Femto Mega cameras support.
+ HEVC/H265 support in VideoWriter with MS Media
Foundation backend.
+ Fixed FPS computation on some videos for FFmpeg backend.
+ Added support for VideoCapture CAP_PROP_AUTO_WB and
CV_CAP_PROP_WHITE_BALANCE_BLUE_U for DShow backend.
+ Fixes OBS Virtual Camera capture.
+ CV_32S encoding support with tiff.
* Python Bindings:
+ Python typing stubs.
+ Fix reference counting errors in registerNewType.
+ Fixed ChAruco and diamond boards detector bindings.
+ Added bindings to allow GpuMat and Stream objects to
be initialized from memory initialized in other libraries
+ np.float16 support.
+ Python bindings for RotatedRect, CV_MAKETYPE, CV_8UC(n).
* JavaScript bindings:
+ Added possibility for disabling inlining wasm in opencv.js
+ Extended JS bindings for Aruco, Charuco, QR codes and
bar codes.
* Other:
+ Several critical issue fixes in wechat_qrcode module
(opencv_contrib)
OBS-URL: https://build.opensuse.org/request/show/1114642
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=36
2023-10-02 02:29:16 +02:00
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# Copyright (c) 2023 SUSE LLC
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2010-03-08 18:16:50 +01:00
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#
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# All modifications and additions to the file contributed by third parties
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# remain the property of their copyright owners, unless otherwise agreed
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# upon. The license for this file, and modifications and additions to the
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# file, is the same license as for the pristine package itself (unless the
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# license for the pristine package is not an Open Source License, in which
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# case the license is the MIT License). An "Open Source License" is a
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# license that conforms to the Open Source Definition (Version 1.9)
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# published by the Open Source Initiative.
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2018-11-06 15:18:16 +01:00
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# Please submit bugfixes or comments via https://bugs.opensuse.org/
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2010-03-08 18:16:50 +01:00
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#
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Accepting request 860308 from home:StefanBruens:branches:science
- update to 4.5.1, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version451
* Continued merging of GSoC 2020 results:
+ Develop OpenCV.js DNN modules for promising web use cases
together with their tutorials
+ OpenCV.js: WASM SIMD optimization 2.0
+ High Level API and Samples for Scene Text Detection and
Recognition
+ SIFT: SIMD optimization of GaussianBlur 16U
* DNN module:
+ Improved layers / activations / supported more models:
- optimized: 1D convolution, 1D pool
- fixed: Resize, ReduceMean, Gather with multiple outputs,
importing of Faster RCNN ONNX model
- added support: INT32 ONNX tensors
+ Intel® Inference Engine backend (OpenVINO):
- added support for OpenVINO 2021.2 release
- added preview support for HDDL
+ Fixes and optimizations in DNN CUDA backend (thanks to
@YashasSamaga)
* G-API Framework:
+ Introduced serialization for cv::RMat, including
serialization for user-defined memory adapters
+ Introduced desync, a new Operation for in-graph asynchronous
execution - to allow different parts of the graph run with
a different latency
+ Introduced a notion of "in-graph metadata", now various
media-related information can be accessed in graph directly
(currently only limited to timestamps and frame IDs)
+ Introduced a new generic task-based executor, based on
Threading Building Blocks (TBB)
+ Extended infer<>() API to accept a new cv::GFrame data
structure to allow handling of various media formats without
changes in the graph structure
+ Made copy() an intrinsic where real copy may not happen
(optimized out) based on graph structure, extended it to
support cv::GFrame
+ Various fixes, including addressig static analysis,
documentation, and test issues
* G-API Operations:
+ Introduced new operations morphologyEx, boundingRect,
fitLine, kmeans, Background Subtractor, Kalman filter
* G-API Intel® Inference Engine backend (OpenVINO):
+ Extended cv::gapi::ie::Params<> to import CNN networks (e.g.
pre-compiled ones) instead of passing .XML and .BIN files;
also enabled configuring Inference Engine plugins via
this structure
+ Added a new overload to infer<>() to run inference over a
single region of interest
+ Added support for cv::MediaFrame input data type (projected
from cv::GFrame) and handling for NV12 input image format
* G-API Python bindings:
+ Exposed G-API's Inference and Streaming APIs in the OpenCV
Python bindings
+ Added initial Python support for cv::GArray data structure
* Significant progress on RISC-V port.
- Updated constraints, bump memory to 5 GB
- Cleaned up spec file
OBS-URL: https://build.opensuse.org/request/show/860308
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=23
2021-01-04 20:56:22 +01:00
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2019-08-25 15:21:01 +02:00
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# Build failure with LTO enabled on ppc64le boo#1146096
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%ifarch ppc64le
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%define _lto_cflags %{nil}
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%endif
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2010-03-08 18:16:50 +01:00
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%define libname lib%{name}
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Accepting request 1139607 from home:cabelo:branches:science
- update to 4.9.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version490
Highlights of this release:
* Core Module:
+ Added cv::broadcast
+ Fixed several rounding issues on ARM platform
+ Added detection & dispatching of some modern NEON
instructions (NEON_FP16, NEON_BF16)
+ Added optimization for LoongArch 128-bit vector,
detection & dispatching of LoongArch
* DNN module patches:
+ Experimental transformers support
+ ONNX Attention layer support
+ ONNX Einsum layer support
+ OpenVINO backend for INT8 models
+ ONNX Gather Elements layer
+ ONNX InstanceNorm layer
+ Better support of ONNX Expand layer with cv::broadcast
+ Improved DNN graph fusion with shared nodes and commutative
operations
+ New fastGEMM implementation and several layers on top of it
+ Winograd fp16 optimizations on ARM
+ Tests and multiple fixes for Yolo family models support
+ New layers support and bug fixes in CUDA backend: GEMM,
Gelu, Add
+ CANN backend: bug fix, support HardSwish,
LayerNormalization and InstanceNormalization
+ LayerNormalization: support OpenVINO, OpenCL and
CUDA backend.
* G-API module:
+ Intel® OpenVINO™ DL inference backend:
- Introduced "inferenence only" ("benchmark") mode
in the OV2.0 backend.
- Fixed model layout setting issue in the OV2.0 backend.
- Fixed/relaxed various asserts in the OV2.0 backend.
+ Core and image processing functionality:
- Fluid kernels were rewritten to new universal intrinsics.
Thanks for this contribution!
+ Streaming and video functionality:
- Introduced a QueueSource: an alternative way to manually
push input frames to the G-API pipeline in the streaming
mode.
- Introduced VAS Object Tracker (OT) for the various video
analytics scenarios.
+ Python bindings:
- Exposed VAS OT in G-API Python bindings.
+ Other changes and fixes:
- Updated ADE (the G-API's graph library) to the latest
version.
- Various code clean-ups and warning fixes.
* Objdetect module:
+ Implemented own QR code decoder as replacement for QUIRC
library
+ Bug fixes in QR code encoder version estimation
+ More accurate Aruco marker corner refinement with
dynamic window
+ Fixed contour filtering in ArUco
+ QR code detection sample for Android
+ Multiple local bug fixes and documentation update for
Aruco makers, Charuco boards and QR codes.
* Video:
+ Google Summer of Code: added a new object tracking API
TrackerVit for a vision transformer-based VitTrack.
This work is done by LIU Pengyu.
* VideoIO:
+ Videoio: Add raw encoded video stream encapsulation
to cv::VideoWriter with CAP_FFMPEG
+ Fix GStreamer backend with manual pipelines.
* Calibration module:
+ Multiple fixes and improvements chess board calibration
rig detector.
+ calibrateCamera throws exception, if calibration system
is underconstrained.
+ Fixed bug in findEssentialMat with USAC
+ Fixed out-of-image access in cv::cornerSubPix
+ Fixed crash in ap3p
+ Fixed stereoRectify image boundaries
+ Fixed "use after free" issue in essential_solver.cpp
* Python Bindings:
+ Added type stub generation for missed types and manually
wrapped types.
+ Added read-only flag handling for Numpy arrays.
+ Fixed exception handling and bindings for in module.
+ Improved error messages in Numpy array type handling.
+ Fixed constructors documentation in Python.
* Platforms and hardware Support:
+ Experimental CUDA support as first class language in CMake
+ Added experimental support for Apple VisionOS platform
+ Add support Orbbec Gemini2 and Gemini2 XL camera
+ Fix fullscreen behavior on macOS
* Other:
+ OpenCV Summer of Code: semi-automated refactoring across
multiple pull requests by HAN Liutong made our CPU-optimized
code compatible with SIMD with variable vector
length (RISC-V RVV)
OBS-URL: https://build.opensuse.org/request/show/1139607
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=37
2024-01-19 20:46:30 +01:00
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%define soname 409
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2017-07-11 08:24:11 +02:00
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# disabled by default as many fail
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Accepting request 860308 from home:StefanBruens:branches:science
- update to 4.5.1, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version451
* Continued merging of GSoC 2020 results:
+ Develop OpenCV.js DNN modules for promising web use cases
together with their tutorials
+ OpenCV.js: WASM SIMD optimization 2.0
+ High Level API and Samples for Scene Text Detection and
Recognition
+ SIFT: SIMD optimization of GaussianBlur 16U
* DNN module:
+ Improved layers / activations / supported more models:
- optimized: 1D convolution, 1D pool
- fixed: Resize, ReduceMean, Gather with multiple outputs,
importing of Faster RCNN ONNX model
- added support: INT32 ONNX tensors
+ Intel® Inference Engine backend (OpenVINO):
- added support for OpenVINO 2021.2 release
- added preview support for HDDL
+ Fixes and optimizations in DNN CUDA backend (thanks to
@YashasSamaga)
* G-API Framework:
+ Introduced serialization for cv::RMat, including
serialization for user-defined memory adapters
+ Introduced desync, a new Operation for in-graph asynchronous
execution - to allow different parts of the graph run with
a different latency
+ Introduced a notion of "in-graph metadata", now various
media-related information can be accessed in graph directly
(currently only limited to timestamps and frame IDs)
+ Introduced a new generic task-based executor, based on
Threading Building Blocks (TBB)
+ Extended infer<>() API to accept a new cv::GFrame data
structure to allow handling of various media formats without
changes in the graph structure
+ Made copy() an intrinsic where real copy may not happen
(optimized out) based on graph structure, extended it to
support cv::GFrame
+ Various fixes, including addressig static analysis,
documentation, and test issues
* G-API Operations:
+ Introduced new operations morphologyEx, boundingRect,
fitLine, kmeans, Background Subtractor, Kalman filter
* G-API Intel® Inference Engine backend (OpenVINO):
+ Extended cv::gapi::ie::Params<> to import CNN networks (e.g.
pre-compiled ones) instead of passing .XML and .BIN files;
also enabled configuring Inference Engine plugins via
this structure
+ Added a new overload to infer<>() to run inference over a
single region of interest
+ Added support for cv::MediaFrame input data type (projected
from cv::GFrame) and handling for NV12 input image format
* G-API Python bindings:
+ Exposed G-API's Inference and Streaming APIs in the OpenCV
Python bindings
+ Added initial Python support for cv::GArray data structure
* Significant progress on RISC-V port.
- Updated constraints, bump memory to 5 GB
- Cleaned up spec file
OBS-URL: https://build.opensuse.org/request/show/860308
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=23
2021-01-04 20:56:22 +01:00
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%bcond_with tests
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2019-10-13 13:42:06 +02:00
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%bcond_without gapi
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2017-07-11 08:24:11 +02:00
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%bcond_without ffmpeg
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2018-01-16 09:32:34 +01:00
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%bcond_without python3
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2018-06-02 11:53:10 +02:00
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%bcond_without openblas
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2024-02-05 08:31:49 +01:00
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%if %{with python3}
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# Enable python311 for SLE15 in addition to the regular python3 which is python 3.6
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%{?sle15allpythons}
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%endif
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2013-08-01 15:56:40 +02:00
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Name: opencv
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Accepting request 1139607 from home:cabelo:branches:science
- update to 4.9.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version490
Highlights of this release:
* Core Module:
+ Added cv::broadcast
+ Fixed several rounding issues on ARM platform
+ Added detection & dispatching of some modern NEON
instructions (NEON_FP16, NEON_BF16)
+ Added optimization for LoongArch 128-bit vector,
detection & dispatching of LoongArch
* DNN module patches:
+ Experimental transformers support
+ ONNX Attention layer support
+ ONNX Einsum layer support
+ OpenVINO backend for INT8 models
+ ONNX Gather Elements layer
+ ONNX InstanceNorm layer
+ Better support of ONNX Expand layer with cv::broadcast
+ Improved DNN graph fusion with shared nodes and commutative
operations
+ New fastGEMM implementation and several layers on top of it
+ Winograd fp16 optimizations on ARM
+ Tests and multiple fixes for Yolo family models support
+ New layers support and bug fixes in CUDA backend: GEMM,
Gelu, Add
+ CANN backend: bug fix, support HardSwish,
LayerNormalization and InstanceNormalization
+ LayerNormalization: support OpenVINO, OpenCL and
CUDA backend.
* G-API module:
+ Intel® OpenVINO™ DL inference backend:
- Introduced "inferenence only" ("benchmark") mode
in the OV2.0 backend.
- Fixed model layout setting issue in the OV2.0 backend.
- Fixed/relaxed various asserts in the OV2.0 backend.
+ Core and image processing functionality:
- Fluid kernels were rewritten to new universal intrinsics.
Thanks for this contribution!
+ Streaming and video functionality:
- Introduced a QueueSource: an alternative way to manually
push input frames to the G-API pipeline in the streaming
mode.
- Introduced VAS Object Tracker (OT) for the various video
analytics scenarios.
+ Python bindings:
- Exposed VAS OT in G-API Python bindings.
+ Other changes and fixes:
- Updated ADE (the G-API's graph library) to the latest
version.
- Various code clean-ups and warning fixes.
* Objdetect module:
+ Implemented own QR code decoder as replacement for QUIRC
library
+ Bug fixes in QR code encoder version estimation
+ More accurate Aruco marker corner refinement with
dynamic window
+ Fixed contour filtering in ArUco
+ QR code detection sample for Android
+ Multiple local bug fixes and documentation update for
Aruco makers, Charuco boards and QR codes.
* Video:
+ Google Summer of Code: added a new object tracking API
TrackerVit for a vision transformer-based VitTrack.
This work is done by LIU Pengyu.
* VideoIO:
+ Videoio: Add raw encoded video stream encapsulation
to cv::VideoWriter with CAP_FFMPEG
+ Fix GStreamer backend with manual pipelines.
* Calibration module:
+ Multiple fixes and improvements chess board calibration
rig detector.
+ calibrateCamera throws exception, if calibration system
is underconstrained.
+ Fixed bug in findEssentialMat with USAC
+ Fixed out-of-image access in cv::cornerSubPix
+ Fixed crash in ap3p
+ Fixed stereoRectify image boundaries
+ Fixed "use after free" issue in essential_solver.cpp
* Python Bindings:
+ Added type stub generation for missed types and manually
wrapped types.
+ Added read-only flag handling for Numpy arrays.
+ Fixed exception handling and bindings for in module.
+ Improved error messages in Numpy array type handling.
+ Fixed constructors documentation in Python.
* Platforms and hardware Support:
+ Experimental CUDA support as first class language in CMake
+ Added experimental support for Apple VisionOS platform
+ Add support Orbbec Gemini2 and Gemini2 XL camera
+ Fix fullscreen behavior on macOS
* Other:
+ OpenCV Summer of Code: semi-automated refactoring across
multiple pull requests by HAN Liutong made our CPU-optimized
code compatible with SIMD with variable vector
length (RISC-V RVV)
OBS-URL: https://build.opensuse.org/request/show/1139607
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=37
2024-01-19 20:46:30 +01:00
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Version: 4.9.0
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2012-01-04 07:25:38 +01:00
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Release: 0
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2011-07-07 14:28:27 +02:00
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Summary: Collection of algorithms for computer vision
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2018-06-02 11:53:10 +02:00
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# GPL-2.0 AND Apache-2.0 files are in 3rdparty/ittnotify which is not build
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License: BSD-3-Clause AND GPL-2.0-only AND Apache-2.0
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2011-10-18 14:24:16 +02:00
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Group: Development/Libraries/C and C++
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2019-08-11 17:12:15 +02:00
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URL: https://opencv.org/
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2017-11-19 11:08:51 +01:00
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Source0: https://github.com/opencv/opencv/archive/%{version}.tar.gz#/%{name}-%{version}.tar.gz
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2021-12-26 02:29:53 +01:00
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# Several modules from the opencv_contrib package
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2018-06-02 11:53:10 +02:00
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Source1: https://github.com/opencv/opencv_contrib/archive/%{version}.tar.gz#/opencv_contrib-%{version}.tar.gz
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2011-07-07 14:28:27 +02:00
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BuildRequires: cmake
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2011-10-18 14:24:16 +02:00
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BuildRequires: fdupes
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2013-08-01 15:56:40 +02:00
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BuildRequires: libeigen3-devel
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2017-07-11 08:24:11 +02:00
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BuildRequires: libjpeg-devel
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2022-03-31 23:51:33 +02:00
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BuildRequires: memory-constraints
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2017-07-11 08:24:11 +02:00
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BuildRequires: pkgconfig
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Accepting request 814492 from home:StefanBruens:branches:science
- Update to 4.3.0
* DNN module:
+ Improved layers / activations / supported more models:
- ONNX: LSTM, Broadcasting, Algebra over constants, Slice with
multiple inputs
- DarkNet: grouped convolutions, sigmoid, swish, scale_channels
- MobileNet-SSD v3: #16760
+ New samples / demos:
- Clothes parts segmentation and CP-VTON
- DaSiamRPN tracker
Intel® Inference Engine backend (OpenVINO™):
- added support for custom layers through nGraph OpenVINO
API: #16628
- nGraph OpenVINO API is used by default: #16746
+ Many fixes and optimizations in CUDA backend (thanks to
@YashasSamaga)
+ OPEN AI LAB team submitted the patch that accelerates OpenCV
DNN on ARM using their Tengine library
* G-API module:
+ Introduced a new graph-level data type GOpaque<T>. This type
can be used to pass arbitrary user data types between G-API
nodes in the graph (supported for CPU/OpenCV backend only).
+ Introduced a way to declare G-API CPU (OpenCV) kernels in-place
+ Added a new sample "Privacy masking camera", combining Deep
Learning with traditional Image Processing (link)
+ Added more operations in the default library: WarpAffine,
WarpPerspective, NV12toGray.
* Performance improvements:
+ IPP-ICV library with CPU optimizations has been updated to
version 2020.0.0 Gold
+ SIMD intrinsics: integral, resize, (opencv_contrib) RLOF
implementation #2476
* And many other great contributions from OpenCV community:
+ (opencv_contrib) Computer Vision based Alpha Matting
(GSoC 2019) #2306
+ calib3d: findChessboardCornersSB improvements: #16625
+ calib3d: updated documentation for RT matrices: #16860
+ core: improved getNumberOfCPUs(): #16268
+ imgproc: new algorithm HOUGH_GRADIENT_ALT is added to
HoughCircles() function #16561. It has much better recall
and precision
+ imgcodecs: added initial support for OpenJPEG library
(version 2+): #16494
+ highgui(Qt): added Copy to clipboard: #16677
+ dnn: TensorFlow, Darknet and ONNX importers improvements
by @ashishkrshrivastava
+ (opencv_contrib) added rapid module for silhouette based 3D
object tracking: #2356
+ (opencv_contrib) SIFT detector is enabled by default due
patents expiration (without requirement of NONFREE build
option)
+ help materials: OpenCV Cheat Sheet in Python: #4875
* Changes that can potentially break compatibility:
+ image filtering functions throws exception on empty input
(voting results)
- Packaging changes:
* Stop mangling CMake diagnostic output, no dependency versions
end up in the packages anyway, drop opencv-build-compare.patch
* Set empty OPENCV_DOWNLOAD_TRIES_LIST, skip downloads even when
network is available during builds (e.g. local build).
* Drop upstream GLES patches:
+ 0001-Do-not-include-glx.h-when-using-GLES.patch
+ opencv-gles.patch
OBS-URL: https://build.opensuse.org/request/show/814492
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=15
2020-06-14 22:35:02 +02:00
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Accepting request 814492 from home:StefanBruens:branches:science
- Update to 4.3.0
* DNN module:
+ Improved layers / activations / supported more models:
- ONNX: LSTM, Broadcasting, Algebra over constants, Slice with
multiple inputs
- DarkNet: grouped convolutions, sigmoid, swish, scale_channels
- MobileNet-SSD v3: #16760
+ New samples / demos:
- Clothes parts segmentation and CP-VTON
- DaSiamRPN tracker
Intel® Inference Engine backend (OpenVINO™):
- added support for custom layers through nGraph OpenVINO
API: #16628
- nGraph OpenVINO API is used by default: #16746
+ Many fixes and optimizations in CUDA backend (thanks to
@YashasSamaga)
+ OPEN AI LAB team submitted the patch that accelerates OpenCV
DNN on ARM using their Tengine library
* G-API module:
+ Introduced a new graph-level data type GOpaque<T>. This type
can be used to pass arbitrary user data types between G-API
nodes in the graph (supported for CPU/OpenCV backend only).
+ Introduced a way to declare G-API CPU (OpenCV) kernels in-place
+ Added a new sample "Privacy masking camera", combining Deep
Learning with traditional Image Processing (link)
+ Added more operations in the default library: WarpAffine,
WarpPerspective, NV12toGray.
* Performance improvements:
+ IPP-ICV library with CPU optimizations has been updated to
version 2020.0.0 Gold
+ SIMD intrinsics: integral, resize, (opencv_contrib) RLOF
implementation #2476
* And many other great contributions from OpenCV community:
+ (opencv_contrib) Computer Vision based Alpha Matting
(GSoC 2019) #2306
+ calib3d: findChessboardCornersSB improvements: #16625
+ calib3d: updated documentation for RT matrices: #16860
+ core: improved getNumberOfCPUs(): #16268
+ imgproc: new algorithm HOUGH_GRADIENT_ALT is added to
HoughCircles() function #16561. It has much better recall
and precision
+ imgcodecs: added initial support for OpenJPEG library
(version 2+): #16494
+ highgui(Qt): added Copy to clipboard: #16677
+ dnn: TensorFlow, Darknet and ONNX importers improvements
by @ashishkrshrivastava
+ (opencv_contrib) added rapid module for silhouette based 3D
object tracking: #2356
+ (opencv_contrib) SIFT detector is enabled by default due
patents expiration (without requirement of NONFREE build
option)
+ help materials: OpenCV Cheat Sheet in Python: #4875
* Changes that can potentially break compatibility:
+ image filtering functions throws exception on empty input
(voting results)
- Packaging changes:
* Stop mangling CMake diagnostic output, no dependency versions
end up in the packages anyway, drop opencv-build-compare.patch
* Set empty OPENCV_DOWNLOAD_TRIES_LIST, skip downloads even when
network is available during builds (e.g. local build).
* Drop upstream GLES patches:
+ 0001-Do-not-include-glx.h-when-using-GLES.patch
+ opencv-gles.patch
OBS-URL: https://build.opensuse.org/request/show/814492
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=15
2020-06-14 22:35:02 +02:00
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Accepting request 889708 from home:StefanBruens:branches:science
- update to 4.5.2, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version452
* core: added support for parallel backends.
* imgproc: added IntelligentScissors implementation (JS demo).
* videoio: improved hardware-accelerated video de-/encoding tasks.
* DNN module:
+ Improved debugging of TensorFlow parsing errors: #19220
+ Improved layers / activations / supported more models:
- optimized: NMS processing, DetectionOutput
- fixed: Div with constant, MatMul, Reshape
(TensorFlow behaviour)
- added support: Mish ONNX subgraph, NormalizeL2 (ONNX),
LeakyReLU (TensorFlow), TanH + SAM (Darknet), Exp
+ Intel® Inference Engine backend ( OpenVINO™ ):
added support for OpenVINO 2021.3 release
* G-API module:
+ Python support:
- Introduced a new Python backend - now G-API can run custom
kernels written in Python as part of the pipeline: #19351
- Extended Inference support in the G-API bindings: #19318
- Added more graph data types in the G-API bindings: #19319
+ Inference support:
- Introduced dynamic input / CNN reshape functionality in the
OpenVINO inference backend #18240
- Introduced asynchronous execution support in the OpenVINO
inference backend, now it can run in multiple parallel
requests to increase stream density/throughput: #19487, #19425
- Extended supported data types with INT64/INT32 in ONNX
inference backend and with INT32 in the OpenVINO inference
backend #19792
- Introduced cv::GFrame / cv::MediaFrame and constant support
in the ONNX backend: #19070
+ Media support:
- Introduced cv::GFrame / cv::MediaFrame support in the
drawing/rendering interface: #19516
- Introduced multi-stream input support in Streaming mode
and frame synchronization policies to support cases like
Stereo: #19731
- Added Y and UV operations to access NV12 data of cv::GFrame
at the graph level; conversions are done on-the-fly if the
media format is different: #19325
+ Operations and kernels:
- Added performance tests for new operations (MorphologyEx,
BoundingRect, FitLine, FindContours, KMeans, Kalman,
BackgroundSubtractor)
- Fixed RMat input support in the PlaidML backend: #19782
- Added ARM NEON optimizations for Fluid AbsDiffC, AddWeighted,
and bitwise operations: #18466, #19233
- Other various static analysis and warning fixes
+ Documentation:
- [GSoC] Added TF/PyTorch classification conversion: #17604
- [GSoC] Added TF/PyTorch segmentation conversion: #17801
- [GSoC] Added TF/PyTorch detection model conversion: #18237
- Updated documentation to address Wide Universal Intrinsics
(WUI) SIMD API: #18952
+ And many other great contributions from OpenCV community:
- core: cuda::Stream constructor with stream flags: #19286
- highgui: pollKey() implementation for w32 backend: #19411
- imgcodecs: Added Exif parsing for PNG: #19439
- imgcodecs: OpenEXR compression options: #19540
- imgproc: connectedComponents optimizations: (Spaghetti
Labeling): #19631
- videoio: Android NDK camera support #19597
- (contrib) WeChat QRCode module open source: #2821
- (contrib) Implemented cv::cuda::inRange(): #2803
- (contrib) Added algorithms from Edge Drawing Library: #2313
- (contrib) Added Python bindings for Viz module: #2882
- Add libva build dependency for HW accelerated videoio
- Slight bump for memory constraints
OBS-URL: https://build.opensuse.org/request/show/889708
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=25
2021-05-04 13:50:28 +02:00
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Accepting request 714221 from science
- Update to version 4.1.0
* DNN module:
+ Reduced peak memory consumption for some models up to 30%.
+ Inference Engine
- Inference Engine 2018R3 is now a minimal supported version of IE.
- Myriad X (Intel® Neural Compute Stick 2) is now supported and tested.
- Automatic IR network reshaping for different inputs.
- Improved samples to work with models from OpenVINO Open Model Zoo
+ New networks from TensorFlow Object Detection API: Faster-RCNNs, SSDs
and Mask-RCNN with dilated convolutions, FPN SSD
* Performance improvements:
+ More optimization using AVX2 instruction set.
+ Automatic runtime dispatching is available for large set of functions
from core and imgproc modules.
* Other improvements:
+ Matplotlib Perceptually Uniform Sequential colormaps
+ Add keypoints matching visualization for real-time pose estimation tutorial
+ Add Hand-Eye calibration methods
+ Java: improved support for multidimensional arrays (Mat)
+ Dynamically loaded videoio backends (FFmpeg, GStreamer)
+ opencv_contrib: Robust local optical flow (RLOF) implementations
+ opencv_contrib: Implementation of Quasi Dense Stereo algorithm
+ opencv_contrib: New module: Image Quality Analysis (IQA) API
+ opencv_contrib: BRISQUE No Reference Image Quality Assessment (IQA) API
Check https://github.com/opencv/opencv/wiki/ChangeLog#version410
- Update to version 4.0.0
* A lot of C API from OpenCV 1.x has been removed. The affected modules are
objdetect, photo, video, videoio, imgcodecs, calib3d.
* Persistence (storing and loading structured data to/from XML, YAML or JSON)
in the core module has been completely reimplemented.
* OpenCV is now C++11 library and requires C++11-compliant compiler.
Thanks to the extended C++11 standard library, we could get rid of hand-crafted
cv::String and cv::Ptr. Now cv::String == std::string and cv::Ptr is a thin
wrapper on top of std::shared_ptr. Also, on Linux/BSD for cv::parallel_for_
we now use std::thread's instead of pthreads.
* DNN improvements
* Completely new module opencv_gapi has been added. It is the engine for very
efficient image processing, based on lazy evaluation and on-fly construction.
* Performance improvements
A few hundreds of basic kernels in OpenCV have been rewritten using so-called
"wide universal intrinsics". Those intrinsics map to SSE2, SSE4, AVX2, NEON or
VSX intrinsics, depending on the target platform and the compile flags.
* QR code detector and decoder have been added to opencv/objdetect module.
* The popular Kinect Fusion algorithm has been implemented, optimized for CPU and
GPU (OpenCL), and integrated into opencv_contrib/rgbd module.
* Very efficient and yet high-quality DIS dense optical flow algorithm has been
moved from opencv_contrib to opencv, video module. See the example.
* The slower TV L1 optical flow algorithm has been moved to opencv_contrib.
Check https://github.com/opencv/opencv/wiki/ChangeLog#version400
- Drop obsolete opencv-lib_suffix.patch
- Add 0001-Handle-absolute-OPENCV_INCLUDE_INSTALL_PATH-correctl.patch
- As this is a major version upgrade, the old 3.4.x package is still
available as opencv3
- Update to 3.4.3
* Compatibility fixes with python 3.7
* Added a new computational target DNN_TARGET_OPENCL_FP16
* Extended support of Intel's Inference Engine backend
* Enabled import of Intel's OpenVINO pre-trained networks from
intermediate representation (IR).
* tutorials improvements
Check https://github.com/opencv/opencv/wiki/ChangeLog#version343
for the complete changelog.
- Drop fix-build-i386-nosse.patch, build-workaround-issues-with-c.patch
(fixed upstream)
- Refresh patches
- Add patch to fix use of headers from C:
* build-workaround-issues-with-c.patch
- Update to 3.4.1:
* Added support for quantized TensorFlow networks
* OpenCV is now able to use Intel DL inference engine as DNN
acceleration backend
* Added AVX-512 acceleration to the performance-critical kernels
* For more information, read
https://github.com/opencv/opencv/wiki/ChangeLog#version341
- Update contrib modules to 3.4.1:
* No changelog available
- Change mechanism the contrib modules are built
- Include LICENSE of contrib tarball as well
- Build with python3 on >= 15
- Add patch to fix build on i386 without SSE:
* fix-build-i386-nosse.patch
- Refresh patches:
* fix_processor_detection_for_32bit_on_64bit.patch
* opencv-build-compare.patch
- Mention all libs explicitly
- Rebase 3.4.0 update from i@marguerite.su
- update to 3.4.0
* Added faster R-CNN support
* Javascript bindings have been extended to
cover DNN module
* DNN has been further accelerated for iGPU
using OpenCL
* On-disk caching of precompiled OpenCL
kernels has been finally implemented
* possible to load and run pre-compiled
OpenCL kernels via T-API
* Bit-exact 8-bit and 16-bit resize has been
implemented (currently supported only
bilinear interpolation)
- update face module to 3.4.0
- add opencv-lib_suffix.patch, remove LIB_SUFFIX
from OPENCV_LIB_INSTALL_PATH, as CMAKE_INSTALL
_LIBDIR is arch dependent.
- Add option to build without openblas
- Add conditionals for python2 and python3 to allow us enabling
only desired python variants when needed
- Do not depend on sphinx as py2 and py3 seem to collide there
- Readd opencv-gles.patch, it is *not* included upstream; otherwise
build breaks on all GLES Qt5 platforms (armv6l, armv7l, aarch64)
- add fix_processor_detection_for_32bit_on_64bit.patch
- Correctly set optimizations and dynamic dispatch on ARM, use
OpenCV 3.3 syntax on x86.
- Update licensing information
- change requires of python-numpy-devel to build in Leap and
to not break factory in future
- fix build error/unresolvable for Leap 42.2 and 42.3
- Update to version 3.3.1:
* Lots of various bugfixes
- Update source url
- Rename python subpackage to python2
- Do not explicitly require python-base for python subpackages
- Update to 3.3
- Dropped obsolete patches
* opencv-gcc6-fix-pch-support-PR8345.patch
* opencv-gles.patch
- Updated opencv-build-compare.patch
- Add 0001-Do-not-include-glx.h-when-using-GLES.patch
Fix build for 32bit ARM, including both GLES and desktop GL headers
causes incompatible pointer type errors
- Add conditional for the qt5/qt4 integration
* This is used only for gui tools, library is not affected
- Add provides/obsoletes for the qt5 packages to allow migration
- Drop patch opencv-qt5-sobump.diff
* Used only by the obsoleted qt5 variant
- Cleanup a bit with spec-cleaner
- Use %cmake macros
- Remove the conditions that are not really needed
- Add tests conditional disabled by default
* Many tests fail and there are missing testdata
- Switch to pkgconfig style dependencies
- Update to OpenCV 3.2.0
- Results from 11 GSoC 2016 projects have been submitted to the library:
+ sinusoidal patterns for structured light and phase unwrapping module
[Ambroise Moreau (Delia Passalacqua)]
+ DIS optical flow (excellent dense optical flow algorithm that is both
significantly better and significantly faster than Farneback’s algorithm –
our baseline), and learning-based color constancy algorithms implementation
[Alexander Bokov (Maksim Shabunin)]
+ CNN based tracking algorithm (GOTURN) [Tyan Vladimir (Antonella Cascitelli)]
+ PCAFlow and Global Patch Collider algorithms implementation
[Vladislav Samsonov (Ethan Rublee)]
+ Multi-language OpenCV Tutorials in Python, C++ and Java
[João Cartucho (Vincent Rabaud)]
+ New camera model and parallel processing for stitching pipeline
[Jiri Horner (Bo Li)]
+ Optimizations and improvements of dnn module
[Vitaliy Lyudvichenko (Anatoly Baksheev)]
+ Base64 and JSON support for file storage. Use names like
“myfilestorage.xml?base64” when writing file storage to store big chunks of
numerical data in base64-encoded form. [Iric Wu (Vadim Pisarevsky)]
+ tiny_dnn improvements and integration
[Edgar Riba (Manuele Tamburrano, Stefano Fabri)]
+ Quantization and semantic saliency detection with tiny_dnn
[Yida Wang (Manuele Tamburrano, Stefano Fabri)]
+ Word-spotting CNN based algorithm
[Anguelos Nicolaou (Lluis Gomez)]
- Contributions besides GSoC:
+ Greatly improved and accelerated dnn module in opencv_contrib:
- Many new layers, including deconvolution, LSTM etc.
- Support for semantic segmentation and SSD networks with samples.
- TensorFlow importer + sample that runs Inception net by Google.
+ More image formats and camera backends supported
+ Interactive camera calibration app
+ Multiple algorithms implemented in opencv_contrib
+ Supported latest OSes, including Ubuntu 16.04 LTS and OSX 10.12
+ Lot’s of optimizations for IA and ARM archs using parallelism, vector
instructions and new OpenCL kernels.
+ OpenCV now can use vendor-provided OpenVX and LAPACK/BLAS (including Intel MKL,
Apple’s Accelerate, OpenBLAS and Atlas) for acceleration
- Refreshed opencv-build-compare.patch
- Dropped upstream opencv-gcc5.patch
- Replace opencv-gcc6-disable-pch.patch with upstream patch
opencv-gcc6-fix-pch-support-PR8345.patch
- Enable TBB support (C++ threading library)
- Add dependency on openBLAS
- Enable ffmpeg support unconditional
- In case we build using GCC6 (or newer), add -mlra to CFLAGS to
workaround gcc bug
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=71294.
- Apply upstream patch opencv-gcc6-disable-pch.patch to disable
PCH for GCC6.
- Test for python versions greater than or equal to the current
version.
- Add python 3 support
- Added opencv_contrib_face-3.1.0.tar.bz2
* This tarball is created to take only the face module from the
contrib package. The Face module is required by libkface, which
in its turn is required by digikam.
- Added _constraints file to avoid random failures on small workers
(at least for builds on PMBS)
- Update to OpenCV 3.1.0
- A lot of new functionality has been introduced during Google
Summer of Code 2015:
+ “Omnidirectional Cameras Calibration and Stereo 3D
Reconstruction” – opencv_contrib/ccalib module
(Baisheng Lai, Bo Li)
+ “Structure From Motion” – opencv_contrib/sfm module
(Edgar Riba, Vincent Rabaud)
+ “Improved Deformable Part-based Models” – opencv_contrib/dpm
module (Jiaolong Xu, Bence Magyar)
+ “Real-time Multi-object Tracking using Kernelized Correlation
Filter” – opencv_contrib/tracking module
(Laksono Kurnianggoro, Fernando J. Iglesias Garcia)
+ “Improved and expanded Scene Text Detection” –
opencv_contrib/text module (Lluis Gomez, Vadim Pisarevsky)
+ “Stereo correspondence improvements” – opencv_contrib/stereo
module (Mircea Paul Muresan, Sergei Nosov)
+ “Structured-Light System Calibration” –
opencv_contrib/structured_light (Roberta Ravanelli,
Delia Passalacqua, Stefano Fabri, Claudia Rapuano)
+ “Chessboard+ArUco for camera calibration” –
opencv_contrib/aruco (Sergio Garrido, Prasanna, Gary Bradski)
+ “Implementation of universal interface for deep neural
network frameworks” – opencv_contrib/dnn module
(Vitaliy Lyudvichenko, Anatoly Baksheev)
+ “Recent advances in edge-aware filtering, improved SGBM
stereo algorithm” – opencv/calib3d and opencv_contrib/ximgproc
(Alexander Bokov, Maksim Shabunin)
+ “Improved ICF detector, waldboost implementation” –
opencv_contrib/xobjdetect (Vlad Shakhuro, Alexander Bovyrin)
+ “Multi-target TLD tracking” – opencv_contrib/tracking module
(Vladimir Tyan, Antonella Cascitelli)
+ “3D pose estimation using CNNs” – opencv_contrib/cnn_3dobj
(Yida Wang, Manuele Tamburrano, Stefano Fabri)
- Many great contributions made by the community, such as:
+ Support for HDF5 format
+ New/Improved optical flow algorithms
+ Multiple new image processing algorithms for filtering,
segmentation and feature detection
+ Superpixel segmentation and much more
- IPPICV is now based on IPP 9.0.1, which should make OpenCV
even faster on modern Intel chips
- opencv_contrib modules can now be included into the
opencv2.framework for iOS
- Newest operating systems are supported: Windows 10 and
OSX 10.11 (Visual Studio 2015 and XCode 7.1.1)
- Interoperability between T-API and OpenCL, OpenGL, DirectX and
Video Acceleration API on Linux, as well as Android 5 camera.
- HAL (Hardware Acceleration Layer) module functionality has been
moved into corresponding basic modules; the HAL replacement
mechanism has been implemented along with the examples
- Removed improve-sphinx-search.diff, opencv-altivec-vector.patch,
opencv-pkgconfig.patch and opencv-samples.patch, fixed upstream.
- Fixed opencv-qt5-sobump.diff, opencv-build-compare.patch,
opencv-gcc5.patch and opencv-gles.patch.
- Version OpenCV 3.0.0
+ ~1500 patches, submitted as PR @ github. All our patches go
the same route.
+ opencv_contrib (http://github.com/itseez/opencv_contrib)
repository has been added. A lot of new functionality is there
already! opencv_contrib is only compatible with 3.0/master,
not 2.4. Clone the repository and use “cmake …
-D OPENCV_EXTRA_MODULES_PATH=<path_to opencv_contrib/modules> …”
to build opencv and opencv_contrib together.
+ a subset of Intel IPP (IPPCV) is given to us and our users free
of charge, free of licensing fees, for commercial and
non-commerical use. It’s used by default in x86 and x64 builds
on Windows, Linux and Mac.
+ T-API (transparent API) has been introduced, this is transparent
GPU acceleration layer using OpenCL. It does not add any
compile-time or runtime dependency of OpenCL. When OpenCL is
available, it’s detected and used, but it can be disabled at
compile time or at runtime. It covers ~100 OpenCV functions.
This work has been done by contract and with generous support
from AMD and Intel companies.
+ ~40 OpenCV functions have been accelerated using NEON intrinsics
and because these are mostly basic functions, some higher-level
functions got accelerated as well.
+ There is also new OpenCV HAL layer that will simplifies creation
of NEON-optimized code and that should form a base for the
open-source and proprietary OpenCV accelerators.
+ The documentation is now in Doxygen: http://docs.opencv.org/master/
+ We cleaned up API of many high-level algorithms from features2d,
calib3d, objdetect etc. They now follow the uniform
“abstract interface – hidden implementation” pattern and make
extensive use of smart pointers (Ptr<>).
+ Greatly improved and extended Python & Java bindings (also,
see below on the Python bindings), newly introduced Matlab
bindings (still in alpha stage).
+ Improved Android support – now OpenCV Manager is in Java and
supports both 2.4 and 3.0.
+ Greatly improved WinRT support, including video capturing and
multi-threading capabilities. Thanks for Microsoft team for this!
+ Big thanks to Google who funded several successive GSoC programs
and let OpenCV in. The results of many successful GSoC 2013 and
2014 projects have been integrated in opencv 3.0 and
opencv_contrib (earlier results are also available in
OpenCV 2.4.x). We can name:
- text detection
- many computational photography algorithms (HDR, inpainting,
edge-aware filters, superpixels, …)
- tracking and optical flow algorithms
- new features, including line descriptors, KAZE/AKAZE
- general use optimization (hill climbing, linear programming)
- greatly improved Python support, including Python 3.0 support,
many new tutorials & samples on how to use OpenCV with Python.
- 2d shape matching module and 3d surface matching module
- RGB-D module
- VTK-based 3D visualization module
- etc.
+ Besides Google, we enjoyed (and hope that you will enjoy too)
many useful contributions from community, like:
- biologically inspired vision module
- DAISY features, LATCH descriptor, improved BRIEF
- image registration module
- etc.
- Reduce build-compare noise
opencv-build-compare.patch
- Remove BuildRequirement for python-sphinx in SLE12, since it's
not available there and it's not a mandatory requirement.
- Reduce differences between two spec files
- Use pkgconfig for ffmpeg BuildRequires
- Update improve-sphinx-search.diff for new python-Sphinx(1.3.1)
* now that sphinx-build disallow executing without arguments and
give you "Insufficient arguments" error, use "sphinx-build -h"
instead
* the default usages output ie. sphinx-build(or --help) no longer
are standard error but standard output, drop OUTPUT_QUIET and
add OUTPUT_VARIABLE throws the output to SPHINX_OUTPUT as well
- support gcc 5 (i.e. gcc versions without minor version):
opencv-gcc5.patch
- Update to OpenCV 2.4.11 - can't find NEWS or Changelog
merely collecting bug fixes while 3.0 is in the making, 2.4.11
didn't even make it on their web page, it's only on download
server
- remove opencv-underlinking.patch as obsolete
- remove upstream patch bomb_commit_gstreamer-1x-support.patch
- commenting out opencv-pkgconfig.patch - possibly it requires a rebase,
but the problem it tries to solve is unclear
- Add specific buildrequires for libpng15, so that we are
building against the system provided libpng.
- Update to OpenCV 2.4.9
More info at:
http://opencv.org/opencv-2-4-9-is-out.html
The brief list of changes:
* new 3D visualization module ‘viz’;
* performance fixes in ‘ocl’ module;
* fixes in Android Camera;
* improved CUDA support for mobile platforms;
* bugfixes from community;
* 55 reported bugs have been closed;
* 156 pull requests have been merged.
- Drop the BuildRequires on libucil and libunicap for Factory. This
stops us from getting ride of Gstreamer 0.10 and besides these two
libraries seem to be unmaintained upstream as that the latest
actions are from 2010
- Add upstream patch (3.0 version) to support Gstreamer 1.x
* bomb_commit_gstreamer-1x-support.patch
- Upstream now provides tarballs with source only as git tags
from github so update Source0 path.
- Add requires on various X extensions linked to opencv_ts module.
As those are present in the .pc file we need it anyway.
- Update to OpenCV 2.4.8
More info at:
http://opencv.org/opencv-2-4-8.html
The brief list of changes:
* NVidia CUDA support on Android devices with CUDA capable SoC and
CUDA sample;
* Concurrent kernel execution and user defined context support for
OpenCL;
* Integration with Intel Perceptual SDK and new depth sensors support
for Windows;
* 32 reported bugs have been closed;
* 139 pull requests have been merged;
- Fix build with altivec:
opencv-altivec-vector.patch
- Added opencv-pkgconfig.patch: make sure to provide link flags in
OpenCV pc file (bnc#853036)
- Update to OpenCV 2.4.7
More info at:
http://opencv.org/opencv-2-4-7-is-out.html
The brief list of changes:
* dynamic OpenCL runtime loading, setting default OpenCL device
via env var, many bug-fixes and some new optimization with OpenCL
* bug-fixes and new optimizations in CUDA stuff
* latest NDK and Android OS support, Native Android Camera tuning
* minor fixes, XAML sample and MS Certification compatibility
in WinRT stuff
* 382 pull requests have been merged
* 54 reported bugs have been fixed
- Added pkgconfig(glu) Requires to devel package, as per .pc file
- Make devel package provides also devel-static one
- Drop assume-Sphinx-is-there.diff, and add improve-sphinx-search.diff,
for properly finding sphinx with alphabetic chars in version
- Add patch assume-Sphinx-is-there.diff to fix building with
Sphinx versions that have alphanumeric characters in the version
(Only for factory builds at the moment)
- Use eigen3 instead of eigen2 as build requirement for openSUSE > 12.3.
- Enable compilation with libucil and libunicap.
- Removed dos2unix build requirement (not needed anymore).
- Update to OpenCV 2.4.6.1
More info at:
http://opencv.org/opencv-2-4-6-is-out.html
The brief list of changes:
* added video file i/o Windows RT and sample application using
camera, enabled parallelization with TBB or MS Concurrency
* added CUDA 5.5 support for desktop and ARM systems
* added Qt 5 support
* added many new OpenCL algorithms ports, included OpenCL binaries
into the Windows superpack
* iOS build scripts (together with Android ones) moved to
‘opencv/platforms’ directory
* added functions for UIImage <-> cv::Mat conversion
* correct front/back camera selection in Android app framework
* added Linaro NDK support and fixes for MIPS to Android CMake
toolchain
* stability has been improved by a lot, numerous bug-fixes across
all the library
- build with LFS_CFLAGS in 32 bit archs.
- Disable SSE3 for all architectures (bnc#814333)
- Disable SSE(2) on non x86_64 architectures, causes crashing
kde#276923, bnc#789173
- Update to OpenCV 2.4.5
More info at:
http://opencv.org/opencv-2-4-5-is-out.html
The brief list of changes:
* experimental WinRT support
* new video super-resolution module
* CLAHE (adaptive histogram equalization) algorithm on both CPU
and GPU
* further improvements and extensions in ocl module
(stereo block matching and belief propagation have been added,
fixed crashes on Intel HD4000)
* Visual Studio 2012 cv::Mat visualizer plugin debugger tutorial
from Microsoft Research
* OpenCV4Android SDK improvements
(NDK r8e support, native activity sample using OpenCV Manager,
bug-fixes)
* ~25 reported problems have been resolved since 2.4.4, ~78 pull
requests have been merged, thanks everybody who participated!
- Update to OpenCV 2.4.4
More info at:
http://opencv.org/opencv-2-4-4-is-out.html
The brief list of changes:
* OpenCV Java bindings are ported from Android to desktop Java!
Actually any JVM language will work, see Tutorial for details,
and Java or Scala code samples.
* Android application framework, samples, tutorials, and OpenCV
Manager are improved.
* Optimizations for the new NVIDIA Kepler architecture, CARMA
platform support and other new optimizations in CUDA.
* OpenCL module now builds successfully with various SDKs (from
AMD, NVIDIA, Intel and Apple) and runs well on different GPUs
(AMD, NVidia, Intel HD4000). A lot of new functionality has been
added, tons of bugs fixed, performance of many functions has
been significantly improved.
* 100+ reported problems have been resolved since 2.4.3, thanks
everybody who participated!
- Drop the buildrequire for libxine
- Update to OpenCV 2.4.3
More info at:
http://opencv.org/opencv-2-4-3-released.html
The nicely formatted changelog can be seen here:
http://code.opencv.org/projects/opencv/wiki/ChangeLog;
here are the highlights:
* A lot of good stuff from the Google Summer of Code 2012 has been
integrated; this was a very productive summer!
* Significantly improved and optimized Android and iOS ports.
* Greatly extended GPU (i.e. CUDA-based) module.
* The brand new ocl (OpenCL-based) module that unleashes GPU power
also for AMD and Intel GPU users. It’s not included into the
binary package, since there are different SDKs, and it’s not
turned on by default. You need to run CMake and turn on
“WITH_OPENCL”. Also, please note that this is very first version
of the module, so it may be not very stable and not very
functional.
* Much better performance on many-core systems out of the box. You
do not need TBB anymore on MacOSX, iOS and Windows. BTW, the
binary package for Windows is now built without TBB support.
Libraries and DLLs for Visual Studio 2010 use the Concurrency
framework.
* About 130 bugs have been fixed since 2.4.2.
* Since 2.4.3rc we fixed several more problems, in particular some
compile problems with iOS 6 SDK.
- buildrequire glu
- Update to OpenCV 2.4.2
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Drop opencv-datadir.patch to comply with upstream directory layout
- Update to OpenCV 2.4.1
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Update to OpenCV 2.4.0
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Add opencv-gcc47.patch: Fix build with gcc 4.7.
- Use Explicit Buildrequires on several needed libraries
future dependency cleanups may/will cause build to fail otherwise.
- Add upstream r6881 to fix clang compatibility
- uncomment libraries not in 12.1 for now
- Changed groups (fix for RPMLINT warning)
- Added check for duplicate files (fix for RPMLINT warning)
- Added py_requires macros and python-base dependencies (fix for RPMLINT warning)
- Escaped macros (fix for RPMLINT warning)
- Fixed end-of-line encoding problems (fix for RPMLINT warning)
- Added libeigen2-devel buildrequires
- Added libunicap and libucil buildrequires (libunicap supports requires libucil)
- Cleaned up spec file formatting
- Dropped opencv-2.3-ffmpeg.patch, applied upstream
- Revive opencv-2.3-ffmpeg.patch, needs rebase
- Tag all patches according to openSUSE packaging guidelines
- Removed opencv-2.3-cmake.patch, old cmake cannot be used any more.
- Python bindings cannot be built without NumPy any more.
- Update to OpenCV 2.3.1
- Update and readd opencv-2.3-underlinking.patch since it is still
necessary.
- Fix support for new ffmpeg versions
- Removed unnecessary patches
- Enable Python NumPy support on openSUSE 11.2
- Build Qt instead of Gtk GUI
- Fix cmake files for openSUSE 11.1
- No GStreamer support on openSUSE 11.1
- Update to OpenCV 2.3.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Fix build on openSUSE 11.2
- Add opencv-v4l-2.6.38.patch: use the new libv4l2 interface
- Enable Python NumPy support
- SWIG is not required any more
- Enable OpenEXR support
- Update to OpenCV 2.2.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Use system zlib, oh, and do not export ZLIB symbols to
other applications, clashes ensued.
- fix build with gcc 4.6
- add -underlinking patch
- devel package renamed to opencv-devel, so that switching between
OBS and packman opencv packages is easier
- fix gstreamer support
- fix xine support
- fix some rpmlint warnings
- fix shared libraries permissions
- Do not waste resources building the tests as we do not run them
- Do not disable SSE,SSE2,etc. According to OpenCV changelog,
it should be safe to leave these enabled.
- fix build on openSUSE 11.0
- Update to OpenCV 2.1.0:
* The whole OpenCV is now using exceptions instead of the old
libc-style mechanism
* Experimental "static" OpenCV configuration in CMake was
contributed by Jose Luis Blanco.
Pass "BUILD_SHARED_LIBS=OFF" to CMake to build OpenCV statically.
* new improved version of one-way descriptor is added
* User can now control the image areas visible after the stereo
rectification
* Fullscreen has been added (thanks to Yannick Verdie).
* Further info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- fix build with libpng14
- small spec file cleanup
- Moved to the KDE repositories to enable inclusion in kipi-plugins
- Initial package
OBS-URL: https://build.opensuse.org/request/show/714221
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/opencv?expand=0&rev=73
2019-07-17 13:13:58 +02:00
|
|
|
Provides: opencv-qt5 = %{version}
|
|
|
|
|
Obsoletes: opencv-qt5 < %{version}
|
2019-08-11 17:12:15 +02:00
|
|
|
%if %{with gapi}
|
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|
BuildRequires: ade-devel >= 0.1.0
|
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|
|
%endif
|
2018-06-02 11:53:10 +02:00
|
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|
%if %{with openblas}
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BuildRequires: openblas-devel
|
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|
%endif
|
2018-01-16 09:32:34 +01:00
|
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|
%if %{with python3}
|
2021-12-26 02:29:53 +01:00
|
|
|
BuildRequires: python-rpm-macros
|
2024-02-05 08:31:49 +01:00
|
|
|
BuildRequires: %{python_module numpy-devel}
|
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|
|
BuildRequires: %{python_module devel}
|
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|
BuildRequires: %{python_module setuptools}
|
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|
%else
|
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BuildRequires: python3-base
|
2018-01-16 09:32:34 +01:00
|
|
|
%endif
|
2017-07-11 08:24:11 +02:00
|
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|
BuildRequires: pkgconfig(Qt5Concurrent) >= 5.2.0
|
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|
BuildRequires: pkgconfig(Qt5Gui) >= 5.2.0
|
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|
BuildRequires: pkgconfig(Qt5OpenGL) >= 5.2.0
|
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|
BuildRequires: pkgconfig(Qt5Test) >= 5.2.0
|
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|
BuildRequires: pkgconfig(Qt5Widgets) >= 5.2.0
|
2013-08-01 15:56:40 +02:00
|
|
|
%if %{with ffmpeg}
|
2016-07-28 23:43:33 +02:00
|
|
|
BuildRequires: pkgconfig(libavcodec)
|
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|
BuildRequires: pkgconfig(libavformat)
|
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|
BuildRequires: pkgconfig(libavutil)
|
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|
BuildRequires: pkgconfig(libswscale)
|
2013-08-01 15:56:40 +02:00
|
|
|
%endif
|
2024-02-05 08:31:49 +01:00
|
|
|
%if %{with python3}
|
|
|
|
|
%if "%pythons" != "python3"
|
|
|
|
|
# For Tumbleweed and SLE15 with activated multiflavor
|
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|
%define python_subpackage_only 1
|
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|
%python_subpackages
|
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|
%else
|
|
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|
|
# For old SLE15 with only python3 and possibly old python-rpm-macros
|
|
|
|
|
%define python_sitearch %python3_sitearch
|
|
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|
|
%define python_files() -n python3-%{**}
|
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|
|
%endif
|
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|
|
|
%endif
|
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|
2010-12-14 10:27:03 +01:00
|
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|
2010-03-08 18:16:50 +01:00
|
|
|
%description
|
2019-08-28 18:59:01 +02:00
|
|
|
OpenCV means Intel Open Source Computer Vision Library. It is a collection of C
|
2010-03-08 18:16:50 +01:00
|
|
|
functions and a few C++ classes that implement some popular Image Processing and
|
|
|
|
|
Computer Vision algorithms.
|
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|
|
2020-11-03 06:51:22 +01:00
|
|
|
%package -n %{name}4-cascades-data
|
2020-11-03 06:17:42 +01:00
|
|
|
Summary: Classifier cascades for OpenCV
|
|
|
|
|
License: BSD-3-Clause
|
|
|
|
|
Group: System/Libraries
|
Accepting request 983700 from home:StefanBruens:branches:science
- update to 4.6.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version460
* OpenCV project infrastructure migrating on GitHub Actions
workflows for CI and release purposes
* Added support for GCC 12, Clang 15
* Added support for FFmpeg 5.0
* DNN module patches:
+ Improved layers / activations / supported more models:
- LSTM (+CUDA), resize (+ONNX13), Sign, Shrink, Reciprocal,
depth2space, space2depth
- fixes in Reduce, Slice, Expand
+ Disabled floating-point denormals processing #21521
+ Changed layer names in ONNX importer to support "output"
entities properly
+ Added TIM-VX NPU backend support:
https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU
+ Added Softmax parameter to ClassificationModel
+ Added audio speech recognition sample (C++) #21458
+ Intel® Inference Engine backend (OpenVINO):
- added initial support for OpenVINO 2022.1 release
- removed support of legacy API (dropped since 2020.3)
* G-API module:
+ G-API framework:
- Introduced a Grayscale image format support for
cv::MediaFrame: #21511;
- Enabeled .reshape() support in the CPU backend: #21669;
- Fixed possible hang in streaming execution mode with constant
inputs: #21567;
- Introduced proper error/exception propagation in the
asynchronous streaming execution mode: #21660;
- Fixed new stream event handling: #21731.
+ Fluid backend:
- Fixed horizontal pass in the Resize kernel, fixed Valgrind
issues: #21144;
- Extended Resize kernel with F32 version: #21678,
added AVX: #21728.
- Enabled dynamic dispatch for Split4 kernel: #21520;
- Enabled dynamic dispatch for Merge3 kernel: #21529;
- Added a SIMD version for DivC kernel: #21474;
- Added a SIMD version for DivRC kernel: #21530;
- Enabled dynamic dispatch for Add kernel: #21686;
- Enabled dynamic dispatch for Sub kernel: #21746;
- Added a SIMD version for ConvertTo kernel: #21777;
- Fixed kernel matrix size for Sobel kernel: #21613.
+ Intel® OpenVINO™ inference backend:
- Fixed NV12 format support for remote memory when OpenVINO
remote context is used: #21424.
- Implemented correct error handling in the backend: #21579.
- Fixed ngraph warnings #21362.
+ OpenCV AI Kit backend:
- Introduced a new backend to program OpenCV AI Kit boards via
G-API. Currently the backend is in experimental state, but allows
to build Camera+NN pipeline and supports heterogeneity (mixing
with host-side code): #20785, #21504.
+ Media integration:
- Enabled GPU inference with oneVPL and DirectX11 on Windows in
Intel OpenVINO inference backend: #21232, #21618, #21658, #21687,
#21688. Now GPU textures decoded by oneVPL decoder can be
preprocessed and inferred on GPU with no extra host processing.
- Enabled oneVPL support on Linux: #21883.
- Extended GStreamer pipeline source with Grayscale image format
support: #21560.
+ Python bindings:
- Exposed GStreamer pipeline source in Python bindings: #20832.
- Fixed Python bindings for CudaBufferPool, cudacodec and cudastereo
modules in OpenCV Contrib.
+ Samples:
- Introduced a pipeline modelling tool for cascaded model
benchmarking: #21477, #21636, #21719. The tool supports a
declarative YAML-based config to describe pipelines with simulated
pre-/post-processing. The tool collects and reports latency and
throughput information for the modelled pipeline.
+ Other changes and fixes:
- Moved GKernelPackage into cv:: namespace by default, its cv::gapi::
alias remain for compatibility: #21318;
- Moved Resize kernel from core to imgproc kernel packages for
CPU, OpenCL, and Fluid backends: #21157. Also moved tests
appropriately: #21475;
- Avoided sporadic test failures in DivC: #21626;
- Fixed 1D Mat handling in the framework: #21782;
- Reduced the number of G-API generated accuracy tests: #21909.
- Drop upstream patches:
* 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
* videoio_initial_FFmpeg_5_0_support.patch
* videoio_ffmpeg_avoid_memory_leaks.patch
OBS-URL: https://build.opensuse.org/request/show/983700
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=33
2022-06-27 18:05:05 +02:00
|
|
|
Conflicts: %{name} < 4.5.1
|
2020-11-03 06:17:42 +01:00
|
|
|
Provides: %{name}:%{_datadir}/opencv4/lbpcascades/lbpcascade_silverware.xml
|
|
|
|
|
BuildArch: noarch
|
|
|
|
|
|
2020-11-03 06:51:22 +01:00
|
|
|
%description -n %{name}4-cascades-data
|
2020-11-03 06:17:42 +01:00
|
|
|
Haar and LBP cascades for face and object detecton
|
|
|
|
|
|
2010-03-08 18:16:50 +01:00
|
|
|
%package -n %{libname}%{soname}
|
2017-07-11 08:24:11 +02:00
|
|
|
Summary: Libraries to use OpenCV computer vision
|
2017-11-19 11:08:51 +01:00
|
|
|
License: BSD-3-Clause
|
2017-07-11 08:24:11 +02:00
|
|
|
Group: System/Libraries
|
2010-03-08 18:16:50 +01:00
|
|
|
|
|
|
|
|
%description -n %{libname}%{soname}
|
|
|
|
|
The Open Computer Vision Library is a collection of algorithms and sample code
|
|
|
|
|
for various computer vision problems. The library is compatible with IPL and
|
|
|
|
|
utilizes Intel Integrated Performance Primitives for better performance.
|
|
|
|
|
|
2021-02-22 20:10:19 +01:00
|
|
|
%package -n libopencv_aruco%{soname}
|
|
|
|
|
Summary: Pattern grid detection libraries for OpenCV
|
|
|
|
|
License: BSD-3-Clause
|
|
|
|
|
Group: System/Libraries
|
|
|
|
|
|
|
|
|
|
%description -n libopencv_aruco%{soname}
|
|
|
|
|
Pattern grid detectiion libraries for OpenCV
|
|
|
|
|
|
2020-11-03 06:17:42 +01:00
|
|
|
%package -n libopencv_face%{soname}
|
|
|
|
|
Summary: Face detection libraries for OpenCV
|
|
|
|
|
License: BSD-3-Clause
|
|
|
|
|
Group: System/Libraries
|
|
|
|
|
Conflicts: %{libname}%{soname} < %{version}-%{release}
|
2020-11-03 06:51:22 +01:00
|
|
|
Requires: %{name}4-cascades-data
|
2020-11-03 06:17:42 +01:00
|
|
|
|
|
|
|
|
%description -n libopencv_face%{soname}
|
|
|
|
|
Face detection libraries for OpenCV
|
|
|
|
|
|
Accepting request 983700 from home:StefanBruens:branches:science
- update to 4.6.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version460
* OpenCV project infrastructure migrating on GitHub Actions
workflows for CI and release purposes
* Added support for GCC 12, Clang 15
* Added support for FFmpeg 5.0
* DNN module patches:
+ Improved layers / activations / supported more models:
- LSTM (+CUDA), resize (+ONNX13), Sign, Shrink, Reciprocal,
depth2space, space2depth
- fixes in Reduce, Slice, Expand
+ Disabled floating-point denormals processing #21521
+ Changed layer names in ONNX importer to support "output"
entities properly
+ Added TIM-VX NPU backend support:
https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU
+ Added Softmax parameter to ClassificationModel
+ Added audio speech recognition sample (C++) #21458
+ Intel® Inference Engine backend (OpenVINO):
- added initial support for OpenVINO 2022.1 release
- removed support of legacy API (dropped since 2020.3)
* G-API module:
+ G-API framework:
- Introduced a Grayscale image format support for
cv::MediaFrame: #21511;
- Enabeled .reshape() support in the CPU backend: #21669;
- Fixed possible hang in streaming execution mode with constant
inputs: #21567;
- Introduced proper error/exception propagation in the
asynchronous streaming execution mode: #21660;
- Fixed new stream event handling: #21731.
+ Fluid backend:
- Fixed horizontal pass in the Resize kernel, fixed Valgrind
issues: #21144;
- Extended Resize kernel with F32 version: #21678,
added AVX: #21728.
- Enabled dynamic dispatch for Split4 kernel: #21520;
- Enabled dynamic dispatch for Merge3 kernel: #21529;
- Added a SIMD version for DivC kernel: #21474;
- Added a SIMD version for DivRC kernel: #21530;
- Enabled dynamic dispatch for Add kernel: #21686;
- Enabled dynamic dispatch for Sub kernel: #21746;
- Added a SIMD version for ConvertTo kernel: #21777;
- Fixed kernel matrix size for Sobel kernel: #21613.
+ Intel® OpenVINO™ inference backend:
- Fixed NV12 format support for remote memory when OpenVINO
remote context is used: #21424.
- Implemented correct error handling in the backend: #21579.
- Fixed ngraph warnings #21362.
+ OpenCV AI Kit backend:
- Introduced a new backend to program OpenCV AI Kit boards via
G-API. Currently the backend is in experimental state, but allows
to build Camera+NN pipeline and supports heterogeneity (mixing
with host-side code): #20785, #21504.
+ Media integration:
- Enabled GPU inference with oneVPL and DirectX11 on Windows in
Intel OpenVINO inference backend: #21232, #21618, #21658, #21687,
#21688. Now GPU textures decoded by oneVPL decoder can be
preprocessed and inferred on GPU with no extra host processing.
- Enabled oneVPL support on Linux: #21883.
- Extended GStreamer pipeline source with Grayscale image format
support: #21560.
+ Python bindings:
- Exposed GStreamer pipeline source in Python bindings: #20832.
- Fixed Python bindings for CudaBufferPool, cudacodec and cudastereo
modules in OpenCV Contrib.
+ Samples:
- Introduced a pipeline modelling tool for cascaded model
benchmarking: #21477, #21636, #21719. The tool supports a
declarative YAML-based config to describe pipelines with simulated
pre-/post-processing. The tool collects and reports latency and
throughput information for the modelled pipeline.
+ Other changes and fixes:
- Moved GKernelPackage into cv:: namespace by default, its cv::gapi::
alias remain for compatibility: #21318;
- Moved Resize kernel from core to imgproc kernel packages for
CPU, OpenCL, and Fluid backends: #21157. Also moved tests
appropriately: #21475;
- Avoided sporadic test failures in DivC: #21626;
- Fixed 1D Mat handling in the framework: #21782;
- Reduced the number of G-API generated accuracy tests: #21909.
- Drop upstream patches:
* 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
* videoio_initial_FFmpeg_5_0_support.patch
* videoio_ffmpeg_avoid_memory_leaks.patch
OBS-URL: https://build.opensuse.org/request/show/983700
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=33
2022-06-27 18:05:05 +02:00
|
|
|
%package -n libopencv_gapi%{soname}
|
|
|
|
|
Summary: G-API library component for OpenCV
|
|
|
|
|
License: BSD-3-Clause
|
|
|
|
|
Group: System/Libraries
|
|
|
|
|
|
|
|
|
|
%description -n libopencv_gapi%{soname}
|
|
|
|
|
G-API library component for OpenCV
|
|
|
|
|
|
2020-11-03 06:17:42 +01:00
|
|
|
%package -n libopencv_highgui%{soname}
|
|
|
|
|
Summary: Higlevel GUI libraries for OpenCV
|
|
|
|
|
License: BSD-3-Clause
|
|
|
|
|
Group: System/Libraries
|
|
|
|
|
|
|
|
|
|
%description -n libopencv_highgui%{soname}
|
|
|
|
|
Higlevel GUI libraries for OpenCV
|
|
|
|
|
|
|
|
|
|
%package -n libopencv_imgcodecs%{soname}
|
|
|
|
|
Summary: Image codec libraries for OpenCV
|
|
|
|
|
License: BSD-3-Clause
|
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Group: System/Libraries
|
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|
|
%description -n libopencv_imgcodecs%{soname}
|
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|
Image codec libraries for OpenCV
|
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|
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|
|
%package -n libopencv_superres%{soname}
|
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|
|
Summary: Superresolution libraries for OpenCV
|
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|
License: BSD-3-Clause
|
|
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|
|
Group: System/Libraries
|
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|
|
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|
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|
|
|
%description -n libopencv_superres%{soname}
|
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|
Superresolution libraries for OpenCV
|
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%package -n libopencv_objdetect%{soname}
|
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Summary: Face detection libraries for OpenCV
|
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License: BSD-3-Clause
|
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Group: System/Libraries
|
2020-11-03 06:51:22 +01:00
|
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Requires: %{name}4-cascades-data
|
2020-11-03 06:17:42 +01:00
|
|
|
|
|
|
|
|
%description -n libopencv_objdetect%{soname}
|
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|
|
Object detection libraries for OpenCV
|
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|
Accepting request 983700 from home:StefanBruens:branches:science
- update to 4.6.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version460
* OpenCV project infrastructure migrating on GitHub Actions
workflows for CI and release purposes
* Added support for GCC 12, Clang 15
* Added support for FFmpeg 5.0
* DNN module patches:
+ Improved layers / activations / supported more models:
- LSTM (+CUDA), resize (+ONNX13), Sign, Shrink, Reciprocal,
depth2space, space2depth
- fixes in Reduce, Slice, Expand
+ Disabled floating-point denormals processing #21521
+ Changed layer names in ONNX importer to support "output"
entities properly
+ Added TIM-VX NPU backend support:
https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU
+ Added Softmax parameter to ClassificationModel
+ Added audio speech recognition sample (C++) #21458
+ Intel® Inference Engine backend (OpenVINO):
- added initial support for OpenVINO 2022.1 release
- removed support of legacy API (dropped since 2020.3)
* G-API module:
+ G-API framework:
- Introduced a Grayscale image format support for
cv::MediaFrame: #21511;
- Enabeled .reshape() support in the CPU backend: #21669;
- Fixed possible hang in streaming execution mode with constant
inputs: #21567;
- Introduced proper error/exception propagation in the
asynchronous streaming execution mode: #21660;
- Fixed new stream event handling: #21731.
+ Fluid backend:
- Fixed horizontal pass in the Resize kernel, fixed Valgrind
issues: #21144;
- Extended Resize kernel with F32 version: #21678,
added AVX: #21728.
- Enabled dynamic dispatch for Split4 kernel: #21520;
- Enabled dynamic dispatch for Merge3 kernel: #21529;
- Added a SIMD version for DivC kernel: #21474;
- Added a SIMD version for DivRC kernel: #21530;
- Enabled dynamic dispatch for Add kernel: #21686;
- Enabled dynamic dispatch for Sub kernel: #21746;
- Added a SIMD version for ConvertTo kernel: #21777;
- Fixed kernel matrix size for Sobel kernel: #21613.
+ Intel® OpenVINO™ inference backend:
- Fixed NV12 format support for remote memory when OpenVINO
remote context is used: #21424.
- Implemented correct error handling in the backend: #21579.
- Fixed ngraph warnings #21362.
+ OpenCV AI Kit backend:
- Introduced a new backend to program OpenCV AI Kit boards via
G-API. Currently the backend is in experimental state, but allows
to build Camera+NN pipeline and supports heterogeneity (mixing
with host-side code): #20785, #21504.
+ Media integration:
- Enabled GPU inference with oneVPL and DirectX11 on Windows in
Intel OpenVINO inference backend: #21232, #21618, #21658, #21687,
#21688. Now GPU textures decoded by oneVPL decoder can be
preprocessed and inferred on GPU with no extra host processing.
- Enabled oneVPL support on Linux: #21883.
- Extended GStreamer pipeline source with Grayscale image format
support: #21560.
+ Python bindings:
- Exposed GStreamer pipeline source in Python bindings: #20832.
- Fixed Python bindings for CudaBufferPool, cudacodec and cudastereo
modules in OpenCV Contrib.
+ Samples:
- Introduced a pipeline modelling tool for cascaded model
benchmarking: #21477, #21636, #21719. The tool supports a
declarative YAML-based config to describe pipelines with simulated
pre-/post-processing. The tool collects and reports latency and
throughput information for the modelled pipeline.
+ Other changes and fixes:
- Moved GKernelPackage into cv:: namespace by default, its cv::gapi::
alias remain for compatibility: #21318;
- Moved Resize kernel from core to imgproc kernel packages for
CPU, OpenCL, and Fluid backends: #21157. Also moved tests
appropriately: #21475;
- Avoided sporadic test failures in DivC: #21626;
- Fixed 1D Mat handling in the framework: #21782;
- Reduced the number of G-API generated accuracy tests: #21909.
- Drop upstream patches:
* 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
* videoio_initial_FFmpeg_5_0_support.patch
* videoio_ffmpeg_avoid_memory_leaks.patch
OBS-URL: https://build.opensuse.org/request/show/983700
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=33
2022-06-27 18:05:05 +02:00
|
|
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%package -n libopencv_optflow%{soname}
|
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|
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Summary: Optical flow calculation libraries for OpenCV
|
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License: BSD-3-Clause
|
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|
|
Group: System/Libraries
|
|
|
|
|
|
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|
%description -n libopencv_optflow%{soname}
|
|
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|
|
Optical flow calculation libraries for OpenCV
|
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|
|
2020-11-03 06:17:42 +01:00
|
|
|
%package -n libopencv_videoio%{soname}
|
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|
|
Summary: Video IO libraries for OpenCV
|
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|
License: BSD-3-Clause
|
|
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|
Group: System/Libraries
|
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|
|
|
|
|
|
|
|
%description -n libopencv_videoio%{soname}
|
|
|
|
|
Video IO libraries for OpenCV
|
|
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|
|
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|
|
|
%package -n libopencv_videostab%{soname}
|
|
|
|
|
Summary: Video stabilization libraries for OpenCV
|
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|
|
License: BSD-3-Clause
|
|
|
|
|
Group: System/Libraries
|
|
|
|
|
|
|
|
|
|
%description -n libopencv_videostab%{soname}
|
|
|
|
|
Video stabilization libraries for OpenCV
|
|
|
|
|
|
|
|
|
|
%package -n libopencv_ximgproc%{soname}
|
|
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|
|
Summary: Image processing libraries for OpenCV
|
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|
|
License: BSD-3-Clause
|
|
|
|
|
Group: System/Libraries
|
|
|
|
|
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|
|
%description -n libopencv_ximgproc%{soname}
|
|
|
|
|
Image processing libraries for OpenCV
|
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|
|
|
2010-04-25 18:45:15 +02:00
|
|
|
%package devel
|
2010-03-08 18:16:50 +01:00
|
|
|
Summary: Development files for using the OpenCV library
|
2017-11-19 11:08:51 +01:00
|
|
|
License: BSD-3-Clause
|
2017-06-12 15:13:03 +02:00
|
|
|
Group: Development/Libraries/C and C++
|
2010-03-08 18:16:50 +01:00
|
|
|
Requires: %{libname}%{soname} = %{version}
|
2022-05-03 19:42:13 +02:00
|
|
|
Requires: libopencv_aruco%{soname} = %{version}
|
2020-11-03 06:17:42 +01:00
|
|
|
Requires: libopencv_face%{soname} = %{version}
|
Accepting request 983700 from home:StefanBruens:branches:science
- update to 4.6.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version460
* OpenCV project infrastructure migrating on GitHub Actions
workflows for CI and release purposes
* Added support for GCC 12, Clang 15
* Added support for FFmpeg 5.0
* DNN module patches:
+ Improved layers / activations / supported more models:
- LSTM (+CUDA), resize (+ONNX13), Sign, Shrink, Reciprocal,
depth2space, space2depth
- fixes in Reduce, Slice, Expand
+ Disabled floating-point denormals processing #21521
+ Changed layer names in ONNX importer to support "output"
entities properly
+ Added TIM-VX NPU backend support:
https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU
+ Added Softmax parameter to ClassificationModel
+ Added audio speech recognition sample (C++) #21458
+ Intel® Inference Engine backend (OpenVINO):
- added initial support for OpenVINO 2022.1 release
- removed support of legacy API (dropped since 2020.3)
* G-API module:
+ G-API framework:
- Introduced a Grayscale image format support for
cv::MediaFrame: #21511;
- Enabeled .reshape() support in the CPU backend: #21669;
- Fixed possible hang in streaming execution mode with constant
inputs: #21567;
- Introduced proper error/exception propagation in the
asynchronous streaming execution mode: #21660;
- Fixed new stream event handling: #21731.
+ Fluid backend:
- Fixed horizontal pass in the Resize kernel, fixed Valgrind
issues: #21144;
- Extended Resize kernel with F32 version: #21678,
added AVX: #21728.
- Enabled dynamic dispatch for Split4 kernel: #21520;
- Enabled dynamic dispatch for Merge3 kernel: #21529;
- Added a SIMD version for DivC kernel: #21474;
- Added a SIMD version for DivRC kernel: #21530;
- Enabled dynamic dispatch for Add kernel: #21686;
- Enabled dynamic dispatch for Sub kernel: #21746;
- Added a SIMD version for ConvertTo kernel: #21777;
- Fixed kernel matrix size for Sobel kernel: #21613.
+ Intel® OpenVINO™ inference backend:
- Fixed NV12 format support for remote memory when OpenVINO
remote context is used: #21424.
- Implemented correct error handling in the backend: #21579.
- Fixed ngraph warnings #21362.
+ OpenCV AI Kit backend:
- Introduced a new backend to program OpenCV AI Kit boards via
G-API. Currently the backend is in experimental state, but allows
to build Camera+NN pipeline and supports heterogeneity (mixing
with host-side code): #20785, #21504.
+ Media integration:
- Enabled GPU inference with oneVPL and DirectX11 on Windows in
Intel OpenVINO inference backend: #21232, #21618, #21658, #21687,
#21688. Now GPU textures decoded by oneVPL decoder can be
preprocessed and inferred on GPU with no extra host processing.
- Enabled oneVPL support on Linux: #21883.
- Extended GStreamer pipeline source with Grayscale image format
support: #21560.
+ Python bindings:
- Exposed GStreamer pipeline source in Python bindings: #20832.
- Fixed Python bindings for CudaBufferPool, cudacodec and cudastereo
modules in OpenCV Contrib.
+ Samples:
- Introduced a pipeline modelling tool for cascaded model
benchmarking: #21477, #21636, #21719. The tool supports a
declarative YAML-based config to describe pipelines with simulated
pre-/post-processing. The tool collects and reports latency and
throughput information for the modelled pipeline.
+ Other changes and fixes:
- Moved GKernelPackage into cv:: namespace by default, its cv::gapi::
alias remain for compatibility: #21318;
- Moved Resize kernel from core to imgproc kernel packages for
CPU, OpenCL, and Fluid backends: #21157. Also moved tests
appropriately: #21475;
- Avoided sporadic test failures in DivC: #21626;
- Fixed 1D Mat handling in the framework: #21782;
- Reduced the number of G-API generated accuracy tests: #21909.
- Drop upstream patches:
* 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
* videoio_initial_FFmpeg_5_0_support.patch
* videoio_ffmpeg_avoid_memory_leaks.patch
OBS-URL: https://build.opensuse.org/request/show/983700
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=33
2022-06-27 18:05:05 +02:00
|
|
|
Requires: libopencv_gapi%{soname} = %{version}
|
2020-11-03 06:17:42 +01:00
|
|
|
Requires: libopencv_highgui%{soname} = %{version}
|
|
|
|
|
Requires: libopencv_imgcodecs%{soname} = %{version}
|
|
|
|
|
Requires: libopencv_objdetect%{soname} = %{version}
|
Accepting request 983700 from home:StefanBruens:branches:science
- update to 4.6.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version460
* OpenCV project infrastructure migrating on GitHub Actions
workflows for CI and release purposes
* Added support for GCC 12, Clang 15
* Added support for FFmpeg 5.0
* DNN module patches:
+ Improved layers / activations / supported more models:
- LSTM (+CUDA), resize (+ONNX13), Sign, Shrink, Reciprocal,
depth2space, space2depth
- fixes in Reduce, Slice, Expand
+ Disabled floating-point denormals processing #21521
+ Changed layer names in ONNX importer to support "output"
entities properly
+ Added TIM-VX NPU backend support:
https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU
+ Added Softmax parameter to ClassificationModel
+ Added audio speech recognition sample (C++) #21458
+ Intel® Inference Engine backend (OpenVINO):
- added initial support for OpenVINO 2022.1 release
- removed support of legacy API (dropped since 2020.3)
* G-API module:
+ G-API framework:
- Introduced a Grayscale image format support for
cv::MediaFrame: #21511;
- Enabeled .reshape() support in the CPU backend: #21669;
- Fixed possible hang in streaming execution mode with constant
inputs: #21567;
- Introduced proper error/exception propagation in the
asynchronous streaming execution mode: #21660;
- Fixed new stream event handling: #21731.
+ Fluid backend:
- Fixed horizontal pass in the Resize kernel, fixed Valgrind
issues: #21144;
- Extended Resize kernel with F32 version: #21678,
added AVX: #21728.
- Enabled dynamic dispatch for Split4 kernel: #21520;
- Enabled dynamic dispatch for Merge3 kernel: #21529;
- Added a SIMD version for DivC kernel: #21474;
- Added a SIMD version for DivRC kernel: #21530;
- Enabled dynamic dispatch for Add kernel: #21686;
- Enabled dynamic dispatch for Sub kernel: #21746;
- Added a SIMD version for ConvertTo kernel: #21777;
- Fixed kernel matrix size for Sobel kernel: #21613.
+ Intel® OpenVINO™ inference backend:
- Fixed NV12 format support for remote memory when OpenVINO
remote context is used: #21424.
- Implemented correct error handling in the backend: #21579.
- Fixed ngraph warnings #21362.
+ OpenCV AI Kit backend:
- Introduced a new backend to program OpenCV AI Kit boards via
G-API. Currently the backend is in experimental state, but allows
to build Camera+NN pipeline and supports heterogeneity (mixing
with host-side code): #20785, #21504.
+ Media integration:
- Enabled GPU inference with oneVPL and DirectX11 on Windows in
Intel OpenVINO inference backend: #21232, #21618, #21658, #21687,
#21688. Now GPU textures decoded by oneVPL decoder can be
preprocessed and inferred on GPU with no extra host processing.
- Enabled oneVPL support on Linux: #21883.
- Extended GStreamer pipeline source with Grayscale image format
support: #21560.
+ Python bindings:
- Exposed GStreamer pipeline source in Python bindings: #20832.
- Fixed Python bindings for CudaBufferPool, cudacodec and cudastereo
modules in OpenCV Contrib.
+ Samples:
- Introduced a pipeline modelling tool for cascaded model
benchmarking: #21477, #21636, #21719. The tool supports a
declarative YAML-based config to describe pipelines with simulated
pre-/post-processing. The tool collects and reports latency and
throughput information for the modelled pipeline.
+ Other changes and fixes:
- Moved GKernelPackage into cv:: namespace by default, its cv::gapi::
alias remain for compatibility: #21318;
- Moved Resize kernel from core to imgproc kernel packages for
CPU, OpenCL, and Fluid backends: #21157. Also moved tests
appropriately: #21475;
- Avoided sporadic test failures in DivC: #21626;
- Fixed 1D Mat handling in the framework: #21782;
- Reduced the number of G-API generated accuracy tests: #21909.
- Drop upstream patches:
* 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
* videoio_initial_FFmpeg_5_0_support.patch
* videoio_ffmpeg_avoid_memory_leaks.patch
OBS-URL: https://build.opensuse.org/request/show/983700
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=33
2022-06-27 18:05:05 +02:00
|
|
|
Requires: libopencv_optflow%{soname} = %{version}
|
2020-11-03 06:17:42 +01:00
|
|
|
Requires: libopencv_superres%{soname} = %{version}
|
|
|
|
|
Requires: libopencv_videoio%{soname} = %{version}
|
|
|
|
|
Requires: libopencv_videostab%{soname} = %{version}
|
|
|
|
|
Requires: libopencv_ximgproc%{soname} = %{version}
|
2010-03-08 18:16:50 +01:00
|
|
|
Requires: %{name} = %{version}
|
2014-03-13 20:43:49 +01:00
|
|
|
Requires: pkgconfig(gl)
|
2013-11-18 13:09:08 +01:00
|
|
|
Requires: pkgconfig(glu)
|
2014-03-13 20:43:49 +01:00
|
|
|
Requires: pkgconfig(ice)
|
|
|
|
|
Requires: pkgconfig(sm)
|
|
|
|
|
Requires: pkgconfig(x11)
|
|
|
|
|
Requires: pkgconfig(xext)
|
Accepting request 714221 from science
- Update to version 4.1.0
* DNN module:
+ Reduced peak memory consumption for some models up to 30%.
+ Inference Engine
- Inference Engine 2018R3 is now a minimal supported version of IE.
- Myriad X (Intel® Neural Compute Stick 2) is now supported and tested.
- Automatic IR network reshaping for different inputs.
- Improved samples to work with models from OpenVINO Open Model Zoo
+ New networks from TensorFlow Object Detection API: Faster-RCNNs, SSDs
and Mask-RCNN with dilated convolutions, FPN SSD
* Performance improvements:
+ More optimization using AVX2 instruction set.
+ Automatic runtime dispatching is available for large set of functions
from core and imgproc modules.
* Other improvements:
+ Matplotlib Perceptually Uniform Sequential colormaps
+ Add keypoints matching visualization for real-time pose estimation tutorial
+ Add Hand-Eye calibration methods
+ Java: improved support for multidimensional arrays (Mat)
+ Dynamically loaded videoio backends (FFmpeg, GStreamer)
+ opencv_contrib: Robust local optical flow (RLOF) implementations
+ opencv_contrib: Implementation of Quasi Dense Stereo algorithm
+ opencv_contrib: New module: Image Quality Analysis (IQA) API
+ opencv_contrib: BRISQUE No Reference Image Quality Assessment (IQA) API
Check https://github.com/opencv/opencv/wiki/ChangeLog#version410
- Update to version 4.0.0
* A lot of C API from OpenCV 1.x has been removed. The affected modules are
objdetect, photo, video, videoio, imgcodecs, calib3d.
* Persistence (storing and loading structured data to/from XML, YAML or JSON)
in the core module has been completely reimplemented.
* OpenCV is now C++11 library and requires C++11-compliant compiler.
Thanks to the extended C++11 standard library, we could get rid of hand-crafted
cv::String and cv::Ptr. Now cv::String == std::string and cv::Ptr is a thin
wrapper on top of std::shared_ptr. Also, on Linux/BSD for cv::parallel_for_
we now use std::thread's instead of pthreads.
* DNN improvements
* Completely new module opencv_gapi has been added. It is the engine for very
efficient image processing, based on lazy evaluation and on-fly construction.
* Performance improvements
A few hundreds of basic kernels in OpenCV have been rewritten using so-called
"wide universal intrinsics". Those intrinsics map to SSE2, SSE4, AVX2, NEON or
VSX intrinsics, depending on the target platform and the compile flags.
* QR code detector and decoder have been added to opencv/objdetect module.
* The popular Kinect Fusion algorithm has been implemented, optimized for CPU and
GPU (OpenCL), and integrated into opencv_contrib/rgbd module.
* Very efficient and yet high-quality DIS dense optical flow algorithm has been
moved from opencv_contrib to opencv, video module. See the example.
* The slower TV L1 optical flow algorithm has been moved to opencv_contrib.
Check https://github.com/opencv/opencv/wiki/ChangeLog#version400
- Drop obsolete opencv-lib_suffix.patch
- Add 0001-Handle-absolute-OPENCV_INCLUDE_INSTALL_PATH-correctl.patch
- As this is a major version upgrade, the old 3.4.x package is still
available as opencv3
- Update to 3.4.3
* Compatibility fixes with python 3.7
* Added a new computational target DNN_TARGET_OPENCL_FP16
* Extended support of Intel's Inference Engine backend
* Enabled import of Intel's OpenVINO pre-trained networks from
intermediate representation (IR).
* tutorials improvements
Check https://github.com/opencv/opencv/wiki/ChangeLog#version343
for the complete changelog.
- Drop fix-build-i386-nosse.patch, build-workaround-issues-with-c.patch
(fixed upstream)
- Refresh patches
- Add patch to fix use of headers from C:
* build-workaround-issues-with-c.patch
- Update to 3.4.1:
* Added support for quantized TensorFlow networks
* OpenCV is now able to use Intel DL inference engine as DNN
acceleration backend
* Added AVX-512 acceleration to the performance-critical kernels
* For more information, read
https://github.com/opencv/opencv/wiki/ChangeLog#version341
- Update contrib modules to 3.4.1:
* No changelog available
- Change mechanism the contrib modules are built
- Include LICENSE of contrib tarball as well
- Build with python3 on >= 15
- Add patch to fix build on i386 without SSE:
* fix-build-i386-nosse.patch
- Refresh patches:
* fix_processor_detection_for_32bit_on_64bit.patch
* opencv-build-compare.patch
- Mention all libs explicitly
- Rebase 3.4.0 update from i@marguerite.su
- update to 3.4.0
* Added faster R-CNN support
* Javascript bindings have been extended to
cover DNN module
* DNN has been further accelerated for iGPU
using OpenCL
* On-disk caching of precompiled OpenCL
kernels has been finally implemented
* possible to load and run pre-compiled
OpenCL kernels via T-API
* Bit-exact 8-bit and 16-bit resize has been
implemented (currently supported only
bilinear interpolation)
- update face module to 3.4.0
- add opencv-lib_suffix.patch, remove LIB_SUFFIX
from OPENCV_LIB_INSTALL_PATH, as CMAKE_INSTALL
_LIBDIR is arch dependent.
- Add option to build without openblas
- Add conditionals for python2 and python3 to allow us enabling
only desired python variants when needed
- Do not depend on sphinx as py2 and py3 seem to collide there
- Readd opencv-gles.patch, it is *not* included upstream; otherwise
build breaks on all GLES Qt5 platforms (armv6l, armv7l, aarch64)
- add fix_processor_detection_for_32bit_on_64bit.patch
- Correctly set optimizations and dynamic dispatch on ARM, use
OpenCV 3.3 syntax on x86.
- Update licensing information
- change requires of python-numpy-devel to build in Leap and
to not break factory in future
- fix build error/unresolvable for Leap 42.2 and 42.3
- Update to version 3.3.1:
* Lots of various bugfixes
- Update source url
- Rename python subpackage to python2
- Do not explicitly require python-base for python subpackages
- Update to 3.3
- Dropped obsolete patches
* opencv-gcc6-fix-pch-support-PR8345.patch
* opencv-gles.patch
- Updated opencv-build-compare.patch
- Add 0001-Do-not-include-glx.h-when-using-GLES.patch
Fix build for 32bit ARM, including both GLES and desktop GL headers
causes incompatible pointer type errors
- Add conditional for the qt5/qt4 integration
* This is used only for gui tools, library is not affected
- Add provides/obsoletes for the qt5 packages to allow migration
- Drop patch opencv-qt5-sobump.diff
* Used only by the obsoleted qt5 variant
- Cleanup a bit with spec-cleaner
- Use %cmake macros
- Remove the conditions that are not really needed
- Add tests conditional disabled by default
* Many tests fail and there are missing testdata
- Switch to pkgconfig style dependencies
- Update to OpenCV 3.2.0
- Results from 11 GSoC 2016 projects have been submitted to the library:
+ sinusoidal patterns for structured light and phase unwrapping module
[Ambroise Moreau (Delia Passalacqua)]
+ DIS optical flow (excellent dense optical flow algorithm that is both
significantly better and significantly faster than Farneback’s algorithm –
our baseline), and learning-based color constancy algorithms implementation
[Alexander Bokov (Maksim Shabunin)]
+ CNN based tracking algorithm (GOTURN) [Tyan Vladimir (Antonella Cascitelli)]
+ PCAFlow and Global Patch Collider algorithms implementation
[Vladislav Samsonov (Ethan Rublee)]
+ Multi-language OpenCV Tutorials in Python, C++ and Java
[João Cartucho (Vincent Rabaud)]
+ New camera model and parallel processing for stitching pipeline
[Jiri Horner (Bo Li)]
+ Optimizations and improvements of dnn module
[Vitaliy Lyudvichenko (Anatoly Baksheev)]
+ Base64 and JSON support for file storage. Use names like
“myfilestorage.xml?base64” when writing file storage to store big chunks of
numerical data in base64-encoded form. [Iric Wu (Vadim Pisarevsky)]
+ tiny_dnn improvements and integration
[Edgar Riba (Manuele Tamburrano, Stefano Fabri)]
+ Quantization and semantic saliency detection with tiny_dnn
[Yida Wang (Manuele Tamburrano, Stefano Fabri)]
+ Word-spotting CNN based algorithm
[Anguelos Nicolaou (Lluis Gomez)]
- Contributions besides GSoC:
+ Greatly improved and accelerated dnn module in opencv_contrib:
- Many new layers, including deconvolution, LSTM etc.
- Support for semantic segmentation and SSD networks with samples.
- TensorFlow importer + sample that runs Inception net by Google.
+ More image formats and camera backends supported
+ Interactive camera calibration app
+ Multiple algorithms implemented in opencv_contrib
+ Supported latest OSes, including Ubuntu 16.04 LTS and OSX 10.12
+ Lot’s of optimizations for IA and ARM archs using parallelism, vector
instructions and new OpenCL kernels.
+ OpenCV now can use vendor-provided OpenVX and LAPACK/BLAS (including Intel MKL,
Apple’s Accelerate, OpenBLAS and Atlas) for acceleration
- Refreshed opencv-build-compare.patch
- Dropped upstream opencv-gcc5.patch
- Replace opencv-gcc6-disable-pch.patch with upstream patch
opencv-gcc6-fix-pch-support-PR8345.patch
- Enable TBB support (C++ threading library)
- Add dependency on openBLAS
- Enable ffmpeg support unconditional
- In case we build using GCC6 (or newer), add -mlra to CFLAGS to
workaround gcc bug
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=71294.
- Apply upstream patch opencv-gcc6-disable-pch.patch to disable
PCH for GCC6.
- Test for python versions greater than or equal to the current
version.
- Add python 3 support
- Added opencv_contrib_face-3.1.0.tar.bz2
* This tarball is created to take only the face module from the
contrib package. The Face module is required by libkface, which
in its turn is required by digikam.
- Added _constraints file to avoid random failures on small workers
(at least for builds on PMBS)
- Update to OpenCV 3.1.0
- A lot of new functionality has been introduced during Google
Summer of Code 2015:
+ “Omnidirectional Cameras Calibration and Stereo 3D
Reconstruction” – opencv_contrib/ccalib module
(Baisheng Lai, Bo Li)
+ “Structure From Motion” – opencv_contrib/sfm module
(Edgar Riba, Vincent Rabaud)
+ “Improved Deformable Part-based Models” – opencv_contrib/dpm
module (Jiaolong Xu, Bence Magyar)
+ “Real-time Multi-object Tracking using Kernelized Correlation
Filter” – opencv_contrib/tracking module
(Laksono Kurnianggoro, Fernando J. Iglesias Garcia)
+ “Improved and expanded Scene Text Detection” –
opencv_contrib/text module (Lluis Gomez, Vadim Pisarevsky)
+ “Stereo correspondence improvements” – opencv_contrib/stereo
module (Mircea Paul Muresan, Sergei Nosov)
+ “Structured-Light System Calibration” –
opencv_contrib/structured_light (Roberta Ravanelli,
Delia Passalacqua, Stefano Fabri, Claudia Rapuano)
+ “Chessboard+ArUco for camera calibration” –
opencv_contrib/aruco (Sergio Garrido, Prasanna, Gary Bradski)
+ “Implementation of universal interface for deep neural
network frameworks” – opencv_contrib/dnn module
(Vitaliy Lyudvichenko, Anatoly Baksheev)
+ “Recent advances in edge-aware filtering, improved SGBM
stereo algorithm” – opencv/calib3d and opencv_contrib/ximgproc
(Alexander Bokov, Maksim Shabunin)
+ “Improved ICF detector, waldboost implementation” –
opencv_contrib/xobjdetect (Vlad Shakhuro, Alexander Bovyrin)
+ “Multi-target TLD tracking” – opencv_contrib/tracking module
(Vladimir Tyan, Antonella Cascitelli)
+ “3D pose estimation using CNNs” – opencv_contrib/cnn_3dobj
(Yida Wang, Manuele Tamburrano, Stefano Fabri)
- Many great contributions made by the community, such as:
+ Support for HDF5 format
+ New/Improved optical flow algorithms
+ Multiple new image processing algorithms for filtering,
segmentation and feature detection
+ Superpixel segmentation and much more
- IPPICV is now based on IPP 9.0.1, which should make OpenCV
even faster on modern Intel chips
- opencv_contrib modules can now be included into the
opencv2.framework for iOS
- Newest operating systems are supported: Windows 10 and
OSX 10.11 (Visual Studio 2015 and XCode 7.1.1)
- Interoperability between T-API and OpenCL, OpenGL, DirectX and
Video Acceleration API on Linux, as well as Android 5 camera.
- HAL (Hardware Acceleration Layer) module functionality has been
moved into corresponding basic modules; the HAL replacement
mechanism has been implemented along with the examples
- Removed improve-sphinx-search.diff, opencv-altivec-vector.patch,
opencv-pkgconfig.patch and opencv-samples.patch, fixed upstream.
- Fixed opencv-qt5-sobump.diff, opencv-build-compare.patch,
opencv-gcc5.patch and opencv-gles.patch.
- Version OpenCV 3.0.0
+ ~1500 patches, submitted as PR @ github. All our patches go
the same route.
+ opencv_contrib (http://github.com/itseez/opencv_contrib)
repository has been added. A lot of new functionality is there
already! opencv_contrib is only compatible with 3.0/master,
not 2.4. Clone the repository and use “cmake …
-D OPENCV_EXTRA_MODULES_PATH=<path_to opencv_contrib/modules> …”
to build opencv and opencv_contrib together.
+ a subset of Intel IPP (IPPCV) is given to us and our users free
of charge, free of licensing fees, for commercial and
non-commerical use. It’s used by default in x86 and x64 builds
on Windows, Linux and Mac.
+ T-API (transparent API) has been introduced, this is transparent
GPU acceleration layer using OpenCL. It does not add any
compile-time or runtime dependency of OpenCL. When OpenCL is
available, it’s detected and used, but it can be disabled at
compile time or at runtime. It covers ~100 OpenCV functions.
This work has been done by contract and with generous support
from AMD and Intel companies.
+ ~40 OpenCV functions have been accelerated using NEON intrinsics
and because these are mostly basic functions, some higher-level
functions got accelerated as well.
+ There is also new OpenCV HAL layer that will simplifies creation
of NEON-optimized code and that should form a base for the
open-source and proprietary OpenCV accelerators.
+ The documentation is now in Doxygen: http://docs.opencv.org/master/
+ We cleaned up API of many high-level algorithms from features2d,
calib3d, objdetect etc. They now follow the uniform
“abstract interface – hidden implementation” pattern and make
extensive use of smart pointers (Ptr<>).
+ Greatly improved and extended Python & Java bindings (also,
see below on the Python bindings), newly introduced Matlab
bindings (still in alpha stage).
+ Improved Android support – now OpenCV Manager is in Java and
supports both 2.4 and 3.0.
+ Greatly improved WinRT support, including video capturing and
multi-threading capabilities. Thanks for Microsoft team for this!
+ Big thanks to Google who funded several successive GSoC programs
and let OpenCV in. The results of many successful GSoC 2013 and
2014 projects have been integrated in opencv 3.0 and
opencv_contrib (earlier results are also available in
OpenCV 2.4.x). We can name:
- text detection
- many computational photography algorithms (HDR, inpainting,
edge-aware filters, superpixels, …)
- tracking and optical flow algorithms
- new features, including line descriptors, KAZE/AKAZE
- general use optimization (hill climbing, linear programming)
- greatly improved Python support, including Python 3.0 support,
many new tutorials & samples on how to use OpenCV with Python.
- 2d shape matching module and 3d surface matching module
- RGB-D module
- VTK-based 3D visualization module
- etc.
+ Besides Google, we enjoyed (and hope that you will enjoy too)
many useful contributions from community, like:
- biologically inspired vision module
- DAISY features, LATCH descriptor, improved BRIEF
- image registration module
- etc.
- Reduce build-compare noise
opencv-build-compare.patch
- Remove BuildRequirement for python-sphinx in SLE12, since it's
not available there and it's not a mandatory requirement.
- Reduce differences between two spec files
- Use pkgconfig for ffmpeg BuildRequires
- Update improve-sphinx-search.diff for new python-Sphinx(1.3.1)
* now that sphinx-build disallow executing without arguments and
give you "Insufficient arguments" error, use "sphinx-build -h"
instead
* the default usages output ie. sphinx-build(or --help) no longer
are standard error but standard output, drop OUTPUT_QUIET and
add OUTPUT_VARIABLE throws the output to SPHINX_OUTPUT as well
- support gcc 5 (i.e. gcc versions without minor version):
opencv-gcc5.patch
- Update to OpenCV 2.4.11 - can't find NEWS or Changelog
merely collecting bug fixes while 3.0 is in the making, 2.4.11
didn't even make it on their web page, it's only on download
server
- remove opencv-underlinking.patch as obsolete
- remove upstream patch bomb_commit_gstreamer-1x-support.patch
- commenting out opencv-pkgconfig.patch - possibly it requires a rebase,
but the problem it tries to solve is unclear
- Add specific buildrequires for libpng15, so that we are
building against the system provided libpng.
- Update to OpenCV 2.4.9
More info at:
http://opencv.org/opencv-2-4-9-is-out.html
The brief list of changes:
* new 3D visualization module ‘viz’;
* performance fixes in ‘ocl’ module;
* fixes in Android Camera;
* improved CUDA support for mobile platforms;
* bugfixes from community;
* 55 reported bugs have been closed;
* 156 pull requests have been merged.
- Drop the BuildRequires on libucil and libunicap for Factory. This
stops us from getting ride of Gstreamer 0.10 and besides these two
libraries seem to be unmaintained upstream as that the latest
actions are from 2010
- Add upstream patch (3.0 version) to support Gstreamer 1.x
* bomb_commit_gstreamer-1x-support.patch
- Upstream now provides tarballs with source only as git tags
from github so update Source0 path.
- Add requires on various X extensions linked to opencv_ts module.
As those are present in the .pc file we need it anyway.
- Update to OpenCV 2.4.8
More info at:
http://opencv.org/opencv-2-4-8.html
The brief list of changes:
* NVidia CUDA support on Android devices with CUDA capable SoC and
CUDA sample;
* Concurrent kernel execution and user defined context support for
OpenCL;
* Integration with Intel Perceptual SDK and new depth sensors support
for Windows;
* 32 reported bugs have been closed;
* 139 pull requests have been merged;
- Fix build with altivec:
opencv-altivec-vector.patch
- Added opencv-pkgconfig.patch: make sure to provide link flags in
OpenCV pc file (bnc#853036)
- Update to OpenCV 2.4.7
More info at:
http://opencv.org/opencv-2-4-7-is-out.html
The brief list of changes:
* dynamic OpenCL runtime loading, setting default OpenCL device
via env var, many bug-fixes and some new optimization with OpenCL
* bug-fixes and new optimizations in CUDA stuff
* latest NDK and Android OS support, Native Android Camera tuning
* minor fixes, XAML sample and MS Certification compatibility
in WinRT stuff
* 382 pull requests have been merged
* 54 reported bugs have been fixed
- Added pkgconfig(glu) Requires to devel package, as per .pc file
- Make devel package provides also devel-static one
- Drop assume-Sphinx-is-there.diff, and add improve-sphinx-search.diff,
for properly finding sphinx with alphabetic chars in version
- Add patch assume-Sphinx-is-there.diff to fix building with
Sphinx versions that have alphanumeric characters in the version
(Only for factory builds at the moment)
- Use eigen3 instead of eigen2 as build requirement for openSUSE > 12.3.
- Enable compilation with libucil and libunicap.
- Removed dos2unix build requirement (not needed anymore).
- Update to OpenCV 2.4.6.1
More info at:
http://opencv.org/opencv-2-4-6-is-out.html
The brief list of changes:
* added video file i/o Windows RT and sample application using
camera, enabled parallelization with TBB or MS Concurrency
* added CUDA 5.5 support for desktop and ARM systems
* added Qt 5 support
* added many new OpenCL algorithms ports, included OpenCL binaries
into the Windows superpack
* iOS build scripts (together with Android ones) moved to
‘opencv/platforms’ directory
* added functions for UIImage <-> cv::Mat conversion
* correct front/back camera selection in Android app framework
* added Linaro NDK support and fixes for MIPS to Android CMake
toolchain
* stability has been improved by a lot, numerous bug-fixes across
all the library
- build with LFS_CFLAGS in 32 bit archs.
- Disable SSE3 for all architectures (bnc#814333)
- Disable SSE(2) on non x86_64 architectures, causes crashing
kde#276923, bnc#789173
- Update to OpenCV 2.4.5
More info at:
http://opencv.org/opencv-2-4-5-is-out.html
The brief list of changes:
* experimental WinRT support
* new video super-resolution module
* CLAHE (adaptive histogram equalization) algorithm on both CPU
and GPU
* further improvements and extensions in ocl module
(stereo block matching and belief propagation have been added,
fixed crashes on Intel HD4000)
* Visual Studio 2012 cv::Mat visualizer plugin debugger tutorial
from Microsoft Research
* OpenCV4Android SDK improvements
(NDK r8e support, native activity sample using OpenCV Manager,
bug-fixes)
* ~25 reported problems have been resolved since 2.4.4, ~78 pull
requests have been merged, thanks everybody who participated!
- Update to OpenCV 2.4.4
More info at:
http://opencv.org/opencv-2-4-4-is-out.html
The brief list of changes:
* OpenCV Java bindings are ported from Android to desktop Java!
Actually any JVM language will work, see Tutorial for details,
and Java or Scala code samples.
* Android application framework, samples, tutorials, and OpenCV
Manager are improved.
* Optimizations for the new NVIDIA Kepler architecture, CARMA
platform support and other new optimizations in CUDA.
* OpenCL module now builds successfully with various SDKs (from
AMD, NVIDIA, Intel and Apple) and runs well on different GPUs
(AMD, NVidia, Intel HD4000). A lot of new functionality has been
added, tons of bugs fixed, performance of many functions has
been significantly improved.
* 100+ reported problems have been resolved since 2.4.3, thanks
everybody who participated!
- Drop the buildrequire for libxine
- Update to OpenCV 2.4.3
More info at:
http://opencv.org/opencv-2-4-3-released.html
The nicely formatted changelog can be seen here:
http://code.opencv.org/projects/opencv/wiki/ChangeLog;
here are the highlights:
* A lot of good stuff from the Google Summer of Code 2012 has been
integrated; this was a very productive summer!
* Significantly improved and optimized Android and iOS ports.
* Greatly extended GPU (i.e. CUDA-based) module.
* The brand new ocl (OpenCL-based) module that unleashes GPU power
also for AMD and Intel GPU users. It’s not included into the
binary package, since there are different SDKs, and it’s not
turned on by default. You need to run CMake and turn on
“WITH_OPENCL”. Also, please note that this is very first version
of the module, so it may be not very stable and not very
functional.
* Much better performance on many-core systems out of the box. You
do not need TBB anymore on MacOSX, iOS and Windows. BTW, the
binary package for Windows is now built without TBB support.
Libraries and DLLs for Visual Studio 2010 use the Concurrency
framework.
* About 130 bugs have been fixed since 2.4.2.
* Since 2.4.3rc we fixed several more problems, in particular some
compile problems with iOS 6 SDK.
- buildrequire glu
- Update to OpenCV 2.4.2
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Drop opencv-datadir.patch to comply with upstream directory layout
- Update to OpenCV 2.4.1
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Update to OpenCV 2.4.0
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Add opencv-gcc47.patch: Fix build with gcc 4.7.
- Use Explicit Buildrequires on several needed libraries
future dependency cleanups may/will cause build to fail otherwise.
- Add upstream r6881 to fix clang compatibility
- uncomment libraries not in 12.1 for now
- Changed groups (fix for RPMLINT warning)
- Added check for duplicate files (fix for RPMLINT warning)
- Added py_requires macros and python-base dependencies (fix for RPMLINT warning)
- Escaped macros (fix for RPMLINT warning)
- Fixed end-of-line encoding problems (fix for RPMLINT warning)
- Added libeigen2-devel buildrequires
- Added libunicap and libucil buildrequires (libunicap supports requires libucil)
- Cleaned up spec file formatting
- Dropped opencv-2.3-ffmpeg.patch, applied upstream
- Revive opencv-2.3-ffmpeg.patch, needs rebase
- Tag all patches according to openSUSE packaging guidelines
- Removed opencv-2.3-cmake.patch, old cmake cannot be used any more.
- Python bindings cannot be built without NumPy any more.
- Update to OpenCV 2.3.1
- Update and readd opencv-2.3-underlinking.patch since it is still
necessary.
- Fix support for new ffmpeg versions
- Removed unnecessary patches
- Enable Python NumPy support on openSUSE 11.2
- Build Qt instead of Gtk GUI
- Fix cmake files for openSUSE 11.1
- No GStreamer support on openSUSE 11.1
- Update to OpenCV 2.3.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Fix build on openSUSE 11.2
- Add opencv-v4l-2.6.38.patch: use the new libv4l2 interface
- Enable Python NumPy support
- SWIG is not required any more
- Enable OpenEXR support
- Update to OpenCV 2.2.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Use system zlib, oh, and do not export ZLIB symbols to
other applications, clashes ensued.
- fix build with gcc 4.6
- add -underlinking patch
- devel package renamed to opencv-devel, so that switching between
OBS and packman opencv packages is easier
- fix gstreamer support
- fix xine support
- fix some rpmlint warnings
- fix shared libraries permissions
- Do not waste resources building the tests as we do not run them
- Do not disable SSE,SSE2,etc. According to OpenCV changelog,
it should be safe to leave these enabled.
- fix build on openSUSE 11.0
- Update to OpenCV 2.1.0:
* The whole OpenCV is now using exceptions instead of the old
libc-style mechanism
* Experimental "static" OpenCV configuration in CMake was
contributed by Jose Luis Blanco.
Pass "BUILD_SHARED_LIBS=OFF" to CMake to build OpenCV statically.
* new improved version of one-way descriptor is added
* User can now control the image areas visible after the stereo
rectification
* Fullscreen has been added (thanks to Yannick Verdie).
* Further info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- fix build with libpng14
- small spec file cleanup
- Moved to the KDE repositories to enable inclusion in kipi-plugins
- Initial package
OBS-URL: https://build.opensuse.org/request/show/714221
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/opencv?expand=0&rev=73
2019-07-17 13:13:58 +02:00
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2010-03-08 18:16:50 +01:00
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2010-04-25 18:45:15 +02:00
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%description devel
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Summary: Python %{python_version} bindings for apps which use OpenCV
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%if "%{python_flavor}" == "python3" || "%{python_provides}" == "python3"
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This package contains Python %{python_version} bindings for the OpenCV library.
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2016-03-26 15:20:54 +01:00
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Summary: Python 3 bindings for apps which use OpenCV
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License: BSD-3-Clause
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2016-03-26 15:20:54 +01:00
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Group: Development/Libraries/Python
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Accepting request 714221 from science
- Update to version 4.1.0
* DNN module:
+ Reduced peak memory consumption for some models up to 30%.
+ Inference Engine
- Inference Engine 2018R3 is now a minimal supported version of IE.
- Myriad X (Intel® Neural Compute Stick 2) is now supported and tested.
- Automatic IR network reshaping for different inputs.
- Improved samples to work with models from OpenVINO Open Model Zoo
+ New networks from TensorFlow Object Detection API: Faster-RCNNs, SSDs
and Mask-RCNN with dilated convolutions, FPN SSD
* Performance improvements:
+ More optimization using AVX2 instruction set.
+ Automatic runtime dispatching is available for large set of functions
from core and imgproc modules.
* Other improvements:
+ Matplotlib Perceptually Uniform Sequential colormaps
+ Add keypoints matching visualization for real-time pose estimation tutorial
+ Add Hand-Eye calibration methods
+ Java: improved support for multidimensional arrays (Mat)
+ Dynamically loaded videoio backends (FFmpeg, GStreamer)
+ opencv_contrib: Robust local optical flow (RLOF) implementations
+ opencv_contrib: Implementation of Quasi Dense Stereo algorithm
+ opencv_contrib: New module: Image Quality Analysis (IQA) API
+ opencv_contrib: BRISQUE No Reference Image Quality Assessment (IQA) API
Check https://github.com/opencv/opencv/wiki/ChangeLog#version410
- Update to version 4.0.0
* A lot of C API from OpenCV 1.x has been removed. The affected modules are
objdetect, photo, video, videoio, imgcodecs, calib3d.
* Persistence (storing and loading structured data to/from XML, YAML or JSON)
in the core module has been completely reimplemented.
* OpenCV is now C++11 library and requires C++11-compliant compiler.
Thanks to the extended C++11 standard library, we could get rid of hand-crafted
cv::String and cv::Ptr. Now cv::String == std::string and cv::Ptr is a thin
wrapper on top of std::shared_ptr. Also, on Linux/BSD for cv::parallel_for_
we now use std::thread's instead of pthreads.
* DNN improvements
* Completely new module opencv_gapi has been added. It is the engine for very
efficient image processing, based on lazy evaluation and on-fly construction.
* Performance improvements
A few hundreds of basic kernels in OpenCV have been rewritten using so-called
"wide universal intrinsics". Those intrinsics map to SSE2, SSE4, AVX2, NEON or
VSX intrinsics, depending on the target platform and the compile flags.
* QR code detector and decoder have been added to opencv/objdetect module.
* The popular Kinect Fusion algorithm has been implemented, optimized for CPU and
GPU (OpenCL), and integrated into opencv_contrib/rgbd module.
* Very efficient and yet high-quality DIS dense optical flow algorithm has been
moved from opencv_contrib to opencv, video module. See the example.
* The slower TV L1 optical flow algorithm has been moved to opencv_contrib.
Check https://github.com/opencv/opencv/wiki/ChangeLog#version400
- Drop obsolete opencv-lib_suffix.patch
- Add 0001-Handle-absolute-OPENCV_INCLUDE_INSTALL_PATH-correctl.patch
- As this is a major version upgrade, the old 3.4.x package is still
available as opencv3
- Update to 3.4.3
* Compatibility fixes with python 3.7
* Added a new computational target DNN_TARGET_OPENCL_FP16
* Extended support of Intel's Inference Engine backend
* Enabled import of Intel's OpenVINO pre-trained networks from
intermediate representation (IR).
* tutorials improvements
Check https://github.com/opencv/opencv/wiki/ChangeLog#version343
for the complete changelog.
- Drop fix-build-i386-nosse.patch, build-workaround-issues-with-c.patch
(fixed upstream)
- Refresh patches
- Add patch to fix use of headers from C:
* build-workaround-issues-with-c.patch
- Update to 3.4.1:
* Added support for quantized TensorFlow networks
* OpenCV is now able to use Intel DL inference engine as DNN
acceleration backend
* Added AVX-512 acceleration to the performance-critical kernels
* For more information, read
https://github.com/opencv/opencv/wiki/ChangeLog#version341
- Update contrib modules to 3.4.1:
* No changelog available
- Change mechanism the contrib modules are built
- Include LICENSE of contrib tarball as well
- Build with python3 on >= 15
- Add patch to fix build on i386 without SSE:
* fix-build-i386-nosse.patch
- Refresh patches:
* fix_processor_detection_for_32bit_on_64bit.patch
* opencv-build-compare.patch
- Mention all libs explicitly
- Rebase 3.4.0 update from i@marguerite.su
- update to 3.4.0
* Added faster R-CNN support
* Javascript bindings have been extended to
cover DNN module
* DNN has been further accelerated for iGPU
using OpenCL
* On-disk caching of precompiled OpenCL
kernels has been finally implemented
* possible to load and run pre-compiled
OpenCL kernels via T-API
* Bit-exact 8-bit and 16-bit resize has been
implemented (currently supported only
bilinear interpolation)
- update face module to 3.4.0
- add opencv-lib_suffix.patch, remove LIB_SUFFIX
from OPENCV_LIB_INSTALL_PATH, as CMAKE_INSTALL
_LIBDIR is arch dependent.
- Add option to build without openblas
- Add conditionals for python2 and python3 to allow us enabling
only desired python variants when needed
- Do not depend on sphinx as py2 and py3 seem to collide there
- Readd opencv-gles.patch, it is *not* included upstream; otherwise
build breaks on all GLES Qt5 platforms (armv6l, armv7l, aarch64)
- add fix_processor_detection_for_32bit_on_64bit.patch
- Correctly set optimizations and dynamic dispatch on ARM, use
OpenCV 3.3 syntax on x86.
- Update licensing information
- change requires of python-numpy-devel to build in Leap and
to not break factory in future
- fix build error/unresolvable for Leap 42.2 and 42.3
- Update to version 3.3.1:
* Lots of various bugfixes
- Update source url
- Rename python subpackage to python2
- Do not explicitly require python-base for python subpackages
- Update to 3.3
- Dropped obsolete patches
* opencv-gcc6-fix-pch-support-PR8345.patch
* opencv-gles.patch
- Updated opencv-build-compare.patch
- Add 0001-Do-not-include-glx.h-when-using-GLES.patch
Fix build for 32bit ARM, including both GLES and desktop GL headers
causes incompatible pointer type errors
- Add conditional for the qt5/qt4 integration
* This is used only for gui tools, library is not affected
- Add provides/obsoletes for the qt5 packages to allow migration
- Drop patch opencv-qt5-sobump.diff
* Used only by the obsoleted qt5 variant
- Cleanup a bit with spec-cleaner
- Use %cmake macros
- Remove the conditions that are not really needed
- Add tests conditional disabled by default
* Many tests fail and there are missing testdata
- Switch to pkgconfig style dependencies
- Update to OpenCV 3.2.0
- Results from 11 GSoC 2016 projects have been submitted to the library:
+ sinusoidal patterns for structured light and phase unwrapping module
[Ambroise Moreau (Delia Passalacqua)]
+ DIS optical flow (excellent dense optical flow algorithm that is both
significantly better and significantly faster than Farneback’s algorithm –
our baseline), and learning-based color constancy algorithms implementation
[Alexander Bokov (Maksim Shabunin)]
+ CNN based tracking algorithm (GOTURN) [Tyan Vladimir (Antonella Cascitelli)]
+ PCAFlow and Global Patch Collider algorithms implementation
[Vladislav Samsonov (Ethan Rublee)]
+ Multi-language OpenCV Tutorials in Python, C++ and Java
[João Cartucho (Vincent Rabaud)]
+ New camera model and parallel processing for stitching pipeline
[Jiri Horner (Bo Li)]
+ Optimizations and improvements of dnn module
[Vitaliy Lyudvichenko (Anatoly Baksheev)]
+ Base64 and JSON support for file storage. Use names like
“myfilestorage.xml?base64” when writing file storage to store big chunks of
numerical data in base64-encoded form. [Iric Wu (Vadim Pisarevsky)]
+ tiny_dnn improvements and integration
[Edgar Riba (Manuele Tamburrano, Stefano Fabri)]
+ Quantization and semantic saliency detection with tiny_dnn
[Yida Wang (Manuele Tamburrano, Stefano Fabri)]
+ Word-spotting CNN based algorithm
[Anguelos Nicolaou (Lluis Gomez)]
- Contributions besides GSoC:
+ Greatly improved and accelerated dnn module in opencv_contrib:
- Many new layers, including deconvolution, LSTM etc.
- Support for semantic segmentation and SSD networks with samples.
- TensorFlow importer + sample that runs Inception net by Google.
+ More image formats and camera backends supported
+ Interactive camera calibration app
+ Multiple algorithms implemented in opencv_contrib
+ Supported latest OSes, including Ubuntu 16.04 LTS and OSX 10.12
+ Lot’s of optimizations for IA and ARM archs using parallelism, vector
instructions and new OpenCL kernels.
+ OpenCV now can use vendor-provided OpenVX and LAPACK/BLAS (including Intel MKL,
Apple’s Accelerate, OpenBLAS and Atlas) for acceleration
- Refreshed opencv-build-compare.patch
- Dropped upstream opencv-gcc5.patch
- Replace opencv-gcc6-disable-pch.patch with upstream patch
opencv-gcc6-fix-pch-support-PR8345.patch
- Enable TBB support (C++ threading library)
- Add dependency on openBLAS
- Enable ffmpeg support unconditional
- In case we build using GCC6 (or newer), add -mlra to CFLAGS to
workaround gcc bug
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=71294.
- Apply upstream patch opencv-gcc6-disable-pch.patch to disable
PCH for GCC6.
- Test for python versions greater than or equal to the current
version.
- Add python 3 support
- Added opencv_contrib_face-3.1.0.tar.bz2
* This tarball is created to take only the face module from the
contrib package. The Face module is required by libkface, which
in its turn is required by digikam.
- Added _constraints file to avoid random failures on small workers
(at least for builds on PMBS)
- Update to OpenCV 3.1.0
- A lot of new functionality has been introduced during Google
Summer of Code 2015:
+ “Omnidirectional Cameras Calibration and Stereo 3D
Reconstruction” – opencv_contrib/ccalib module
(Baisheng Lai, Bo Li)
+ “Structure From Motion” – opencv_contrib/sfm module
(Edgar Riba, Vincent Rabaud)
+ “Improved Deformable Part-based Models” – opencv_contrib/dpm
module (Jiaolong Xu, Bence Magyar)
+ “Real-time Multi-object Tracking using Kernelized Correlation
Filter” – opencv_contrib/tracking module
(Laksono Kurnianggoro, Fernando J. Iglesias Garcia)
+ “Improved and expanded Scene Text Detection” –
opencv_contrib/text module (Lluis Gomez, Vadim Pisarevsky)
+ “Stereo correspondence improvements” – opencv_contrib/stereo
module (Mircea Paul Muresan, Sergei Nosov)
+ “Structured-Light System Calibration” –
opencv_contrib/structured_light (Roberta Ravanelli,
Delia Passalacqua, Stefano Fabri, Claudia Rapuano)
+ “Chessboard+ArUco for camera calibration” –
opencv_contrib/aruco (Sergio Garrido, Prasanna, Gary Bradski)
+ “Implementation of universal interface for deep neural
network frameworks” – opencv_contrib/dnn module
(Vitaliy Lyudvichenko, Anatoly Baksheev)
+ “Recent advances in edge-aware filtering, improved SGBM
stereo algorithm” – opencv/calib3d and opencv_contrib/ximgproc
(Alexander Bokov, Maksim Shabunin)
+ “Improved ICF detector, waldboost implementation” –
opencv_contrib/xobjdetect (Vlad Shakhuro, Alexander Bovyrin)
+ “Multi-target TLD tracking” – opencv_contrib/tracking module
(Vladimir Tyan, Antonella Cascitelli)
+ “3D pose estimation using CNNs” – opencv_contrib/cnn_3dobj
(Yida Wang, Manuele Tamburrano, Stefano Fabri)
- Many great contributions made by the community, such as:
+ Support for HDF5 format
+ New/Improved optical flow algorithms
+ Multiple new image processing algorithms for filtering,
segmentation and feature detection
+ Superpixel segmentation and much more
- IPPICV is now based on IPP 9.0.1, which should make OpenCV
even faster on modern Intel chips
- opencv_contrib modules can now be included into the
opencv2.framework for iOS
- Newest operating systems are supported: Windows 10 and
OSX 10.11 (Visual Studio 2015 and XCode 7.1.1)
- Interoperability between T-API and OpenCL, OpenGL, DirectX and
Video Acceleration API on Linux, as well as Android 5 camera.
- HAL (Hardware Acceleration Layer) module functionality has been
moved into corresponding basic modules; the HAL replacement
mechanism has been implemented along with the examples
- Removed improve-sphinx-search.diff, opencv-altivec-vector.patch,
opencv-pkgconfig.patch and opencv-samples.patch, fixed upstream.
- Fixed opencv-qt5-sobump.diff, opencv-build-compare.patch,
opencv-gcc5.patch and opencv-gles.patch.
- Version OpenCV 3.0.0
+ ~1500 patches, submitted as PR @ github. All our patches go
the same route.
+ opencv_contrib (http://github.com/itseez/opencv_contrib)
repository has been added. A lot of new functionality is there
already! opencv_contrib is only compatible with 3.0/master,
not 2.4. Clone the repository and use “cmake …
-D OPENCV_EXTRA_MODULES_PATH=<path_to opencv_contrib/modules> …”
to build opencv and opencv_contrib together.
+ a subset of Intel IPP (IPPCV) is given to us and our users free
of charge, free of licensing fees, for commercial and
non-commerical use. It’s used by default in x86 and x64 builds
on Windows, Linux and Mac.
+ T-API (transparent API) has been introduced, this is transparent
GPU acceleration layer using OpenCL. It does not add any
compile-time or runtime dependency of OpenCL. When OpenCL is
available, it’s detected and used, but it can be disabled at
compile time or at runtime. It covers ~100 OpenCV functions.
This work has been done by contract and with generous support
from AMD and Intel companies.
+ ~40 OpenCV functions have been accelerated using NEON intrinsics
and because these are mostly basic functions, some higher-level
functions got accelerated as well.
+ There is also new OpenCV HAL layer that will simplifies creation
of NEON-optimized code and that should form a base for the
open-source and proprietary OpenCV accelerators.
+ The documentation is now in Doxygen: http://docs.opencv.org/master/
+ We cleaned up API of many high-level algorithms from features2d,
calib3d, objdetect etc. They now follow the uniform
“abstract interface – hidden implementation” pattern and make
extensive use of smart pointers (Ptr<>).
+ Greatly improved and extended Python & Java bindings (also,
see below on the Python bindings), newly introduced Matlab
bindings (still in alpha stage).
+ Improved Android support – now OpenCV Manager is in Java and
supports both 2.4 and 3.0.
+ Greatly improved WinRT support, including video capturing and
multi-threading capabilities. Thanks for Microsoft team for this!
+ Big thanks to Google who funded several successive GSoC programs
and let OpenCV in. The results of many successful GSoC 2013 and
2014 projects have been integrated in opencv 3.0 and
opencv_contrib (earlier results are also available in
OpenCV 2.4.x). We can name:
- text detection
- many computational photography algorithms (HDR, inpainting,
edge-aware filters, superpixels, …)
- tracking and optical flow algorithms
- new features, including line descriptors, KAZE/AKAZE
- general use optimization (hill climbing, linear programming)
- greatly improved Python support, including Python 3.0 support,
many new tutorials & samples on how to use OpenCV with Python.
- 2d shape matching module and 3d surface matching module
- RGB-D module
- VTK-based 3D visualization module
- etc.
+ Besides Google, we enjoyed (and hope that you will enjoy too)
many useful contributions from community, like:
- biologically inspired vision module
- DAISY features, LATCH descriptor, improved BRIEF
- image registration module
- etc.
- Reduce build-compare noise
opencv-build-compare.patch
- Remove BuildRequirement for python-sphinx in SLE12, since it's
not available there and it's not a mandatory requirement.
- Reduce differences between two spec files
- Use pkgconfig for ffmpeg BuildRequires
- Update improve-sphinx-search.diff for new python-Sphinx(1.3.1)
* now that sphinx-build disallow executing without arguments and
give you "Insufficient arguments" error, use "sphinx-build -h"
instead
* the default usages output ie. sphinx-build(or --help) no longer
are standard error but standard output, drop OUTPUT_QUIET and
add OUTPUT_VARIABLE throws the output to SPHINX_OUTPUT as well
- support gcc 5 (i.e. gcc versions without minor version):
opencv-gcc5.patch
- Update to OpenCV 2.4.11 - can't find NEWS or Changelog
merely collecting bug fixes while 3.0 is in the making, 2.4.11
didn't even make it on their web page, it's only on download
server
- remove opencv-underlinking.patch as obsolete
- remove upstream patch bomb_commit_gstreamer-1x-support.patch
- commenting out opencv-pkgconfig.patch - possibly it requires a rebase,
but the problem it tries to solve is unclear
- Add specific buildrequires for libpng15, so that we are
building against the system provided libpng.
- Update to OpenCV 2.4.9
More info at:
http://opencv.org/opencv-2-4-9-is-out.html
The brief list of changes:
* new 3D visualization module ‘viz’;
* performance fixes in ‘ocl’ module;
* fixes in Android Camera;
* improved CUDA support for mobile platforms;
* bugfixes from community;
* 55 reported bugs have been closed;
* 156 pull requests have been merged.
- Drop the BuildRequires on libucil and libunicap for Factory. This
stops us from getting ride of Gstreamer 0.10 and besides these two
libraries seem to be unmaintained upstream as that the latest
actions are from 2010
- Add upstream patch (3.0 version) to support Gstreamer 1.x
* bomb_commit_gstreamer-1x-support.patch
- Upstream now provides tarballs with source only as git tags
from github so update Source0 path.
- Add requires on various X extensions linked to opencv_ts module.
As those are present in the .pc file we need it anyway.
- Update to OpenCV 2.4.8
More info at:
http://opencv.org/opencv-2-4-8.html
The brief list of changes:
* NVidia CUDA support on Android devices with CUDA capable SoC and
CUDA sample;
* Concurrent kernel execution and user defined context support for
OpenCL;
* Integration with Intel Perceptual SDK and new depth sensors support
for Windows;
* 32 reported bugs have been closed;
* 139 pull requests have been merged;
- Fix build with altivec:
opencv-altivec-vector.patch
- Added opencv-pkgconfig.patch: make sure to provide link flags in
OpenCV pc file (bnc#853036)
- Update to OpenCV 2.4.7
More info at:
http://opencv.org/opencv-2-4-7-is-out.html
The brief list of changes:
* dynamic OpenCL runtime loading, setting default OpenCL device
via env var, many bug-fixes and some new optimization with OpenCL
* bug-fixes and new optimizations in CUDA stuff
* latest NDK and Android OS support, Native Android Camera tuning
* minor fixes, XAML sample and MS Certification compatibility
in WinRT stuff
* 382 pull requests have been merged
* 54 reported bugs have been fixed
- Added pkgconfig(glu) Requires to devel package, as per .pc file
- Make devel package provides also devel-static one
- Drop assume-Sphinx-is-there.diff, and add improve-sphinx-search.diff,
for properly finding sphinx with alphabetic chars in version
- Add patch assume-Sphinx-is-there.diff to fix building with
Sphinx versions that have alphanumeric characters in the version
(Only for factory builds at the moment)
- Use eigen3 instead of eigen2 as build requirement for openSUSE > 12.3.
- Enable compilation with libucil and libunicap.
- Removed dos2unix build requirement (not needed anymore).
- Update to OpenCV 2.4.6.1
More info at:
http://opencv.org/opencv-2-4-6-is-out.html
The brief list of changes:
* added video file i/o Windows RT and sample application using
camera, enabled parallelization with TBB or MS Concurrency
* added CUDA 5.5 support for desktop and ARM systems
* added Qt 5 support
* added many new OpenCL algorithms ports, included OpenCL binaries
into the Windows superpack
* iOS build scripts (together with Android ones) moved to
‘opencv/platforms’ directory
* added functions for UIImage <-> cv::Mat conversion
* correct front/back camera selection in Android app framework
* added Linaro NDK support and fixes for MIPS to Android CMake
toolchain
* stability has been improved by a lot, numerous bug-fixes across
all the library
- build with LFS_CFLAGS in 32 bit archs.
- Disable SSE3 for all architectures (bnc#814333)
- Disable SSE(2) on non x86_64 architectures, causes crashing
kde#276923, bnc#789173
- Update to OpenCV 2.4.5
More info at:
http://opencv.org/opencv-2-4-5-is-out.html
The brief list of changes:
* experimental WinRT support
* new video super-resolution module
* CLAHE (adaptive histogram equalization) algorithm on both CPU
and GPU
* further improvements and extensions in ocl module
(stereo block matching and belief propagation have been added,
fixed crashes on Intel HD4000)
* Visual Studio 2012 cv::Mat visualizer plugin debugger tutorial
from Microsoft Research
* OpenCV4Android SDK improvements
(NDK r8e support, native activity sample using OpenCV Manager,
bug-fixes)
* ~25 reported problems have been resolved since 2.4.4, ~78 pull
requests have been merged, thanks everybody who participated!
- Update to OpenCV 2.4.4
More info at:
http://opencv.org/opencv-2-4-4-is-out.html
The brief list of changes:
* OpenCV Java bindings are ported from Android to desktop Java!
Actually any JVM language will work, see Tutorial for details,
and Java or Scala code samples.
* Android application framework, samples, tutorials, and OpenCV
Manager are improved.
* Optimizations for the new NVIDIA Kepler architecture, CARMA
platform support and other new optimizations in CUDA.
* OpenCL module now builds successfully with various SDKs (from
AMD, NVIDIA, Intel and Apple) and runs well on different GPUs
(AMD, NVidia, Intel HD4000). A lot of new functionality has been
added, tons of bugs fixed, performance of many functions has
been significantly improved.
* 100+ reported problems have been resolved since 2.4.3, thanks
everybody who participated!
- Drop the buildrequire for libxine
- Update to OpenCV 2.4.3
More info at:
http://opencv.org/opencv-2-4-3-released.html
The nicely formatted changelog can be seen here:
http://code.opencv.org/projects/opencv/wiki/ChangeLog;
here are the highlights:
* A lot of good stuff from the Google Summer of Code 2012 has been
integrated; this was a very productive summer!
* Significantly improved and optimized Android and iOS ports.
* Greatly extended GPU (i.e. CUDA-based) module.
* The brand new ocl (OpenCL-based) module that unleashes GPU power
also for AMD and Intel GPU users. It’s not included into the
binary package, since there are different SDKs, and it’s not
turned on by default. You need to run CMake and turn on
“WITH_OPENCL”. Also, please note that this is very first version
of the module, so it may be not very stable and not very
functional.
* Much better performance on many-core systems out of the box. You
do not need TBB anymore on MacOSX, iOS and Windows. BTW, the
binary package for Windows is now built without TBB support.
Libraries and DLLs for Visual Studio 2010 use the Concurrency
framework.
* About 130 bugs have been fixed since 2.4.2.
* Since 2.4.3rc we fixed several more problems, in particular some
compile problems with iOS 6 SDK.
- buildrequire glu
- Update to OpenCV 2.4.2
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Drop opencv-datadir.patch to comply with upstream directory layout
- Update to OpenCV 2.4.1
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Update to OpenCV 2.4.0
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Add opencv-gcc47.patch: Fix build with gcc 4.7.
- Use Explicit Buildrequires on several needed libraries
future dependency cleanups may/will cause build to fail otherwise.
- Add upstream r6881 to fix clang compatibility
- uncomment libraries not in 12.1 for now
- Changed groups (fix for RPMLINT warning)
- Added check for duplicate files (fix for RPMLINT warning)
- Added py_requires macros and python-base dependencies (fix for RPMLINT warning)
- Escaped macros (fix for RPMLINT warning)
- Fixed end-of-line encoding problems (fix for RPMLINT warning)
- Added libeigen2-devel buildrequires
- Added libunicap and libucil buildrequires (libunicap supports requires libucil)
- Cleaned up spec file formatting
- Dropped opencv-2.3-ffmpeg.patch, applied upstream
- Revive opencv-2.3-ffmpeg.patch, needs rebase
- Tag all patches according to openSUSE packaging guidelines
- Removed opencv-2.3-cmake.patch, old cmake cannot be used any more.
- Python bindings cannot be built without NumPy any more.
- Update to OpenCV 2.3.1
- Update and readd opencv-2.3-underlinking.patch since it is still
necessary.
- Fix support for new ffmpeg versions
- Removed unnecessary patches
- Enable Python NumPy support on openSUSE 11.2
- Build Qt instead of Gtk GUI
- Fix cmake files for openSUSE 11.1
- No GStreamer support on openSUSE 11.1
- Update to OpenCV 2.3.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Fix build on openSUSE 11.2
- Add opencv-v4l-2.6.38.patch: use the new libv4l2 interface
- Enable Python NumPy support
- SWIG is not required any more
- Enable OpenEXR support
- Update to OpenCV 2.2.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Use system zlib, oh, and do not export ZLIB symbols to
other applications, clashes ensued.
- fix build with gcc 4.6
- add -underlinking patch
- devel package renamed to opencv-devel, so that switching between
OBS and packman opencv packages is easier
- fix gstreamer support
- fix xine support
- fix some rpmlint warnings
- fix shared libraries permissions
- Do not waste resources building the tests as we do not run them
- Do not disable SSE,SSE2,etc. According to OpenCV changelog,
it should be safe to leave these enabled.
- fix build on openSUSE 11.0
- Update to OpenCV 2.1.0:
* The whole OpenCV is now using exceptions instead of the old
libc-style mechanism
* Experimental "static" OpenCV configuration in CMake was
contributed by Jose Luis Blanco.
Pass "BUILD_SHARED_LIBS=OFF" to CMake to build OpenCV statically.
* new improved version of one-way descriptor is added
* User can now control the image areas visible after the stereo
rectification
* Fullscreen has been added (thanks to Yannick Verdie).
* Further info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- fix build with libpng14
- small spec file cleanup
- Moved to the KDE repositories to enable inclusion in kipi-plugins
- Initial package
OBS-URL: https://build.opensuse.org/request/show/714221
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/opencv?expand=0&rev=73
2019-07-17 13:13:58 +02:00
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Provides: python3-%{name}-qt5 = %{version}
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Obsoletes: python3-%{name}-qt5 < %{version}
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2016-03-26 15:20:54 +01:00
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%description -n python3-%{name}
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This package contains Python 3 bindings for the OpenCV library.
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2024-02-05 08:31:49 +01:00
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%endif
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2010-03-08 18:16:50 +01:00
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2013-08-01 15:56:40 +02:00
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%package doc
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2010-03-08 18:16:50 +01:00
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Summary: Documentation and examples for OpenCV
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2017-11-19 11:08:51 +01:00
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License: BSD-3-Clause
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2017-07-11 08:24:11 +02:00
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Group: Documentation/Other
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2010-03-08 18:16:50 +01:00
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# Since this package also contains examples that need -devel to be compiled
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2017-07-11 08:24:11 +02:00
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Suggests: %{name}-devel
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Accepting request 714221 from science
- Update to version 4.1.0
* DNN module:
+ Reduced peak memory consumption for some models up to 30%.
+ Inference Engine
- Inference Engine 2018R3 is now a minimal supported version of IE.
- Myriad X (Intel® Neural Compute Stick 2) is now supported and tested.
- Automatic IR network reshaping for different inputs.
- Improved samples to work with models from OpenVINO Open Model Zoo
+ New networks from TensorFlow Object Detection API: Faster-RCNNs, SSDs
and Mask-RCNN with dilated convolutions, FPN SSD
* Performance improvements:
+ More optimization using AVX2 instruction set.
+ Automatic runtime dispatching is available for large set of functions
from core and imgproc modules.
* Other improvements:
+ Matplotlib Perceptually Uniform Sequential colormaps
+ Add keypoints matching visualization for real-time pose estimation tutorial
+ Add Hand-Eye calibration methods
+ Java: improved support for multidimensional arrays (Mat)
+ Dynamically loaded videoio backends (FFmpeg, GStreamer)
+ opencv_contrib: Robust local optical flow (RLOF) implementations
+ opencv_contrib: Implementation of Quasi Dense Stereo algorithm
+ opencv_contrib: New module: Image Quality Analysis (IQA) API
+ opencv_contrib: BRISQUE No Reference Image Quality Assessment (IQA) API
Check https://github.com/opencv/opencv/wiki/ChangeLog#version410
- Update to version 4.0.0
* A lot of C API from OpenCV 1.x has been removed. The affected modules are
objdetect, photo, video, videoio, imgcodecs, calib3d.
* Persistence (storing and loading structured data to/from XML, YAML or JSON)
in the core module has been completely reimplemented.
* OpenCV is now C++11 library and requires C++11-compliant compiler.
Thanks to the extended C++11 standard library, we could get rid of hand-crafted
cv::String and cv::Ptr. Now cv::String == std::string and cv::Ptr is a thin
wrapper on top of std::shared_ptr. Also, on Linux/BSD for cv::parallel_for_
we now use std::thread's instead of pthreads.
* DNN improvements
* Completely new module opencv_gapi has been added. It is the engine for very
efficient image processing, based on lazy evaluation and on-fly construction.
* Performance improvements
A few hundreds of basic kernels in OpenCV have been rewritten using so-called
"wide universal intrinsics". Those intrinsics map to SSE2, SSE4, AVX2, NEON or
VSX intrinsics, depending on the target platform and the compile flags.
* QR code detector and decoder have been added to opencv/objdetect module.
* The popular Kinect Fusion algorithm has been implemented, optimized for CPU and
GPU (OpenCL), and integrated into opencv_contrib/rgbd module.
* Very efficient and yet high-quality DIS dense optical flow algorithm has been
moved from opencv_contrib to opencv, video module. See the example.
* The slower TV L1 optical flow algorithm has been moved to opencv_contrib.
Check https://github.com/opencv/opencv/wiki/ChangeLog#version400
- Drop obsolete opencv-lib_suffix.patch
- Add 0001-Handle-absolute-OPENCV_INCLUDE_INSTALL_PATH-correctl.patch
- As this is a major version upgrade, the old 3.4.x package is still
available as opencv3
- Update to 3.4.3
* Compatibility fixes with python 3.7
* Added a new computational target DNN_TARGET_OPENCL_FP16
* Extended support of Intel's Inference Engine backend
* Enabled import of Intel's OpenVINO pre-trained networks from
intermediate representation (IR).
* tutorials improvements
Check https://github.com/opencv/opencv/wiki/ChangeLog#version343
for the complete changelog.
- Drop fix-build-i386-nosse.patch, build-workaround-issues-with-c.patch
(fixed upstream)
- Refresh patches
- Add patch to fix use of headers from C:
* build-workaround-issues-with-c.patch
- Update to 3.4.1:
* Added support for quantized TensorFlow networks
* OpenCV is now able to use Intel DL inference engine as DNN
acceleration backend
* Added AVX-512 acceleration to the performance-critical kernels
* For more information, read
https://github.com/opencv/opencv/wiki/ChangeLog#version341
- Update contrib modules to 3.4.1:
* No changelog available
- Change mechanism the contrib modules are built
- Include LICENSE of contrib tarball as well
- Build with python3 on >= 15
- Add patch to fix build on i386 without SSE:
* fix-build-i386-nosse.patch
- Refresh patches:
* fix_processor_detection_for_32bit_on_64bit.patch
* opencv-build-compare.patch
- Mention all libs explicitly
- Rebase 3.4.0 update from i@marguerite.su
- update to 3.4.0
* Added faster R-CNN support
* Javascript bindings have been extended to
cover DNN module
* DNN has been further accelerated for iGPU
using OpenCL
* On-disk caching of precompiled OpenCL
kernels has been finally implemented
* possible to load and run pre-compiled
OpenCL kernels via T-API
* Bit-exact 8-bit and 16-bit resize has been
implemented (currently supported only
bilinear interpolation)
- update face module to 3.4.0
- add opencv-lib_suffix.patch, remove LIB_SUFFIX
from OPENCV_LIB_INSTALL_PATH, as CMAKE_INSTALL
_LIBDIR is arch dependent.
- Add option to build without openblas
- Add conditionals for python2 and python3 to allow us enabling
only desired python variants when needed
- Do not depend on sphinx as py2 and py3 seem to collide there
- Readd opencv-gles.patch, it is *not* included upstream; otherwise
build breaks on all GLES Qt5 platforms (armv6l, armv7l, aarch64)
- add fix_processor_detection_for_32bit_on_64bit.patch
- Correctly set optimizations and dynamic dispatch on ARM, use
OpenCV 3.3 syntax on x86.
- Update licensing information
- change requires of python-numpy-devel to build in Leap and
to not break factory in future
- fix build error/unresolvable for Leap 42.2 and 42.3
- Update to version 3.3.1:
* Lots of various bugfixes
- Update source url
- Rename python subpackage to python2
- Do not explicitly require python-base for python subpackages
- Update to 3.3
- Dropped obsolete patches
* opencv-gcc6-fix-pch-support-PR8345.patch
* opencv-gles.patch
- Updated opencv-build-compare.patch
- Add 0001-Do-not-include-glx.h-when-using-GLES.patch
Fix build for 32bit ARM, including both GLES and desktop GL headers
causes incompatible pointer type errors
- Add conditional for the qt5/qt4 integration
* This is used only for gui tools, library is not affected
- Add provides/obsoletes for the qt5 packages to allow migration
- Drop patch opencv-qt5-sobump.diff
* Used only by the obsoleted qt5 variant
- Cleanup a bit with spec-cleaner
- Use %cmake macros
- Remove the conditions that are not really needed
- Add tests conditional disabled by default
* Many tests fail and there are missing testdata
- Switch to pkgconfig style dependencies
- Update to OpenCV 3.2.0
- Results from 11 GSoC 2016 projects have been submitted to the library:
+ sinusoidal patterns for structured light and phase unwrapping module
[Ambroise Moreau (Delia Passalacqua)]
+ DIS optical flow (excellent dense optical flow algorithm that is both
significantly better and significantly faster than Farneback’s algorithm –
our baseline), and learning-based color constancy algorithms implementation
[Alexander Bokov (Maksim Shabunin)]
+ CNN based tracking algorithm (GOTURN) [Tyan Vladimir (Antonella Cascitelli)]
+ PCAFlow and Global Patch Collider algorithms implementation
[Vladislav Samsonov (Ethan Rublee)]
+ Multi-language OpenCV Tutorials in Python, C++ and Java
[João Cartucho (Vincent Rabaud)]
+ New camera model and parallel processing for stitching pipeline
[Jiri Horner (Bo Li)]
+ Optimizations and improvements of dnn module
[Vitaliy Lyudvichenko (Anatoly Baksheev)]
+ Base64 and JSON support for file storage. Use names like
“myfilestorage.xml?base64” when writing file storage to store big chunks of
numerical data in base64-encoded form. [Iric Wu (Vadim Pisarevsky)]
+ tiny_dnn improvements and integration
[Edgar Riba (Manuele Tamburrano, Stefano Fabri)]
+ Quantization and semantic saliency detection with tiny_dnn
[Yida Wang (Manuele Tamburrano, Stefano Fabri)]
+ Word-spotting CNN based algorithm
[Anguelos Nicolaou (Lluis Gomez)]
- Contributions besides GSoC:
+ Greatly improved and accelerated dnn module in opencv_contrib:
- Many new layers, including deconvolution, LSTM etc.
- Support for semantic segmentation and SSD networks with samples.
- TensorFlow importer + sample that runs Inception net by Google.
+ More image formats and camera backends supported
+ Interactive camera calibration app
+ Multiple algorithms implemented in opencv_contrib
+ Supported latest OSes, including Ubuntu 16.04 LTS and OSX 10.12
+ Lot’s of optimizations for IA and ARM archs using parallelism, vector
instructions and new OpenCL kernels.
+ OpenCV now can use vendor-provided OpenVX and LAPACK/BLAS (including Intel MKL,
Apple’s Accelerate, OpenBLAS and Atlas) for acceleration
- Refreshed opencv-build-compare.patch
- Dropped upstream opencv-gcc5.patch
- Replace opencv-gcc6-disable-pch.patch with upstream patch
opencv-gcc6-fix-pch-support-PR8345.patch
- Enable TBB support (C++ threading library)
- Add dependency on openBLAS
- Enable ffmpeg support unconditional
- In case we build using GCC6 (or newer), add -mlra to CFLAGS to
workaround gcc bug
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=71294.
- Apply upstream patch opencv-gcc6-disable-pch.patch to disable
PCH for GCC6.
- Test for python versions greater than or equal to the current
version.
- Add python 3 support
- Added opencv_contrib_face-3.1.0.tar.bz2
* This tarball is created to take only the face module from the
contrib package. The Face module is required by libkface, which
in its turn is required by digikam.
- Added _constraints file to avoid random failures on small workers
(at least for builds on PMBS)
- Update to OpenCV 3.1.0
- A lot of new functionality has been introduced during Google
Summer of Code 2015:
+ “Omnidirectional Cameras Calibration and Stereo 3D
Reconstruction” – opencv_contrib/ccalib module
(Baisheng Lai, Bo Li)
+ “Structure From Motion” – opencv_contrib/sfm module
(Edgar Riba, Vincent Rabaud)
+ “Improved Deformable Part-based Models” – opencv_contrib/dpm
module (Jiaolong Xu, Bence Magyar)
+ “Real-time Multi-object Tracking using Kernelized Correlation
Filter” – opencv_contrib/tracking module
(Laksono Kurnianggoro, Fernando J. Iglesias Garcia)
+ “Improved and expanded Scene Text Detection” –
opencv_contrib/text module (Lluis Gomez, Vadim Pisarevsky)
+ “Stereo correspondence improvements” – opencv_contrib/stereo
module (Mircea Paul Muresan, Sergei Nosov)
+ “Structured-Light System Calibration” –
opencv_contrib/structured_light (Roberta Ravanelli,
Delia Passalacqua, Stefano Fabri, Claudia Rapuano)
+ “Chessboard+ArUco for camera calibration” –
opencv_contrib/aruco (Sergio Garrido, Prasanna, Gary Bradski)
+ “Implementation of universal interface for deep neural
network frameworks” – opencv_contrib/dnn module
(Vitaliy Lyudvichenko, Anatoly Baksheev)
+ “Recent advances in edge-aware filtering, improved SGBM
stereo algorithm” – opencv/calib3d and opencv_contrib/ximgproc
(Alexander Bokov, Maksim Shabunin)
+ “Improved ICF detector, waldboost implementation” –
opencv_contrib/xobjdetect (Vlad Shakhuro, Alexander Bovyrin)
+ “Multi-target TLD tracking” – opencv_contrib/tracking module
(Vladimir Tyan, Antonella Cascitelli)
+ “3D pose estimation using CNNs” – opencv_contrib/cnn_3dobj
(Yida Wang, Manuele Tamburrano, Stefano Fabri)
- Many great contributions made by the community, such as:
+ Support for HDF5 format
+ New/Improved optical flow algorithms
+ Multiple new image processing algorithms for filtering,
segmentation and feature detection
+ Superpixel segmentation and much more
- IPPICV is now based on IPP 9.0.1, which should make OpenCV
even faster on modern Intel chips
- opencv_contrib modules can now be included into the
opencv2.framework for iOS
- Newest operating systems are supported: Windows 10 and
OSX 10.11 (Visual Studio 2015 and XCode 7.1.1)
- Interoperability between T-API and OpenCL, OpenGL, DirectX and
Video Acceleration API on Linux, as well as Android 5 camera.
- HAL (Hardware Acceleration Layer) module functionality has been
moved into corresponding basic modules; the HAL replacement
mechanism has been implemented along with the examples
- Removed improve-sphinx-search.diff, opencv-altivec-vector.patch,
opencv-pkgconfig.patch and opencv-samples.patch, fixed upstream.
- Fixed opencv-qt5-sobump.diff, opencv-build-compare.patch,
opencv-gcc5.patch and opencv-gles.patch.
- Version OpenCV 3.0.0
+ ~1500 patches, submitted as PR @ github. All our patches go
the same route.
+ opencv_contrib (http://github.com/itseez/opencv_contrib)
repository has been added. A lot of new functionality is there
already! opencv_contrib is only compatible with 3.0/master,
not 2.4. Clone the repository and use “cmake …
-D OPENCV_EXTRA_MODULES_PATH=<path_to opencv_contrib/modules> …”
to build opencv and opencv_contrib together.
+ a subset of Intel IPP (IPPCV) is given to us and our users free
of charge, free of licensing fees, for commercial and
non-commerical use. It’s used by default in x86 and x64 builds
on Windows, Linux and Mac.
+ T-API (transparent API) has been introduced, this is transparent
GPU acceleration layer using OpenCL. It does not add any
compile-time or runtime dependency of OpenCL. When OpenCL is
available, it’s detected and used, but it can be disabled at
compile time or at runtime. It covers ~100 OpenCV functions.
This work has been done by contract and with generous support
from AMD and Intel companies.
+ ~40 OpenCV functions have been accelerated using NEON intrinsics
and because these are mostly basic functions, some higher-level
functions got accelerated as well.
+ There is also new OpenCV HAL layer that will simplifies creation
of NEON-optimized code and that should form a base for the
open-source and proprietary OpenCV accelerators.
+ The documentation is now in Doxygen: http://docs.opencv.org/master/
+ We cleaned up API of many high-level algorithms from features2d,
calib3d, objdetect etc. They now follow the uniform
“abstract interface – hidden implementation” pattern and make
extensive use of smart pointers (Ptr<>).
+ Greatly improved and extended Python & Java bindings (also,
see below on the Python bindings), newly introduced Matlab
bindings (still in alpha stage).
+ Improved Android support – now OpenCV Manager is in Java and
supports both 2.4 and 3.0.
+ Greatly improved WinRT support, including video capturing and
multi-threading capabilities. Thanks for Microsoft team for this!
+ Big thanks to Google who funded several successive GSoC programs
and let OpenCV in. The results of many successful GSoC 2013 and
2014 projects have been integrated in opencv 3.0 and
opencv_contrib (earlier results are also available in
OpenCV 2.4.x). We can name:
- text detection
- many computational photography algorithms (HDR, inpainting,
edge-aware filters, superpixels, …)
- tracking and optical flow algorithms
- new features, including line descriptors, KAZE/AKAZE
- general use optimization (hill climbing, linear programming)
- greatly improved Python support, including Python 3.0 support,
many new tutorials & samples on how to use OpenCV with Python.
- 2d shape matching module and 3d surface matching module
- RGB-D module
- VTK-based 3D visualization module
- etc.
+ Besides Google, we enjoyed (and hope that you will enjoy too)
many useful contributions from community, like:
- biologically inspired vision module
- DAISY features, LATCH descriptor, improved BRIEF
- image registration module
- etc.
- Reduce build-compare noise
opencv-build-compare.patch
- Remove BuildRequirement for python-sphinx in SLE12, since it's
not available there and it's not a mandatory requirement.
- Reduce differences between two spec files
- Use pkgconfig for ffmpeg BuildRequires
- Update improve-sphinx-search.diff for new python-Sphinx(1.3.1)
* now that sphinx-build disallow executing without arguments and
give you "Insufficient arguments" error, use "sphinx-build -h"
instead
* the default usages output ie. sphinx-build(or --help) no longer
are standard error but standard output, drop OUTPUT_QUIET and
add OUTPUT_VARIABLE throws the output to SPHINX_OUTPUT as well
- support gcc 5 (i.e. gcc versions without minor version):
opencv-gcc5.patch
- Update to OpenCV 2.4.11 - can't find NEWS or Changelog
merely collecting bug fixes while 3.0 is in the making, 2.4.11
didn't even make it on their web page, it's only on download
server
- remove opencv-underlinking.patch as obsolete
- remove upstream patch bomb_commit_gstreamer-1x-support.patch
- commenting out opencv-pkgconfig.patch - possibly it requires a rebase,
but the problem it tries to solve is unclear
- Add specific buildrequires for libpng15, so that we are
building against the system provided libpng.
- Update to OpenCV 2.4.9
More info at:
http://opencv.org/opencv-2-4-9-is-out.html
The brief list of changes:
* new 3D visualization module ‘viz’;
* performance fixes in ‘ocl’ module;
* fixes in Android Camera;
* improved CUDA support for mobile platforms;
* bugfixes from community;
* 55 reported bugs have been closed;
* 156 pull requests have been merged.
- Drop the BuildRequires on libucil and libunicap for Factory. This
stops us from getting ride of Gstreamer 0.10 and besides these two
libraries seem to be unmaintained upstream as that the latest
actions are from 2010
- Add upstream patch (3.0 version) to support Gstreamer 1.x
* bomb_commit_gstreamer-1x-support.patch
- Upstream now provides tarballs with source only as git tags
from github so update Source0 path.
- Add requires on various X extensions linked to opencv_ts module.
As those are present in the .pc file we need it anyway.
- Update to OpenCV 2.4.8
More info at:
http://opencv.org/opencv-2-4-8.html
The brief list of changes:
* NVidia CUDA support on Android devices with CUDA capable SoC and
CUDA sample;
* Concurrent kernel execution and user defined context support for
OpenCL;
* Integration with Intel Perceptual SDK and new depth sensors support
for Windows;
* 32 reported bugs have been closed;
* 139 pull requests have been merged;
- Fix build with altivec:
opencv-altivec-vector.patch
- Added opencv-pkgconfig.patch: make sure to provide link flags in
OpenCV pc file (bnc#853036)
- Update to OpenCV 2.4.7
More info at:
http://opencv.org/opencv-2-4-7-is-out.html
The brief list of changes:
* dynamic OpenCL runtime loading, setting default OpenCL device
via env var, many bug-fixes and some new optimization with OpenCL
* bug-fixes and new optimizations in CUDA stuff
* latest NDK and Android OS support, Native Android Camera tuning
* minor fixes, XAML sample and MS Certification compatibility
in WinRT stuff
* 382 pull requests have been merged
* 54 reported bugs have been fixed
- Added pkgconfig(glu) Requires to devel package, as per .pc file
- Make devel package provides also devel-static one
- Drop assume-Sphinx-is-there.diff, and add improve-sphinx-search.diff,
for properly finding sphinx with alphabetic chars in version
- Add patch assume-Sphinx-is-there.diff to fix building with
Sphinx versions that have alphanumeric characters in the version
(Only for factory builds at the moment)
- Use eigen3 instead of eigen2 as build requirement for openSUSE > 12.3.
- Enable compilation with libucil and libunicap.
- Removed dos2unix build requirement (not needed anymore).
- Update to OpenCV 2.4.6.1
More info at:
http://opencv.org/opencv-2-4-6-is-out.html
The brief list of changes:
* added video file i/o Windows RT and sample application using
camera, enabled parallelization with TBB or MS Concurrency
* added CUDA 5.5 support for desktop and ARM systems
* added Qt 5 support
* added many new OpenCL algorithms ports, included OpenCL binaries
into the Windows superpack
* iOS build scripts (together with Android ones) moved to
‘opencv/platforms’ directory
* added functions for UIImage <-> cv::Mat conversion
* correct front/back camera selection in Android app framework
* added Linaro NDK support and fixes for MIPS to Android CMake
toolchain
* stability has been improved by a lot, numerous bug-fixes across
all the library
- build with LFS_CFLAGS in 32 bit archs.
- Disable SSE3 for all architectures (bnc#814333)
- Disable SSE(2) on non x86_64 architectures, causes crashing
kde#276923, bnc#789173
- Update to OpenCV 2.4.5
More info at:
http://opencv.org/opencv-2-4-5-is-out.html
The brief list of changes:
* experimental WinRT support
* new video super-resolution module
* CLAHE (adaptive histogram equalization) algorithm on both CPU
and GPU
* further improvements and extensions in ocl module
(stereo block matching and belief propagation have been added,
fixed crashes on Intel HD4000)
* Visual Studio 2012 cv::Mat visualizer plugin debugger tutorial
from Microsoft Research
* OpenCV4Android SDK improvements
(NDK r8e support, native activity sample using OpenCV Manager,
bug-fixes)
* ~25 reported problems have been resolved since 2.4.4, ~78 pull
requests have been merged, thanks everybody who participated!
- Update to OpenCV 2.4.4
More info at:
http://opencv.org/opencv-2-4-4-is-out.html
The brief list of changes:
* OpenCV Java bindings are ported from Android to desktop Java!
Actually any JVM language will work, see Tutorial for details,
and Java or Scala code samples.
* Android application framework, samples, tutorials, and OpenCV
Manager are improved.
* Optimizations for the new NVIDIA Kepler architecture, CARMA
platform support and other new optimizations in CUDA.
* OpenCL module now builds successfully with various SDKs (from
AMD, NVIDIA, Intel and Apple) and runs well on different GPUs
(AMD, NVidia, Intel HD4000). A lot of new functionality has been
added, tons of bugs fixed, performance of many functions has
been significantly improved.
* 100+ reported problems have been resolved since 2.4.3, thanks
everybody who participated!
- Drop the buildrequire for libxine
- Update to OpenCV 2.4.3
More info at:
http://opencv.org/opencv-2-4-3-released.html
The nicely formatted changelog can be seen here:
http://code.opencv.org/projects/opencv/wiki/ChangeLog;
here are the highlights:
* A lot of good stuff from the Google Summer of Code 2012 has been
integrated; this was a very productive summer!
* Significantly improved and optimized Android and iOS ports.
* Greatly extended GPU (i.e. CUDA-based) module.
* The brand new ocl (OpenCL-based) module that unleashes GPU power
also for AMD and Intel GPU users. It’s not included into the
binary package, since there are different SDKs, and it’s not
turned on by default. You need to run CMake and turn on
“WITH_OPENCL”. Also, please note that this is very first version
of the module, so it may be not very stable and not very
functional.
* Much better performance on many-core systems out of the box. You
do not need TBB anymore on MacOSX, iOS and Windows. BTW, the
binary package for Windows is now built without TBB support.
Libraries and DLLs for Visual Studio 2010 use the Concurrency
framework.
* About 130 bugs have been fixed since 2.4.2.
* Since 2.4.3rc we fixed several more problems, in particular some
compile problems with iOS 6 SDK.
- buildrequire glu
- Update to OpenCV 2.4.2
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Drop opencv-datadir.patch to comply with upstream directory layout
- Update to OpenCV 2.4.1
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Update to OpenCV 2.4.0
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Add opencv-gcc47.patch: Fix build with gcc 4.7.
- Use Explicit Buildrequires on several needed libraries
future dependency cleanups may/will cause build to fail otherwise.
- Add upstream r6881 to fix clang compatibility
- uncomment libraries not in 12.1 for now
- Changed groups (fix for RPMLINT warning)
- Added check for duplicate files (fix for RPMLINT warning)
- Added py_requires macros and python-base dependencies (fix for RPMLINT warning)
- Escaped macros (fix for RPMLINT warning)
- Fixed end-of-line encoding problems (fix for RPMLINT warning)
- Added libeigen2-devel buildrequires
- Added libunicap and libucil buildrequires (libunicap supports requires libucil)
- Cleaned up spec file formatting
- Dropped opencv-2.3-ffmpeg.patch, applied upstream
- Revive opencv-2.3-ffmpeg.patch, needs rebase
- Tag all patches according to openSUSE packaging guidelines
- Removed opencv-2.3-cmake.patch, old cmake cannot be used any more.
- Python bindings cannot be built without NumPy any more.
- Update to OpenCV 2.3.1
- Update and readd opencv-2.3-underlinking.patch since it is still
necessary.
- Fix support for new ffmpeg versions
- Removed unnecessary patches
- Enable Python NumPy support on openSUSE 11.2
- Build Qt instead of Gtk GUI
- Fix cmake files for openSUSE 11.1
- No GStreamer support on openSUSE 11.1
- Update to OpenCV 2.3.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Fix build on openSUSE 11.2
- Add opencv-v4l-2.6.38.patch: use the new libv4l2 interface
- Enable Python NumPy support
- SWIG is not required any more
- Enable OpenEXR support
- Update to OpenCV 2.2.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Use system zlib, oh, and do not export ZLIB symbols to
other applications, clashes ensued.
- fix build with gcc 4.6
- add -underlinking patch
- devel package renamed to opencv-devel, so that switching between
OBS and packman opencv packages is easier
- fix gstreamer support
- fix xine support
- fix some rpmlint warnings
- fix shared libraries permissions
- Do not waste resources building the tests as we do not run them
- Do not disable SSE,SSE2,etc. According to OpenCV changelog,
it should be safe to leave these enabled.
- fix build on openSUSE 11.0
- Update to OpenCV 2.1.0:
* The whole OpenCV is now using exceptions instead of the old
libc-style mechanism
* Experimental "static" OpenCV configuration in CMake was
contributed by Jose Luis Blanco.
Pass "BUILD_SHARED_LIBS=OFF" to CMake to build OpenCV statically.
* new improved version of one-way descriptor is added
* User can now control the image areas visible after the stereo
rectification
* Fullscreen has been added (thanks to Yannick Verdie).
* Further info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- fix build with libpng14
- small spec file cleanup
- Moved to the KDE repositories to enable inclusion in kipi-plugins
- Initial package
OBS-URL: https://build.opensuse.org/request/show/714221
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/opencv?expand=0&rev=73
2019-07-17 13:13:58 +02:00
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Accepting request 983700 from home:StefanBruens:branches:science
- update to 4.6.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version460
* OpenCV project infrastructure migrating on GitHub Actions
workflows for CI and release purposes
* Added support for GCC 12, Clang 15
* Added support for FFmpeg 5.0
* DNN module patches:
+ Improved layers / activations / supported more models:
- LSTM (+CUDA), resize (+ONNX13), Sign, Shrink, Reciprocal,
depth2space, space2depth
- fixes in Reduce, Slice, Expand
+ Disabled floating-point denormals processing #21521
+ Changed layer names in ONNX importer to support "output"
entities properly
+ Added TIM-VX NPU backend support:
https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU
+ Added Softmax parameter to ClassificationModel
+ Added audio speech recognition sample (C++) #21458
+ Intel® Inference Engine backend (OpenVINO):
- added initial support for OpenVINO 2022.1 release
- removed support of legacy API (dropped since 2020.3)
* G-API module:
+ G-API framework:
- Introduced a Grayscale image format support for
cv::MediaFrame: #21511;
- Enabeled .reshape() support in the CPU backend: #21669;
- Fixed possible hang in streaming execution mode with constant
inputs: #21567;
- Introduced proper error/exception propagation in the
asynchronous streaming execution mode: #21660;
- Fixed new stream event handling: #21731.
+ Fluid backend:
- Fixed horizontal pass in the Resize kernel, fixed Valgrind
issues: #21144;
- Extended Resize kernel with F32 version: #21678,
added AVX: #21728.
- Enabled dynamic dispatch for Split4 kernel: #21520;
- Enabled dynamic dispatch for Merge3 kernel: #21529;
- Added a SIMD version for DivC kernel: #21474;
- Added a SIMD version for DivRC kernel: #21530;
- Enabled dynamic dispatch for Add kernel: #21686;
- Enabled dynamic dispatch for Sub kernel: #21746;
- Added a SIMD version for ConvertTo kernel: #21777;
- Fixed kernel matrix size for Sobel kernel: #21613.
+ Intel® OpenVINO™ inference backend:
- Fixed NV12 format support for remote memory when OpenVINO
remote context is used: #21424.
- Implemented correct error handling in the backend: #21579.
- Fixed ngraph warnings #21362.
+ OpenCV AI Kit backend:
- Introduced a new backend to program OpenCV AI Kit boards via
G-API. Currently the backend is in experimental state, but allows
to build Camera+NN pipeline and supports heterogeneity (mixing
with host-side code): #20785, #21504.
+ Media integration:
- Enabled GPU inference with oneVPL and DirectX11 on Windows in
Intel OpenVINO inference backend: #21232, #21618, #21658, #21687,
#21688. Now GPU textures decoded by oneVPL decoder can be
preprocessed and inferred on GPU with no extra host processing.
- Enabled oneVPL support on Linux: #21883.
- Extended GStreamer pipeline source with Grayscale image format
support: #21560.
+ Python bindings:
- Exposed GStreamer pipeline source in Python bindings: #20832.
- Fixed Python bindings for CudaBufferPool, cudacodec and cudastereo
modules in OpenCV Contrib.
+ Samples:
- Introduced a pipeline modelling tool for cascaded model
benchmarking: #21477, #21636, #21719. The tool supports a
declarative YAML-based config to describe pipelines with simulated
pre-/post-processing. The tool collects and reports latency and
throughput information for the modelled pipeline.
+ Other changes and fixes:
- Moved GKernelPackage into cv:: namespace by default, its cv::gapi::
alias remain for compatibility: #21318;
- Moved Resize kernel from core to imgproc kernel packages for
CPU, OpenCL, and Fluid backends: #21157. Also moved tests
appropriately: #21475;
- Avoided sporadic test failures in DivC: #21626;
- Fixed 1D Mat handling in the framework: #21782;
- Reduced the number of G-API generated accuracy tests: #21909.
- Drop upstream patches:
* 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
* videoio_initial_FFmpeg_5_0_support.patch
* videoio_ffmpeg_avoid_memory_leaks.patch
OBS-URL: https://build.opensuse.org/request/show/983700
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=33
2022-06-27 18:05:05 +02:00
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BuildArch: noarch
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2010-03-08 18:16:50 +01:00
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2013-08-01 15:56:40 +02:00
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%description doc
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2010-03-08 18:16:50 +01:00
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This package contains the documentation and examples for the OpenCV library.
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%prep
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2016-03-05 11:21:23 +01:00
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%setup -q -a 1
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2021-12-26 02:29:53 +01:00
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%autopatch -p1
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2011-07-07 14:28:27 +02:00
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2018-06-02 11:53:10 +02:00
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# Only copy over modules we need
|
2021-02-22 20:10:19 +01:00
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mv opencv_contrib-%{version}/modules/{aruco,face,tracking,optflow,plot,shape,superres,videostab,ximgproc} modules/
|
Accepting request 983700 from home:StefanBruens:branches:science
- update to 4.6.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version460
* OpenCV project infrastructure migrating on GitHub Actions
workflows for CI and release purposes
* Added support for GCC 12, Clang 15
* Added support for FFmpeg 5.0
* DNN module patches:
+ Improved layers / activations / supported more models:
- LSTM (+CUDA), resize (+ONNX13), Sign, Shrink, Reciprocal,
depth2space, space2depth
- fixes in Reduce, Slice, Expand
+ Disabled floating-point denormals processing #21521
+ Changed layer names in ONNX importer to support "output"
entities properly
+ Added TIM-VX NPU backend support:
https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU
+ Added Softmax parameter to ClassificationModel
+ Added audio speech recognition sample (C++) #21458
+ Intel® Inference Engine backend (OpenVINO):
- added initial support for OpenVINO 2022.1 release
- removed support of legacy API (dropped since 2020.3)
* G-API module:
+ G-API framework:
- Introduced a Grayscale image format support for
cv::MediaFrame: #21511;
- Enabeled .reshape() support in the CPU backend: #21669;
- Fixed possible hang in streaming execution mode with constant
inputs: #21567;
- Introduced proper error/exception propagation in the
asynchronous streaming execution mode: #21660;
- Fixed new stream event handling: #21731.
+ Fluid backend:
- Fixed horizontal pass in the Resize kernel, fixed Valgrind
issues: #21144;
- Extended Resize kernel with F32 version: #21678,
added AVX: #21728.
- Enabled dynamic dispatch for Split4 kernel: #21520;
- Enabled dynamic dispatch for Merge3 kernel: #21529;
- Added a SIMD version for DivC kernel: #21474;
- Added a SIMD version for DivRC kernel: #21530;
- Enabled dynamic dispatch for Add kernel: #21686;
- Enabled dynamic dispatch for Sub kernel: #21746;
- Added a SIMD version for ConvertTo kernel: #21777;
- Fixed kernel matrix size for Sobel kernel: #21613.
+ Intel® OpenVINO™ inference backend:
- Fixed NV12 format support for remote memory when OpenVINO
remote context is used: #21424.
- Implemented correct error handling in the backend: #21579.
- Fixed ngraph warnings #21362.
+ OpenCV AI Kit backend:
- Introduced a new backend to program OpenCV AI Kit boards via
G-API. Currently the backend is in experimental state, but allows
to build Camera+NN pipeline and supports heterogeneity (mixing
with host-side code): #20785, #21504.
+ Media integration:
- Enabled GPU inference with oneVPL and DirectX11 on Windows in
Intel OpenVINO inference backend: #21232, #21618, #21658, #21687,
#21688. Now GPU textures decoded by oneVPL decoder can be
preprocessed and inferred on GPU with no extra host processing.
- Enabled oneVPL support on Linux: #21883.
- Extended GStreamer pipeline source with Grayscale image format
support: #21560.
+ Python bindings:
- Exposed GStreamer pipeline source in Python bindings: #20832.
- Fixed Python bindings for CudaBufferPool, cudacodec and cudastereo
modules in OpenCV Contrib.
+ Samples:
- Introduced a pipeline modelling tool for cascaded model
benchmarking: #21477, #21636, #21719. The tool supports a
declarative YAML-based config to describe pipelines with simulated
pre-/post-processing. The tool collects and reports latency and
throughput information for the modelled pipeline.
+ Other changes and fixes:
- Moved GKernelPackage into cv:: namespace by default, its cv::gapi::
alias remain for compatibility: #21318;
- Moved Resize kernel from core to imgproc kernel packages for
CPU, OpenCL, and Fluid backends: #21157. Also moved tests
appropriately: #21475;
- Avoided sporadic test failures in DivC: #21626;
- Fixed 1D Mat handling in the framework: #21782;
- Reduced the number of G-API generated accuracy tests: #21909.
- Drop upstream patches:
* 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
* videoio_initial_FFmpeg_5_0_support.patch
* videoio_ffmpeg_avoid_memory_leaks.patch
OBS-URL: https://build.opensuse.org/request/show/983700
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=33
2022-06-27 18:05:05 +02:00
|
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rm -Rf opencv_contrib-%{version}/modules/*
|
2018-06-02 11:53:10 +02:00
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cp opencv_contrib-%{version}/LICENSE LICENSE.contrib
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2013-08-01 15:56:40 +02:00
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# Remove Windows specific files
|
2011-07-07 14:28:27 +02:00
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rm -f doc/packaging.txt
|
2010-03-08 18:16:50 +01:00
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%build
|
2022-04-09 19:55:23 +02:00
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%limit_build -m 1800
|
2022-03-31 23:51:33 +02:00
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|
Accepting request 860308 from home:StefanBruens:branches:science
- update to 4.5.1, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version451
* Continued merging of GSoC 2020 results:
+ Develop OpenCV.js DNN modules for promising web use cases
together with their tutorials
+ OpenCV.js: WASM SIMD optimization 2.0
+ High Level API and Samples for Scene Text Detection and
Recognition
+ SIFT: SIMD optimization of GaussianBlur 16U
* DNN module:
+ Improved layers / activations / supported more models:
- optimized: 1D convolution, 1D pool
- fixed: Resize, ReduceMean, Gather with multiple outputs,
importing of Faster RCNN ONNX model
- added support: INT32 ONNX tensors
+ Intel® Inference Engine backend (OpenVINO):
- added support for OpenVINO 2021.2 release
- added preview support for HDDL
+ Fixes and optimizations in DNN CUDA backend (thanks to
@YashasSamaga)
* G-API Framework:
+ Introduced serialization for cv::RMat, including
serialization for user-defined memory adapters
+ Introduced desync, a new Operation for in-graph asynchronous
execution - to allow different parts of the graph run with
a different latency
+ Introduced a notion of "in-graph metadata", now various
media-related information can be accessed in graph directly
(currently only limited to timestamps and frame IDs)
+ Introduced a new generic task-based executor, based on
Threading Building Blocks (TBB)
+ Extended infer<>() API to accept a new cv::GFrame data
structure to allow handling of various media formats without
changes in the graph structure
+ Made copy() an intrinsic where real copy may not happen
(optimized out) based on graph structure, extended it to
support cv::GFrame
+ Various fixes, including addressig static analysis,
documentation, and test issues
* G-API Operations:
+ Introduced new operations morphologyEx, boundingRect,
fitLine, kmeans, Background Subtractor, Kalman filter
* G-API Intel® Inference Engine backend (OpenVINO):
+ Extended cv::gapi::ie::Params<> to import CNN networks (e.g.
pre-compiled ones) instead of passing .XML and .BIN files;
also enabled configuring Inference Engine plugins via
this structure
+ Added a new overload to infer<>() to run inference over a
single region of interest
+ Added support for cv::MediaFrame input data type (projected
from cv::GFrame) and handling for NV12 input image format
* G-API Python bindings:
+ Exposed G-API's Inference and Streaming APIs in the OpenCV
Python bindings
+ Added initial Python support for cv::GArray data structure
* Significant progress on RISC-V port.
- Updated constraints, bump memory to 5 GB
- Cleaned up spec file
OBS-URL: https://build.opensuse.org/request/show/860308
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=23
2021-01-04 20:56:22 +01:00
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# openCV does not understand the standard RelWithDebinfo,
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# but has a separate variable for it
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2017-12-03 10:10:30 +01:00
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# Dynamic dispatch: https://github.com/opencv/opencv/wiki/CPU-optimizations-build-options
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# x86: disable SSE on 32bit, do not dispatch AVX and later - SSE3
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# is the highest extension available on any non-64bit x86 CPU
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# ARM: ARMv6, e.g. RPi1, only has VFPv2
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2024-02-05 08:31:49 +01:00
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pushd $PWD
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2017-07-11 08:24:11 +02:00
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%cmake \
|
Accepting request 860308 from home:StefanBruens:branches:science
- update to 4.5.1, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version451
* Continued merging of GSoC 2020 results:
+ Develop OpenCV.js DNN modules for promising web use cases
together with their tutorials
+ OpenCV.js: WASM SIMD optimization 2.0
+ High Level API and Samples for Scene Text Detection and
Recognition
+ SIFT: SIMD optimization of GaussianBlur 16U
* DNN module:
+ Improved layers / activations / supported more models:
- optimized: 1D convolution, 1D pool
- fixed: Resize, ReduceMean, Gather with multiple outputs,
importing of Faster RCNN ONNX model
- added support: INT32 ONNX tensors
+ Intel® Inference Engine backend (OpenVINO):
- added support for OpenVINO 2021.2 release
- added preview support for HDDL
+ Fixes and optimizations in DNN CUDA backend (thanks to
@YashasSamaga)
* G-API Framework:
+ Introduced serialization for cv::RMat, including
serialization for user-defined memory adapters
+ Introduced desync, a new Operation for in-graph asynchronous
execution - to allow different parts of the graph run with
a different latency
+ Introduced a notion of "in-graph metadata", now various
media-related information can be accessed in graph directly
(currently only limited to timestamps and frame IDs)
+ Introduced a new generic task-based executor, based on
Threading Building Blocks (TBB)
+ Extended infer<>() API to accept a new cv::GFrame data
structure to allow handling of various media formats without
changes in the graph structure
+ Made copy() an intrinsic where real copy may not happen
(optimized out) based on graph structure, extended it to
support cv::GFrame
+ Various fixes, including addressig static analysis,
documentation, and test issues
* G-API Operations:
+ Introduced new operations morphologyEx, boundingRect,
fitLine, kmeans, Background Subtractor, Kalman filter
* G-API Intel® Inference Engine backend (OpenVINO):
+ Extended cv::gapi::ie::Params<> to import CNN networks (e.g.
pre-compiled ones) instead of passing .XML and .BIN files;
also enabled configuring Inference Engine plugins via
this structure
+ Added a new overload to infer<>() to run inference over a
single region of interest
+ Added support for cv::MediaFrame input data type (projected
from cv::GFrame) and handling for NV12 input image format
* G-API Python bindings:
+ Exposed G-API's Inference and Streaming APIs in the OpenCV
Python bindings
+ Added initial Python support for cv::GArray data structure
* Significant progress on RISC-V port.
- Updated constraints, bump memory to 5 GB
- Cleaned up spec file
OBS-URL: https://build.opensuse.org/request/show/860308
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=23
2021-01-04 20:56:22 +01:00
|
|
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-DCMAKE_BUILD_TYPE=Release \
|
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|
-DBUILD_WITH_DEBUG_INFO=ON \
|
2017-07-11 08:24:11 +02:00
|
|
|
%if %{with tests}
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-DBUILD_TESTS=ON \
|
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%endif
|
Accepting request 714221 from science
- Update to version 4.1.0
* DNN module:
+ Reduced peak memory consumption for some models up to 30%.
+ Inference Engine
- Inference Engine 2018R3 is now a minimal supported version of IE.
- Myriad X (Intel® Neural Compute Stick 2) is now supported and tested.
- Automatic IR network reshaping for different inputs.
- Improved samples to work with models from OpenVINO Open Model Zoo
+ New networks from TensorFlow Object Detection API: Faster-RCNNs, SSDs
and Mask-RCNN with dilated convolutions, FPN SSD
* Performance improvements:
+ More optimization using AVX2 instruction set.
+ Automatic runtime dispatching is available for large set of functions
from core and imgproc modules.
* Other improvements:
+ Matplotlib Perceptually Uniform Sequential colormaps
+ Add keypoints matching visualization for real-time pose estimation tutorial
+ Add Hand-Eye calibration methods
+ Java: improved support for multidimensional arrays (Mat)
+ Dynamically loaded videoio backends (FFmpeg, GStreamer)
+ opencv_contrib: Robust local optical flow (RLOF) implementations
+ opencv_contrib: Implementation of Quasi Dense Stereo algorithm
+ opencv_contrib: New module: Image Quality Analysis (IQA) API
+ opencv_contrib: BRISQUE No Reference Image Quality Assessment (IQA) API
Check https://github.com/opencv/opencv/wiki/ChangeLog#version410
- Update to version 4.0.0
* A lot of C API from OpenCV 1.x has been removed. The affected modules are
objdetect, photo, video, videoio, imgcodecs, calib3d.
* Persistence (storing and loading structured data to/from XML, YAML or JSON)
in the core module has been completely reimplemented.
* OpenCV is now C++11 library and requires C++11-compliant compiler.
Thanks to the extended C++11 standard library, we could get rid of hand-crafted
cv::String and cv::Ptr. Now cv::String == std::string and cv::Ptr is a thin
wrapper on top of std::shared_ptr. Also, on Linux/BSD for cv::parallel_for_
we now use std::thread's instead of pthreads.
* DNN improvements
* Completely new module opencv_gapi has been added. It is the engine for very
efficient image processing, based on lazy evaluation and on-fly construction.
* Performance improvements
A few hundreds of basic kernels in OpenCV have been rewritten using so-called
"wide universal intrinsics". Those intrinsics map to SSE2, SSE4, AVX2, NEON or
VSX intrinsics, depending on the target platform and the compile flags.
* QR code detector and decoder have been added to opencv/objdetect module.
* The popular Kinect Fusion algorithm has been implemented, optimized for CPU and
GPU (OpenCL), and integrated into opencv_contrib/rgbd module.
* Very efficient and yet high-quality DIS dense optical flow algorithm has been
moved from opencv_contrib to opencv, video module. See the example.
* The slower TV L1 optical flow algorithm has been moved to opencv_contrib.
Check https://github.com/opencv/opencv/wiki/ChangeLog#version400
- Drop obsolete opencv-lib_suffix.patch
- Add 0001-Handle-absolute-OPENCV_INCLUDE_INSTALL_PATH-correctl.patch
- As this is a major version upgrade, the old 3.4.x package is still
available as opencv3
- Update to 3.4.3
* Compatibility fixes with python 3.7
* Added a new computational target DNN_TARGET_OPENCL_FP16
* Extended support of Intel's Inference Engine backend
* Enabled import of Intel's OpenVINO pre-trained networks from
intermediate representation (IR).
* tutorials improvements
Check https://github.com/opencv/opencv/wiki/ChangeLog#version343
for the complete changelog.
- Drop fix-build-i386-nosse.patch, build-workaround-issues-with-c.patch
(fixed upstream)
- Refresh patches
- Add patch to fix use of headers from C:
* build-workaround-issues-with-c.patch
- Update to 3.4.1:
* Added support for quantized TensorFlow networks
* OpenCV is now able to use Intel DL inference engine as DNN
acceleration backend
* Added AVX-512 acceleration to the performance-critical kernels
* For more information, read
https://github.com/opencv/opencv/wiki/ChangeLog#version341
- Update contrib modules to 3.4.1:
* No changelog available
- Change mechanism the contrib modules are built
- Include LICENSE of contrib tarball as well
- Build with python3 on >= 15
- Add patch to fix build on i386 without SSE:
* fix-build-i386-nosse.patch
- Refresh patches:
* fix_processor_detection_for_32bit_on_64bit.patch
* opencv-build-compare.patch
- Mention all libs explicitly
- Rebase 3.4.0 update from i@marguerite.su
- update to 3.4.0
* Added faster R-CNN support
* Javascript bindings have been extended to
cover DNN module
* DNN has been further accelerated for iGPU
using OpenCL
* On-disk caching of precompiled OpenCL
kernels has been finally implemented
* possible to load and run pre-compiled
OpenCL kernels via T-API
* Bit-exact 8-bit and 16-bit resize has been
implemented (currently supported only
bilinear interpolation)
- update face module to 3.4.0
- add opencv-lib_suffix.patch, remove LIB_SUFFIX
from OPENCV_LIB_INSTALL_PATH, as CMAKE_INSTALL
_LIBDIR is arch dependent.
- Add option to build without openblas
- Add conditionals for python2 and python3 to allow us enabling
only desired python variants when needed
- Do not depend on sphinx as py2 and py3 seem to collide there
- Readd opencv-gles.patch, it is *not* included upstream; otherwise
build breaks on all GLES Qt5 platforms (armv6l, armv7l, aarch64)
- add fix_processor_detection_for_32bit_on_64bit.patch
- Correctly set optimizations and dynamic dispatch on ARM, use
OpenCV 3.3 syntax on x86.
- Update licensing information
- change requires of python-numpy-devel to build in Leap and
to not break factory in future
- fix build error/unresolvable for Leap 42.2 and 42.3
- Update to version 3.3.1:
* Lots of various bugfixes
- Update source url
- Rename python subpackage to python2
- Do not explicitly require python-base for python subpackages
- Update to 3.3
- Dropped obsolete patches
* opencv-gcc6-fix-pch-support-PR8345.patch
* opencv-gles.patch
- Updated opencv-build-compare.patch
- Add 0001-Do-not-include-glx.h-when-using-GLES.patch
Fix build for 32bit ARM, including both GLES and desktop GL headers
causes incompatible pointer type errors
- Add conditional for the qt5/qt4 integration
* This is used only for gui tools, library is not affected
- Add provides/obsoletes for the qt5 packages to allow migration
- Drop patch opencv-qt5-sobump.diff
* Used only by the obsoleted qt5 variant
- Cleanup a bit with spec-cleaner
- Use %cmake macros
- Remove the conditions that are not really needed
- Add tests conditional disabled by default
* Many tests fail and there are missing testdata
- Switch to pkgconfig style dependencies
- Update to OpenCV 3.2.0
- Results from 11 GSoC 2016 projects have been submitted to the library:
+ sinusoidal patterns for structured light and phase unwrapping module
[Ambroise Moreau (Delia Passalacqua)]
+ DIS optical flow (excellent dense optical flow algorithm that is both
significantly better and significantly faster than Farneback’s algorithm –
our baseline), and learning-based color constancy algorithms implementation
[Alexander Bokov (Maksim Shabunin)]
+ CNN based tracking algorithm (GOTURN) [Tyan Vladimir (Antonella Cascitelli)]
+ PCAFlow and Global Patch Collider algorithms implementation
[Vladislav Samsonov (Ethan Rublee)]
+ Multi-language OpenCV Tutorials in Python, C++ and Java
[João Cartucho (Vincent Rabaud)]
+ New camera model and parallel processing for stitching pipeline
[Jiri Horner (Bo Li)]
+ Optimizations and improvements of dnn module
[Vitaliy Lyudvichenko (Anatoly Baksheev)]
+ Base64 and JSON support for file storage. Use names like
“myfilestorage.xml?base64” when writing file storage to store big chunks of
numerical data in base64-encoded form. [Iric Wu (Vadim Pisarevsky)]
+ tiny_dnn improvements and integration
[Edgar Riba (Manuele Tamburrano, Stefano Fabri)]
+ Quantization and semantic saliency detection with tiny_dnn
[Yida Wang (Manuele Tamburrano, Stefano Fabri)]
+ Word-spotting CNN based algorithm
[Anguelos Nicolaou (Lluis Gomez)]
- Contributions besides GSoC:
+ Greatly improved and accelerated dnn module in opencv_contrib:
- Many new layers, including deconvolution, LSTM etc.
- Support for semantic segmentation and SSD networks with samples.
- TensorFlow importer + sample that runs Inception net by Google.
+ More image formats and camera backends supported
+ Interactive camera calibration app
+ Multiple algorithms implemented in opencv_contrib
+ Supported latest OSes, including Ubuntu 16.04 LTS and OSX 10.12
+ Lot’s of optimizations for IA and ARM archs using parallelism, vector
instructions and new OpenCL kernels.
+ OpenCV now can use vendor-provided OpenVX and LAPACK/BLAS (including Intel MKL,
Apple’s Accelerate, OpenBLAS and Atlas) for acceleration
- Refreshed opencv-build-compare.patch
- Dropped upstream opencv-gcc5.patch
- Replace opencv-gcc6-disable-pch.patch with upstream patch
opencv-gcc6-fix-pch-support-PR8345.patch
- Enable TBB support (C++ threading library)
- Add dependency on openBLAS
- Enable ffmpeg support unconditional
- In case we build using GCC6 (or newer), add -mlra to CFLAGS to
workaround gcc bug
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=71294.
- Apply upstream patch opencv-gcc6-disable-pch.patch to disable
PCH for GCC6.
- Test for python versions greater than or equal to the current
version.
- Add python 3 support
- Added opencv_contrib_face-3.1.0.tar.bz2
* This tarball is created to take only the face module from the
contrib package. The Face module is required by libkface, which
in its turn is required by digikam.
- Added _constraints file to avoid random failures on small workers
(at least for builds on PMBS)
- Update to OpenCV 3.1.0
- A lot of new functionality has been introduced during Google
Summer of Code 2015:
+ “Omnidirectional Cameras Calibration and Stereo 3D
Reconstruction” – opencv_contrib/ccalib module
(Baisheng Lai, Bo Li)
+ “Structure From Motion” – opencv_contrib/sfm module
(Edgar Riba, Vincent Rabaud)
+ “Improved Deformable Part-based Models” – opencv_contrib/dpm
module (Jiaolong Xu, Bence Magyar)
+ “Real-time Multi-object Tracking using Kernelized Correlation
Filter” – opencv_contrib/tracking module
(Laksono Kurnianggoro, Fernando J. Iglesias Garcia)
+ “Improved and expanded Scene Text Detection” –
opencv_contrib/text module (Lluis Gomez, Vadim Pisarevsky)
+ “Stereo correspondence improvements” – opencv_contrib/stereo
module (Mircea Paul Muresan, Sergei Nosov)
+ “Structured-Light System Calibration” –
opencv_contrib/structured_light (Roberta Ravanelli,
Delia Passalacqua, Stefano Fabri, Claudia Rapuano)
+ “Chessboard+ArUco for camera calibration” –
opencv_contrib/aruco (Sergio Garrido, Prasanna, Gary Bradski)
+ “Implementation of universal interface for deep neural
network frameworks” – opencv_contrib/dnn module
(Vitaliy Lyudvichenko, Anatoly Baksheev)
+ “Recent advances in edge-aware filtering, improved SGBM
stereo algorithm” – opencv/calib3d and opencv_contrib/ximgproc
(Alexander Bokov, Maksim Shabunin)
+ “Improved ICF detector, waldboost implementation” –
opencv_contrib/xobjdetect (Vlad Shakhuro, Alexander Bovyrin)
+ “Multi-target TLD tracking” – opencv_contrib/tracking module
(Vladimir Tyan, Antonella Cascitelli)
+ “3D pose estimation using CNNs” – opencv_contrib/cnn_3dobj
(Yida Wang, Manuele Tamburrano, Stefano Fabri)
- Many great contributions made by the community, such as:
+ Support for HDF5 format
+ New/Improved optical flow algorithms
+ Multiple new image processing algorithms for filtering,
segmentation and feature detection
+ Superpixel segmentation and much more
- IPPICV is now based on IPP 9.0.1, which should make OpenCV
even faster on modern Intel chips
- opencv_contrib modules can now be included into the
opencv2.framework for iOS
- Newest operating systems are supported: Windows 10 and
OSX 10.11 (Visual Studio 2015 and XCode 7.1.1)
- Interoperability between T-API and OpenCL, OpenGL, DirectX and
Video Acceleration API on Linux, as well as Android 5 camera.
- HAL (Hardware Acceleration Layer) module functionality has been
moved into corresponding basic modules; the HAL replacement
mechanism has been implemented along with the examples
- Removed improve-sphinx-search.diff, opencv-altivec-vector.patch,
opencv-pkgconfig.patch and opencv-samples.patch, fixed upstream.
- Fixed opencv-qt5-sobump.diff, opencv-build-compare.patch,
opencv-gcc5.patch and opencv-gles.patch.
- Version OpenCV 3.0.0
+ ~1500 patches, submitted as PR @ github. All our patches go
the same route.
+ opencv_contrib (http://github.com/itseez/opencv_contrib)
repository has been added. A lot of new functionality is there
already! opencv_contrib is only compatible with 3.0/master,
not 2.4. Clone the repository and use “cmake …
-D OPENCV_EXTRA_MODULES_PATH=<path_to opencv_contrib/modules> …”
to build opencv and opencv_contrib together.
+ a subset of Intel IPP (IPPCV) is given to us and our users free
of charge, free of licensing fees, for commercial and
non-commerical use. It’s used by default in x86 and x64 builds
on Windows, Linux and Mac.
+ T-API (transparent API) has been introduced, this is transparent
GPU acceleration layer using OpenCL. It does not add any
compile-time or runtime dependency of OpenCL. When OpenCL is
available, it’s detected and used, but it can be disabled at
compile time or at runtime. It covers ~100 OpenCV functions.
This work has been done by contract and with generous support
from AMD and Intel companies.
+ ~40 OpenCV functions have been accelerated using NEON intrinsics
and because these are mostly basic functions, some higher-level
functions got accelerated as well.
+ There is also new OpenCV HAL layer that will simplifies creation
of NEON-optimized code and that should form a base for the
open-source and proprietary OpenCV accelerators.
+ The documentation is now in Doxygen: http://docs.opencv.org/master/
+ We cleaned up API of many high-level algorithms from features2d,
calib3d, objdetect etc. They now follow the uniform
“abstract interface – hidden implementation” pattern and make
extensive use of smart pointers (Ptr<>).
+ Greatly improved and extended Python & Java bindings (also,
see below on the Python bindings), newly introduced Matlab
bindings (still in alpha stage).
+ Improved Android support – now OpenCV Manager is in Java and
supports both 2.4 and 3.0.
+ Greatly improved WinRT support, including video capturing and
multi-threading capabilities. Thanks for Microsoft team for this!
+ Big thanks to Google who funded several successive GSoC programs
and let OpenCV in. The results of many successful GSoC 2013 and
2014 projects have been integrated in opencv 3.0 and
opencv_contrib (earlier results are also available in
OpenCV 2.4.x). We can name:
- text detection
- many computational photography algorithms (HDR, inpainting,
edge-aware filters, superpixels, …)
- tracking and optical flow algorithms
- new features, including line descriptors, KAZE/AKAZE
- general use optimization (hill climbing, linear programming)
- greatly improved Python support, including Python 3.0 support,
many new tutorials & samples on how to use OpenCV with Python.
- 2d shape matching module and 3d surface matching module
- RGB-D module
- VTK-based 3D visualization module
- etc.
+ Besides Google, we enjoyed (and hope that you will enjoy too)
many useful contributions from community, like:
- biologically inspired vision module
- DAISY features, LATCH descriptor, improved BRIEF
- image registration module
- etc.
- Reduce build-compare noise
opencv-build-compare.patch
- Remove BuildRequirement for python-sphinx in SLE12, since it's
not available there and it's not a mandatory requirement.
- Reduce differences between two spec files
- Use pkgconfig for ffmpeg BuildRequires
- Update improve-sphinx-search.diff for new python-Sphinx(1.3.1)
* now that sphinx-build disallow executing without arguments and
give you "Insufficient arguments" error, use "sphinx-build -h"
instead
* the default usages output ie. sphinx-build(or --help) no longer
are standard error but standard output, drop OUTPUT_QUIET and
add OUTPUT_VARIABLE throws the output to SPHINX_OUTPUT as well
- support gcc 5 (i.e. gcc versions without minor version):
opencv-gcc5.patch
- Update to OpenCV 2.4.11 - can't find NEWS or Changelog
merely collecting bug fixes while 3.0 is in the making, 2.4.11
didn't even make it on their web page, it's only on download
server
- remove opencv-underlinking.patch as obsolete
- remove upstream patch bomb_commit_gstreamer-1x-support.patch
- commenting out opencv-pkgconfig.patch - possibly it requires a rebase,
but the problem it tries to solve is unclear
- Add specific buildrequires for libpng15, so that we are
building against the system provided libpng.
- Update to OpenCV 2.4.9
More info at:
http://opencv.org/opencv-2-4-9-is-out.html
The brief list of changes:
* new 3D visualization module ‘viz’;
* performance fixes in ‘ocl’ module;
* fixes in Android Camera;
* improved CUDA support for mobile platforms;
* bugfixes from community;
* 55 reported bugs have been closed;
* 156 pull requests have been merged.
- Drop the BuildRequires on libucil and libunicap for Factory. This
stops us from getting ride of Gstreamer 0.10 and besides these two
libraries seem to be unmaintained upstream as that the latest
actions are from 2010
- Add upstream patch (3.0 version) to support Gstreamer 1.x
* bomb_commit_gstreamer-1x-support.patch
- Upstream now provides tarballs with source only as git tags
from github so update Source0 path.
- Add requires on various X extensions linked to opencv_ts module.
As those are present in the .pc file we need it anyway.
- Update to OpenCV 2.4.8
More info at:
http://opencv.org/opencv-2-4-8.html
The brief list of changes:
* NVidia CUDA support on Android devices with CUDA capable SoC and
CUDA sample;
* Concurrent kernel execution and user defined context support for
OpenCL;
* Integration with Intel Perceptual SDK and new depth sensors support
for Windows;
* 32 reported bugs have been closed;
* 139 pull requests have been merged;
- Fix build with altivec:
opencv-altivec-vector.patch
- Added opencv-pkgconfig.patch: make sure to provide link flags in
OpenCV pc file (bnc#853036)
- Update to OpenCV 2.4.7
More info at:
http://opencv.org/opencv-2-4-7-is-out.html
The brief list of changes:
* dynamic OpenCL runtime loading, setting default OpenCL device
via env var, many bug-fixes and some new optimization with OpenCL
* bug-fixes and new optimizations in CUDA stuff
* latest NDK and Android OS support, Native Android Camera tuning
* minor fixes, XAML sample and MS Certification compatibility
in WinRT stuff
* 382 pull requests have been merged
* 54 reported bugs have been fixed
- Added pkgconfig(glu) Requires to devel package, as per .pc file
- Make devel package provides also devel-static one
- Drop assume-Sphinx-is-there.diff, and add improve-sphinx-search.diff,
for properly finding sphinx with alphabetic chars in version
- Add patch assume-Sphinx-is-there.diff to fix building with
Sphinx versions that have alphanumeric characters in the version
(Only for factory builds at the moment)
- Use eigen3 instead of eigen2 as build requirement for openSUSE > 12.3.
- Enable compilation with libucil and libunicap.
- Removed dos2unix build requirement (not needed anymore).
- Update to OpenCV 2.4.6.1
More info at:
http://opencv.org/opencv-2-4-6-is-out.html
The brief list of changes:
* added video file i/o Windows RT and sample application using
camera, enabled parallelization with TBB or MS Concurrency
* added CUDA 5.5 support for desktop and ARM systems
* added Qt 5 support
* added many new OpenCL algorithms ports, included OpenCL binaries
into the Windows superpack
* iOS build scripts (together with Android ones) moved to
‘opencv/platforms’ directory
* added functions for UIImage <-> cv::Mat conversion
* correct front/back camera selection in Android app framework
* added Linaro NDK support and fixes for MIPS to Android CMake
toolchain
* stability has been improved by a lot, numerous bug-fixes across
all the library
- build with LFS_CFLAGS in 32 bit archs.
- Disable SSE3 for all architectures (bnc#814333)
- Disable SSE(2) on non x86_64 architectures, causes crashing
kde#276923, bnc#789173
- Update to OpenCV 2.4.5
More info at:
http://opencv.org/opencv-2-4-5-is-out.html
The brief list of changes:
* experimental WinRT support
* new video super-resolution module
* CLAHE (adaptive histogram equalization) algorithm on both CPU
and GPU
* further improvements and extensions in ocl module
(stereo block matching and belief propagation have been added,
fixed crashes on Intel HD4000)
* Visual Studio 2012 cv::Mat visualizer plugin debugger tutorial
from Microsoft Research
* OpenCV4Android SDK improvements
(NDK r8e support, native activity sample using OpenCV Manager,
bug-fixes)
* ~25 reported problems have been resolved since 2.4.4, ~78 pull
requests have been merged, thanks everybody who participated!
- Update to OpenCV 2.4.4
More info at:
http://opencv.org/opencv-2-4-4-is-out.html
The brief list of changes:
* OpenCV Java bindings are ported from Android to desktop Java!
Actually any JVM language will work, see Tutorial for details,
and Java or Scala code samples.
* Android application framework, samples, tutorials, and OpenCV
Manager are improved.
* Optimizations for the new NVIDIA Kepler architecture, CARMA
platform support and other new optimizations in CUDA.
* OpenCL module now builds successfully with various SDKs (from
AMD, NVIDIA, Intel and Apple) and runs well on different GPUs
(AMD, NVidia, Intel HD4000). A lot of new functionality has been
added, tons of bugs fixed, performance of many functions has
been significantly improved.
* 100+ reported problems have been resolved since 2.4.3, thanks
everybody who participated!
- Drop the buildrequire for libxine
- Update to OpenCV 2.4.3
More info at:
http://opencv.org/opencv-2-4-3-released.html
The nicely formatted changelog can be seen here:
http://code.opencv.org/projects/opencv/wiki/ChangeLog;
here are the highlights:
* A lot of good stuff from the Google Summer of Code 2012 has been
integrated; this was a very productive summer!
* Significantly improved and optimized Android and iOS ports.
* Greatly extended GPU (i.e. CUDA-based) module.
* The brand new ocl (OpenCL-based) module that unleashes GPU power
also for AMD and Intel GPU users. It’s not included into the
binary package, since there are different SDKs, and it’s not
turned on by default. You need to run CMake and turn on
“WITH_OPENCL”. Also, please note that this is very first version
of the module, so it may be not very stable and not very
functional.
* Much better performance on many-core systems out of the box. You
do not need TBB anymore on MacOSX, iOS and Windows. BTW, the
binary package for Windows is now built without TBB support.
Libraries and DLLs for Visual Studio 2010 use the Concurrency
framework.
* About 130 bugs have been fixed since 2.4.2.
* Since 2.4.3rc we fixed several more problems, in particular some
compile problems with iOS 6 SDK.
- buildrequire glu
- Update to OpenCV 2.4.2
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Drop opencv-datadir.patch to comply with upstream directory layout
- Update to OpenCV 2.4.1
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Update to OpenCV 2.4.0
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Add opencv-gcc47.patch: Fix build with gcc 4.7.
- Use Explicit Buildrequires on several needed libraries
future dependency cleanups may/will cause build to fail otherwise.
- Add upstream r6881 to fix clang compatibility
- uncomment libraries not in 12.1 for now
- Changed groups (fix for RPMLINT warning)
- Added check for duplicate files (fix for RPMLINT warning)
- Added py_requires macros and python-base dependencies (fix for RPMLINT warning)
- Escaped macros (fix for RPMLINT warning)
- Fixed end-of-line encoding problems (fix for RPMLINT warning)
- Added libeigen2-devel buildrequires
- Added libunicap and libucil buildrequires (libunicap supports requires libucil)
- Cleaned up spec file formatting
- Dropped opencv-2.3-ffmpeg.patch, applied upstream
- Revive opencv-2.3-ffmpeg.patch, needs rebase
- Tag all patches according to openSUSE packaging guidelines
- Removed opencv-2.3-cmake.patch, old cmake cannot be used any more.
- Python bindings cannot be built without NumPy any more.
- Update to OpenCV 2.3.1
- Update and readd opencv-2.3-underlinking.patch since it is still
necessary.
- Fix support for new ffmpeg versions
- Removed unnecessary patches
- Enable Python NumPy support on openSUSE 11.2
- Build Qt instead of Gtk GUI
- Fix cmake files for openSUSE 11.1
- No GStreamer support on openSUSE 11.1
- Update to OpenCV 2.3.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Fix build on openSUSE 11.2
- Add opencv-v4l-2.6.38.patch: use the new libv4l2 interface
- Enable Python NumPy support
- SWIG is not required any more
- Enable OpenEXR support
- Update to OpenCV 2.2.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Use system zlib, oh, and do not export ZLIB symbols to
other applications, clashes ensued.
- fix build with gcc 4.6
- add -underlinking patch
- devel package renamed to opencv-devel, so that switching between
OBS and packman opencv packages is easier
- fix gstreamer support
- fix xine support
- fix some rpmlint warnings
- fix shared libraries permissions
- Do not waste resources building the tests as we do not run them
- Do not disable SSE,SSE2,etc. According to OpenCV changelog,
it should be safe to leave these enabled.
- fix build on openSUSE 11.0
- Update to OpenCV 2.1.0:
* The whole OpenCV is now using exceptions instead of the old
libc-style mechanism
* Experimental "static" OpenCV configuration in CMake was
contributed by Jose Luis Blanco.
Pass "BUILD_SHARED_LIBS=OFF" to CMake to build OpenCV statically.
* new improved version of one-way descriptor is added
* User can now control the image areas visible after the stereo
rectification
* Fullscreen has been added (thanks to Yannick Verdie).
* Further info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- fix build with libpng14
- small spec file cleanup
- Moved to the KDE repositories to enable inclusion in kipi-plugins
- Initial package
OBS-URL: https://build.opensuse.org/request/show/714221
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/opencv?expand=0&rev=73
2019-07-17 13:13:58 +02:00
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2011-10-18 14:24:16 +02:00
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Accepting request 983700 from home:StefanBruens:branches:science
- update to 4.6.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version460
* OpenCV project infrastructure migrating on GitHub Actions
workflows for CI and release purposes
* Added support for GCC 12, Clang 15
* Added support for FFmpeg 5.0
* DNN module patches:
+ Improved layers / activations / supported more models:
- LSTM (+CUDA), resize (+ONNX13), Sign, Shrink, Reciprocal,
depth2space, space2depth
- fixes in Reduce, Slice, Expand
+ Disabled floating-point denormals processing #21521
+ Changed layer names in ONNX importer to support "output"
entities properly
+ Added TIM-VX NPU backend support:
https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU
+ Added Softmax parameter to ClassificationModel
+ Added audio speech recognition sample (C++) #21458
+ Intel® Inference Engine backend (OpenVINO):
- added initial support for OpenVINO 2022.1 release
- removed support of legacy API (dropped since 2020.3)
* G-API module:
+ G-API framework:
- Introduced a Grayscale image format support for
cv::MediaFrame: #21511;
- Enabeled .reshape() support in the CPU backend: #21669;
- Fixed possible hang in streaming execution mode with constant
inputs: #21567;
- Introduced proper error/exception propagation in the
asynchronous streaming execution mode: #21660;
- Fixed new stream event handling: #21731.
+ Fluid backend:
- Fixed horizontal pass in the Resize kernel, fixed Valgrind
issues: #21144;
- Extended Resize kernel with F32 version: #21678,
added AVX: #21728.
- Enabled dynamic dispatch for Split4 kernel: #21520;
- Enabled dynamic dispatch for Merge3 kernel: #21529;
- Added a SIMD version for DivC kernel: #21474;
- Added a SIMD version for DivRC kernel: #21530;
- Enabled dynamic dispatch for Add kernel: #21686;
- Enabled dynamic dispatch for Sub kernel: #21746;
- Added a SIMD version for ConvertTo kernel: #21777;
- Fixed kernel matrix size for Sobel kernel: #21613.
+ Intel® OpenVINO™ inference backend:
- Fixed NV12 format support for remote memory when OpenVINO
remote context is used: #21424.
- Implemented correct error handling in the backend: #21579.
- Fixed ngraph warnings #21362.
+ OpenCV AI Kit backend:
- Introduced a new backend to program OpenCV AI Kit boards via
G-API. Currently the backend is in experimental state, but allows
to build Camera+NN pipeline and supports heterogeneity (mixing
with host-side code): #20785, #21504.
+ Media integration:
- Enabled GPU inference with oneVPL and DirectX11 on Windows in
Intel OpenVINO inference backend: #21232, #21618, #21658, #21687,
#21688. Now GPU textures decoded by oneVPL decoder can be
preprocessed and inferred on GPU with no extra host processing.
- Enabled oneVPL support on Linux: #21883.
- Extended GStreamer pipeline source with Grayscale image format
support: #21560.
+ Python bindings:
- Exposed GStreamer pipeline source in Python bindings: #20832.
- Fixed Python bindings for CudaBufferPool, cudacodec and cudastereo
modules in OpenCV Contrib.
+ Samples:
- Introduced a pipeline modelling tool for cascaded model
benchmarking: #21477, #21636, #21719. The tool supports a
declarative YAML-based config to describe pipelines with simulated
pre-/post-processing. The tool collects and reports latency and
throughput information for the modelled pipeline.
+ Other changes and fixes:
- Moved GKernelPackage into cv:: namespace by default, its cv::gapi::
alias remain for compatibility: #21318;
- Moved Resize kernel from core to imgproc kernel packages for
CPU, OpenCL, and Fluid backends: #21157. Also moved tests
appropriately: #21475;
- Avoided sporadic test failures in DivC: #21626;
- Fixed 1D Mat handling in the framework: #21782;
- Reduced the number of G-API generated accuracy tests: #21909.
- Drop upstream patches:
* 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
* videoio_initial_FFmpeg_5_0_support.patch
* videoio_ffmpeg_avoid_memory_leaks.patch
OBS-URL: https://build.opensuse.org/request/show/983700
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=33
2022-06-27 18:05:05 +02:00
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Accepting request 983700 from home:StefanBruens:branches:science
- update to 4.6.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version460
* OpenCV project infrastructure migrating on GitHub Actions
workflows for CI and release purposes
* Added support for GCC 12, Clang 15
* Added support for FFmpeg 5.0
* DNN module patches:
+ Improved layers / activations / supported more models:
- LSTM (+CUDA), resize (+ONNX13), Sign, Shrink, Reciprocal,
depth2space, space2depth
- fixes in Reduce, Slice, Expand
+ Disabled floating-point denormals processing #21521
+ Changed layer names in ONNX importer to support "output"
entities properly
+ Added TIM-VX NPU backend support:
https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU
+ Added Softmax parameter to ClassificationModel
+ Added audio speech recognition sample (C++) #21458
+ Intel® Inference Engine backend (OpenVINO):
- added initial support for OpenVINO 2022.1 release
- removed support of legacy API (dropped since 2020.3)
* G-API module:
+ G-API framework:
- Introduced a Grayscale image format support for
cv::MediaFrame: #21511;
- Enabeled .reshape() support in the CPU backend: #21669;
- Fixed possible hang in streaming execution mode with constant
inputs: #21567;
- Introduced proper error/exception propagation in the
asynchronous streaming execution mode: #21660;
- Fixed new stream event handling: #21731.
+ Fluid backend:
- Fixed horizontal pass in the Resize kernel, fixed Valgrind
issues: #21144;
- Extended Resize kernel with F32 version: #21678,
added AVX: #21728.
- Enabled dynamic dispatch for Split4 kernel: #21520;
- Enabled dynamic dispatch for Merge3 kernel: #21529;
- Added a SIMD version for DivC kernel: #21474;
- Added a SIMD version for DivRC kernel: #21530;
- Enabled dynamic dispatch for Add kernel: #21686;
- Enabled dynamic dispatch for Sub kernel: #21746;
- Added a SIMD version for ConvertTo kernel: #21777;
- Fixed kernel matrix size for Sobel kernel: #21613.
+ Intel® OpenVINO™ inference backend:
- Fixed NV12 format support for remote memory when OpenVINO
remote context is used: #21424.
- Implemented correct error handling in the backend: #21579.
- Fixed ngraph warnings #21362.
+ OpenCV AI Kit backend:
- Introduced a new backend to program OpenCV AI Kit boards via
G-API. Currently the backend is in experimental state, but allows
to build Camera+NN pipeline and supports heterogeneity (mixing
with host-side code): #20785, #21504.
+ Media integration:
- Enabled GPU inference with oneVPL and DirectX11 on Windows in
Intel OpenVINO inference backend: #21232, #21618, #21658, #21687,
#21688. Now GPU textures decoded by oneVPL decoder can be
preprocessed and inferred on GPU with no extra host processing.
- Enabled oneVPL support on Linux: #21883.
- Extended GStreamer pipeline source with Grayscale image format
support: #21560.
+ Python bindings:
- Exposed GStreamer pipeline source in Python bindings: #20832.
- Fixed Python bindings for CudaBufferPool, cudacodec and cudastereo
modules in OpenCV Contrib.
+ Samples:
- Introduced a pipeline modelling tool for cascaded model
benchmarking: #21477, #21636, #21719. The tool supports a
declarative YAML-based config to describe pipelines with simulated
pre-/post-processing. The tool collects and reports latency and
throughput information for the modelled pipeline.
+ Other changes and fixes:
- Moved GKernelPackage into cv:: namespace by default, its cv::gapi::
alias remain for compatibility: #21318;
- Moved Resize kernel from core to imgproc kernel packages for
CPU, OpenCL, and Fluid backends: #21157. Also moved tests
appropriately: #21475;
- Avoided sporadic test failures in DivC: #21626;
- Fixed 1D Mat handling in the framework: #21782;
- Reduced the number of G-API generated accuracy tests: #21909.
- Drop upstream patches:
* 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
* videoio_initial_FFmpeg_5_0_support.patch
* videoio_ffmpeg_avoid_memory_leaks.patch
OBS-URL: https://build.opensuse.org/request/show/983700
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=33
2022-06-27 18:05:05 +02:00
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Accepting request 714221 from science
- Update to version 4.1.0
* DNN module:
+ Reduced peak memory consumption for some models up to 30%.
+ Inference Engine
- Inference Engine 2018R3 is now a minimal supported version of IE.
- Myriad X (Intel® Neural Compute Stick 2) is now supported and tested.
- Automatic IR network reshaping for different inputs.
- Improved samples to work with models from OpenVINO Open Model Zoo
+ New networks from TensorFlow Object Detection API: Faster-RCNNs, SSDs
and Mask-RCNN with dilated convolutions, FPN SSD
* Performance improvements:
+ More optimization using AVX2 instruction set.
+ Automatic runtime dispatching is available for large set of functions
from core and imgproc modules.
* Other improvements:
+ Matplotlib Perceptually Uniform Sequential colormaps
+ Add keypoints matching visualization for real-time pose estimation tutorial
+ Add Hand-Eye calibration methods
+ Java: improved support for multidimensional arrays (Mat)
+ Dynamically loaded videoio backends (FFmpeg, GStreamer)
+ opencv_contrib: Robust local optical flow (RLOF) implementations
+ opencv_contrib: Implementation of Quasi Dense Stereo algorithm
+ opencv_contrib: New module: Image Quality Analysis (IQA) API
+ opencv_contrib: BRISQUE No Reference Image Quality Assessment (IQA) API
Check https://github.com/opencv/opencv/wiki/ChangeLog#version410
- Update to version 4.0.0
* A lot of C API from OpenCV 1.x has been removed. The affected modules are
objdetect, photo, video, videoio, imgcodecs, calib3d.
* Persistence (storing and loading structured data to/from XML, YAML or JSON)
in the core module has been completely reimplemented.
* OpenCV is now C++11 library and requires C++11-compliant compiler.
Thanks to the extended C++11 standard library, we could get rid of hand-crafted
cv::String and cv::Ptr. Now cv::String == std::string and cv::Ptr is a thin
wrapper on top of std::shared_ptr. Also, on Linux/BSD for cv::parallel_for_
we now use std::thread's instead of pthreads.
* DNN improvements
* Completely new module opencv_gapi has been added. It is the engine for very
efficient image processing, based on lazy evaluation and on-fly construction.
* Performance improvements
A few hundreds of basic kernels in OpenCV have been rewritten using so-called
"wide universal intrinsics". Those intrinsics map to SSE2, SSE4, AVX2, NEON or
VSX intrinsics, depending on the target platform and the compile flags.
* QR code detector and decoder have been added to opencv/objdetect module.
* The popular Kinect Fusion algorithm has been implemented, optimized for CPU and
GPU (OpenCL), and integrated into opencv_contrib/rgbd module.
* Very efficient and yet high-quality DIS dense optical flow algorithm has been
moved from opencv_contrib to opencv, video module. See the example.
* The slower TV L1 optical flow algorithm has been moved to opencv_contrib.
Check https://github.com/opencv/opencv/wiki/ChangeLog#version400
- Drop obsolete opencv-lib_suffix.patch
- Add 0001-Handle-absolute-OPENCV_INCLUDE_INSTALL_PATH-correctl.patch
- As this is a major version upgrade, the old 3.4.x package is still
available as opencv3
- Update to 3.4.3
* Compatibility fixes with python 3.7
* Added a new computational target DNN_TARGET_OPENCL_FP16
* Extended support of Intel's Inference Engine backend
* Enabled import of Intel's OpenVINO pre-trained networks from
intermediate representation (IR).
* tutorials improvements
Check https://github.com/opencv/opencv/wiki/ChangeLog#version343
for the complete changelog.
- Drop fix-build-i386-nosse.patch, build-workaround-issues-with-c.patch
(fixed upstream)
- Refresh patches
- Add patch to fix use of headers from C:
* build-workaround-issues-with-c.patch
- Update to 3.4.1:
* Added support for quantized TensorFlow networks
* OpenCV is now able to use Intel DL inference engine as DNN
acceleration backend
* Added AVX-512 acceleration to the performance-critical kernels
* For more information, read
https://github.com/opencv/opencv/wiki/ChangeLog#version341
- Update contrib modules to 3.4.1:
* No changelog available
- Change mechanism the contrib modules are built
- Include LICENSE of contrib tarball as well
- Build with python3 on >= 15
- Add patch to fix build on i386 without SSE:
* fix-build-i386-nosse.patch
- Refresh patches:
* fix_processor_detection_for_32bit_on_64bit.patch
* opencv-build-compare.patch
- Mention all libs explicitly
- Rebase 3.4.0 update from i@marguerite.su
- update to 3.4.0
* Added faster R-CNN support
* Javascript bindings have been extended to
cover DNN module
* DNN has been further accelerated for iGPU
using OpenCL
* On-disk caching of precompiled OpenCL
kernels has been finally implemented
* possible to load and run pre-compiled
OpenCL kernels via T-API
* Bit-exact 8-bit and 16-bit resize has been
implemented (currently supported only
bilinear interpolation)
- update face module to 3.4.0
- add opencv-lib_suffix.patch, remove LIB_SUFFIX
from OPENCV_LIB_INSTALL_PATH, as CMAKE_INSTALL
_LIBDIR is arch dependent.
- Add option to build without openblas
- Add conditionals for python2 and python3 to allow us enabling
only desired python variants when needed
- Do not depend on sphinx as py2 and py3 seem to collide there
- Readd opencv-gles.patch, it is *not* included upstream; otherwise
build breaks on all GLES Qt5 platforms (armv6l, armv7l, aarch64)
- add fix_processor_detection_for_32bit_on_64bit.patch
- Correctly set optimizations and dynamic dispatch on ARM, use
OpenCV 3.3 syntax on x86.
- Update licensing information
- change requires of python-numpy-devel to build in Leap and
to not break factory in future
- fix build error/unresolvable for Leap 42.2 and 42.3
- Update to version 3.3.1:
* Lots of various bugfixes
- Update source url
- Rename python subpackage to python2
- Do not explicitly require python-base for python subpackages
- Update to 3.3
- Dropped obsolete patches
* opencv-gcc6-fix-pch-support-PR8345.patch
* opencv-gles.patch
- Updated opencv-build-compare.patch
- Add 0001-Do-not-include-glx.h-when-using-GLES.patch
Fix build for 32bit ARM, including both GLES and desktop GL headers
causes incompatible pointer type errors
- Add conditional for the qt5/qt4 integration
* This is used only for gui tools, library is not affected
- Add provides/obsoletes for the qt5 packages to allow migration
- Drop patch opencv-qt5-sobump.diff
* Used only by the obsoleted qt5 variant
- Cleanup a bit with spec-cleaner
- Use %cmake macros
- Remove the conditions that are not really needed
- Add tests conditional disabled by default
* Many tests fail and there are missing testdata
- Switch to pkgconfig style dependencies
- Update to OpenCV 3.2.0
- Results from 11 GSoC 2016 projects have been submitted to the library:
+ sinusoidal patterns for structured light and phase unwrapping module
[Ambroise Moreau (Delia Passalacqua)]
+ DIS optical flow (excellent dense optical flow algorithm that is both
significantly better and significantly faster than Farneback’s algorithm –
our baseline), and learning-based color constancy algorithms implementation
[Alexander Bokov (Maksim Shabunin)]
+ CNN based tracking algorithm (GOTURN) [Tyan Vladimir (Antonella Cascitelli)]
+ PCAFlow and Global Patch Collider algorithms implementation
[Vladislav Samsonov (Ethan Rublee)]
+ Multi-language OpenCV Tutorials in Python, C++ and Java
[João Cartucho (Vincent Rabaud)]
+ New camera model and parallel processing for stitching pipeline
[Jiri Horner (Bo Li)]
+ Optimizations and improvements of dnn module
[Vitaliy Lyudvichenko (Anatoly Baksheev)]
+ Base64 and JSON support for file storage. Use names like
“myfilestorage.xml?base64” when writing file storage to store big chunks of
numerical data in base64-encoded form. [Iric Wu (Vadim Pisarevsky)]
+ tiny_dnn improvements and integration
[Edgar Riba (Manuele Tamburrano, Stefano Fabri)]
+ Quantization and semantic saliency detection with tiny_dnn
[Yida Wang (Manuele Tamburrano, Stefano Fabri)]
+ Word-spotting CNN based algorithm
[Anguelos Nicolaou (Lluis Gomez)]
- Contributions besides GSoC:
+ Greatly improved and accelerated dnn module in opencv_contrib:
- Many new layers, including deconvolution, LSTM etc.
- Support for semantic segmentation and SSD networks with samples.
- TensorFlow importer + sample that runs Inception net by Google.
+ More image formats and camera backends supported
+ Interactive camera calibration app
+ Multiple algorithms implemented in opencv_contrib
+ Supported latest OSes, including Ubuntu 16.04 LTS and OSX 10.12
+ Lot’s of optimizations for IA and ARM archs using parallelism, vector
instructions and new OpenCL kernels.
+ OpenCV now can use vendor-provided OpenVX and LAPACK/BLAS (including Intel MKL,
Apple’s Accelerate, OpenBLAS and Atlas) for acceleration
- Refreshed opencv-build-compare.patch
- Dropped upstream opencv-gcc5.patch
- Replace opencv-gcc6-disable-pch.patch with upstream patch
opencv-gcc6-fix-pch-support-PR8345.patch
- Enable TBB support (C++ threading library)
- Add dependency on openBLAS
- Enable ffmpeg support unconditional
- In case we build using GCC6 (or newer), add -mlra to CFLAGS to
workaround gcc bug
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=71294.
- Apply upstream patch opencv-gcc6-disable-pch.patch to disable
PCH for GCC6.
- Test for python versions greater than or equal to the current
version.
- Add python 3 support
- Added opencv_contrib_face-3.1.0.tar.bz2
* This tarball is created to take only the face module from the
contrib package. The Face module is required by libkface, which
in its turn is required by digikam.
- Added _constraints file to avoid random failures on small workers
(at least for builds on PMBS)
- Update to OpenCV 3.1.0
- A lot of new functionality has been introduced during Google
Summer of Code 2015:
+ “Omnidirectional Cameras Calibration and Stereo 3D
Reconstruction” – opencv_contrib/ccalib module
(Baisheng Lai, Bo Li)
+ “Structure From Motion” – opencv_contrib/sfm module
(Edgar Riba, Vincent Rabaud)
+ “Improved Deformable Part-based Models” – opencv_contrib/dpm
module (Jiaolong Xu, Bence Magyar)
+ “Real-time Multi-object Tracking using Kernelized Correlation
Filter” – opencv_contrib/tracking module
(Laksono Kurnianggoro, Fernando J. Iglesias Garcia)
+ “Improved and expanded Scene Text Detection” –
opencv_contrib/text module (Lluis Gomez, Vadim Pisarevsky)
+ “Stereo correspondence improvements” – opencv_contrib/stereo
module (Mircea Paul Muresan, Sergei Nosov)
+ “Structured-Light System Calibration” –
opencv_contrib/structured_light (Roberta Ravanelli,
Delia Passalacqua, Stefano Fabri, Claudia Rapuano)
+ “Chessboard+ArUco for camera calibration” –
opencv_contrib/aruco (Sergio Garrido, Prasanna, Gary Bradski)
+ “Implementation of universal interface for deep neural
network frameworks” – opencv_contrib/dnn module
(Vitaliy Lyudvichenko, Anatoly Baksheev)
+ “Recent advances in edge-aware filtering, improved SGBM
stereo algorithm” – opencv/calib3d and opencv_contrib/ximgproc
(Alexander Bokov, Maksim Shabunin)
+ “Improved ICF detector, waldboost implementation” –
opencv_contrib/xobjdetect (Vlad Shakhuro, Alexander Bovyrin)
+ “Multi-target TLD tracking” – opencv_contrib/tracking module
(Vladimir Tyan, Antonella Cascitelli)
+ “3D pose estimation using CNNs” – opencv_contrib/cnn_3dobj
(Yida Wang, Manuele Tamburrano, Stefano Fabri)
- Many great contributions made by the community, such as:
+ Support for HDF5 format
+ New/Improved optical flow algorithms
+ Multiple new image processing algorithms for filtering,
segmentation and feature detection
+ Superpixel segmentation and much more
- IPPICV is now based on IPP 9.0.1, which should make OpenCV
even faster on modern Intel chips
- opencv_contrib modules can now be included into the
opencv2.framework for iOS
- Newest operating systems are supported: Windows 10 and
OSX 10.11 (Visual Studio 2015 and XCode 7.1.1)
- Interoperability between T-API and OpenCL, OpenGL, DirectX and
Video Acceleration API on Linux, as well as Android 5 camera.
- HAL (Hardware Acceleration Layer) module functionality has been
moved into corresponding basic modules; the HAL replacement
mechanism has been implemented along with the examples
- Removed improve-sphinx-search.diff, opencv-altivec-vector.patch,
opencv-pkgconfig.patch and opencv-samples.patch, fixed upstream.
- Fixed opencv-qt5-sobump.diff, opencv-build-compare.patch,
opencv-gcc5.patch and opencv-gles.patch.
- Version OpenCV 3.0.0
+ ~1500 patches, submitted as PR @ github. All our patches go
the same route.
+ opencv_contrib (http://github.com/itseez/opencv_contrib)
repository has been added. A lot of new functionality is there
already! opencv_contrib is only compatible with 3.0/master,
not 2.4. Clone the repository and use “cmake …
-D OPENCV_EXTRA_MODULES_PATH=<path_to opencv_contrib/modules> …”
to build opencv and opencv_contrib together.
+ a subset of Intel IPP (IPPCV) is given to us and our users free
of charge, free of licensing fees, for commercial and
non-commerical use. It’s used by default in x86 and x64 builds
on Windows, Linux and Mac.
+ T-API (transparent API) has been introduced, this is transparent
GPU acceleration layer using OpenCL. It does not add any
compile-time or runtime dependency of OpenCL. When OpenCL is
available, it’s detected and used, but it can be disabled at
compile time or at runtime. It covers ~100 OpenCV functions.
This work has been done by contract and with generous support
from AMD and Intel companies.
+ ~40 OpenCV functions have been accelerated using NEON intrinsics
and because these are mostly basic functions, some higher-level
functions got accelerated as well.
+ There is also new OpenCV HAL layer that will simplifies creation
of NEON-optimized code and that should form a base for the
open-source and proprietary OpenCV accelerators.
+ The documentation is now in Doxygen: http://docs.opencv.org/master/
+ We cleaned up API of many high-level algorithms from features2d,
calib3d, objdetect etc. They now follow the uniform
“abstract interface – hidden implementation” pattern and make
extensive use of smart pointers (Ptr<>).
+ Greatly improved and extended Python & Java bindings (also,
see below on the Python bindings), newly introduced Matlab
bindings (still in alpha stage).
+ Improved Android support – now OpenCV Manager is in Java and
supports both 2.4 and 3.0.
+ Greatly improved WinRT support, including video capturing and
multi-threading capabilities. Thanks for Microsoft team for this!
+ Big thanks to Google who funded several successive GSoC programs
and let OpenCV in. The results of many successful GSoC 2013 and
2014 projects have been integrated in opencv 3.0 and
opencv_contrib (earlier results are also available in
OpenCV 2.4.x). We can name:
- text detection
- many computational photography algorithms (HDR, inpainting,
edge-aware filters, superpixels, …)
- tracking and optical flow algorithms
- new features, including line descriptors, KAZE/AKAZE
- general use optimization (hill climbing, linear programming)
- greatly improved Python support, including Python 3.0 support,
many new tutorials & samples on how to use OpenCV with Python.
- 2d shape matching module and 3d surface matching module
- RGB-D module
- VTK-based 3D visualization module
- etc.
+ Besides Google, we enjoyed (and hope that you will enjoy too)
many useful contributions from community, like:
- biologically inspired vision module
- DAISY features, LATCH descriptor, improved BRIEF
- image registration module
- etc.
- Reduce build-compare noise
opencv-build-compare.patch
- Remove BuildRequirement for python-sphinx in SLE12, since it's
not available there and it's not a mandatory requirement.
- Reduce differences between two spec files
- Use pkgconfig for ffmpeg BuildRequires
- Update improve-sphinx-search.diff for new python-Sphinx(1.3.1)
* now that sphinx-build disallow executing without arguments and
give you "Insufficient arguments" error, use "sphinx-build -h"
instead
* the default usages output ie. sphinx-build(or --help) no longer
are standard error but standard output, drop OUTPUT_QUIET and
add OUTPUT_VARIABLE throws the output to SPHINX_OUTPUT as well
- support gcc 5 (i.e. gcc versions without minor version):
opencv-gcc5.patch
- Update to OpenCV 2.4.11 - can't find NEWS or Changelog
merely collecting bug fixes while 3.0 is in the making, 2.4.11
didn't even make it on their web page, it's only on download
server
- remove opencv-underlinking.patch as obsolete
- remove upstream patch bomb_commit_gstreamer-1x-support.patch
- commenting out opencv-pkgconfig.patch - possibly it requires a rebase,
but the problem it tries to solve is unclear
- Add specific buildrequires for libpng15, so that we are
building against the system provided libpng.
- Update to OpenCV 2.4.9
More info at:
http://opencv.org/opencv-2-4-9-is-out.html
The brief list of changes:
* new 3D visualization module ‘viz’;
* performance fixes in ‘ocl’ module;
* fixes in Android Camera;
* improved CUDA support for mobile platforms;
* bugfixes from community;
* 55 reported bugs have been closed;
* 156 pull requests have been merged.
- Drop the BuildRequires on libucil and libunicap for Factory. This
stops us from getting ride of Gstreamer 0.10 and besides these two
libraries seem to be unmaintained upstream as that the latest
actions are from 2010
- Add upstream patch (3.0 version) to support Gstreamer 1.x
* bomb_commit_gstreamer-1x-support.patch
- Upstream now provides tarballs with source only as git tags
from github so update Source0 path.
- Add requires on various X extensions linked to opencv_ts module.
As those are present in the .pc file we need it anyway.
- Update to OpenCV 2.4.8
More info at:
http://opencv.org/opencv-2-4-8.html
The brief list of changes:
* NVidia CUDA support on Android devices with CUDA capable SoC and
CUDA sample;
* Concurrent kernel execution and user defined context support for
OpenCL;
* Integration with Intel Perceptual SDK and new depth sensors support
for Windows;
* 32 reported bugs have been closed;
* 139 pull requests have been merged;
- Fix build with altivec:
opencv-altivec-vector.patch
- Added opencv-pkgconfig.patch: make sure to provide link flags in
OpenCV pc file (bnc#853036)
- Update to OpenCV 2.4.7
More info at:
http://opencv.org/opencv-2-4-7-is-out.html
The brief list of changes:
* dynamic OpenCL runtime loading, setting default OpenCL device
via env var, many bug-fixes and some new optimization with OpenCL
* bug-fixes and new optimizations in CUDA stuff
* latest NDK and Android OS support, Native Android Camera tuning
* minor fixes, XAML sample and MS Certification compatibility
in WinRT stuff
* 382 pull requests have been merged
* 54 reported bugs have been fixed
- Added pkgconfig(glu) Requires to devel package, as per .pc file
- Make devel package provides also devel-static one
- Drop assume-Sphinx-is-there.diff, and add improve-sphinx-search.diff,
for properly finding sphinx with alphabetic chars in version
- Add patch assume-Sphinx-is-there.diff to fix building with
Sphinx versions that have alphanumeric characters in the version
(Only for factory builds at the moment)
- Use eigen3 instead of eigen2 as build requirement for openSUSE > 12.3.
- Enable compilation with libucil and libunicap.
- Removed dos2unix build requirement (not needed anymore).
- Update to OpenCV 2.4.6.1
More info at:
http://opencv.org/opencv-2-4-6-is-out.html
The brief list of changes:
* added video file i/o Windows RT and sample application using
camera, enabled parallelization with TBB or MS Concurrency
* added CUDA 5.5 support for desktop and ARM systems
* added Qt 5 support
* added many new OpenCL algorithms ports, included OpenCL binaries
into the Windows superpack
* iOS build scripts (together with Android ones) moved to
‘opencv/platforms’ directory
* added functions for UIImage <-> cv::Mat conversion
* correct front/back camera selection in Android app framework
* added Linaro NDK support and fixes for MIPS to Android CMake
toolchain
* stability has been improved by a lot, numerous bug-fixes across
all the library
- build with LFS_CFLAGS in 32 bit archs.
- Disable SSE3 for all architectures (bnc#814333)
- Disable SSE(2) on non x86_64 architectures, causes crashing
kde#276923, bnc#789173
- Update to OpenCV 2.4.5
More info at:
http://opencv.org/opencv-2-4-5-is-out.html
The brief list of changes:
* experimental WinRT support
* new video super-resolution module
* CLAHE (adaptive histogram equalization) algorithm on both CPU
and GPU
* further improvements and extensions in ocl module
(stereo block matching and belief propagation have been added,
fixed crashes on Intel HD4000)
* Visual Studio 2012 cv::Mat visualizer plugin debugger tutorial
from Microsoft Research
* OpenCV4Android SDK improvements
(NDK r8e support, native activity sample using OpenCV Manager,
bug-fixes)
* ~25 reported problems have been resolved since 2.4.4, ~78 pull
requests have been merged, thanks everybody who participated!
- Update to OpenCV 2.4.4
More info at:
http://opencv.org/opencv-2-4-4-is-out.html
The brief list of changes:
* OpenCV Java bindings are ported from Android to desktop Java!
Actually any JVM language will work, see Tutorial for details,
and Java or Scala code samples.
* Android application framework, samples, tutorials, and OpenCV
Manager are improved.
* Optimizations for the new NVIDIA Kepler architecture, CARMA
platform support and other new optimizations in CUDA.
* OpenCL module now builds successfully with various SDKs (from
AMD, NVIDIA, Intel and Apple) and runs well on different GPUs
(AMD, NVidia, Intel HD4000). A lot of new functionality has been
added, tons of bugs fixed, performance of many functions has
been significantly improved.
* 100+ reported problems have been resolved since 2.4.3, thanks
everybody who participated!
- Drop the buildrequire for libxine
- Update to OpenCV 2.4.3
More info at:
http://opencv.org/opencv-2-4-3-released.html
The nicely formatted changelog can be seen here:
http://code.opencv.org/projects/opencv/wiki/ChangeLog;
here are the highlights:
* A lot of good stuff from the Google Summer of Code 2012 has been
integrated; this was a very productive summer!
* Significantly improved and optimized Android and iOS ports.
* Greatly extended GPU (i.e. CUDA-based) module.
* The brand new ocl (OpenCL-based) module that unleashes GPU power
also for AMD and Intel GPU users. It’s not included into the
binary package, since there are different SDKs, and it’s not
turned on by default. You need to run CMake and turn on
“WITH_OPENCL”. Also, please note that this is very first version
of the module, so it may be not very stable and not very
functional.
* Much better performance on many-core systems out of the box. You
do not need TBB anymore on MacOSX, iOS and Windows. BTW, the
binary package for Windows is now built without TBB support.
Libraries and DLLs for Visual Studio 2010 use the Concurrency
framework.
* About 130 bugs have been fixed since 2.4.2.
* Since 2.4.3rc we fixed several more problems, in particular some
compile problems with iOS 6 SDK.
- buildrequire glu
- Update to OpenCV 2.4.2
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Drop opencv-datadir.patch to comply with upstream directory layout
- Update to OpenCV 2.4.1
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Update to OpenCV 2.4.0
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Add opencv-gcc47.patch: Fix build with gcc 4.7.
- Use Explicit Buildrequires on several needed libraries
future dependency cleanups may/will cause build to fail otherwise.
- Add upstream r6881 to fix clang compatibility
- uncomment libraries not in 12.1 for now
- Changed groups (fix for RPMLINT warning)
- Added check for duplicate files (fix for RPMLINT warning)
- Added py_requires macros and python-base dependencies (fix for RPMLINT warning)
- Escaped macros (fix for RPMLINT warning)
- Fixed end-of-line encoding problems (fix for RPMLINT warning)
- Added libeigen2-devel buildrequires
- Added libunicap and libucil buildrequires (libunicap supports requires libucil)
- Cleaned up spec file formatting
- Dropped opencv-2.3-ffmpeg.patch, applied upstream
- Revive opencv-2.3-ffmpeg.patch, needs rebase
- Tag all patches according to openSUSE packaging guidelines
- Removed opencv-2.3-cmake.patch, old cmake cannot be used any more.
- Python bindings cannot be built without NumPy any more.
- Update to OpenCV 2.3.1
- Update and readd opencv-2.3-underlinking.patch since it is still
necessary.
- Fix support for new ffmpeg versions
- Removed unnecessary patches
- Enable Python NumPy support on openSUSE 11.2
- Build Qt instead of Gtk GUI
- Fix cmake files for openSUSE 11.1
- No GStreamer support on openSUSE 11.1
- Update to OpenCV 2.3.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Fix build on openSUSE 11.2
- Add opencv-v4l-2.6.38.patch: use the new libv4l2 interface
- Enable Python NumPy support
- SWIG is not required any more
- Enable OpenEXR support
- Update to OpenCV 2.2.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Use system zlib, oh, and do not export ZLIB symbols to
other applications, clashes ensued.
- fix build with gcc 4.6
- add -underlinking patch
- devel package renamed to opencv-devel, so that switching between
OBS and packman opencv packages is easier
- fix gstreamer support
- fix xine support
- fix some rpmlint warnings
- fix shared libraries permissions
- Do not waste resources building the tests as we do not run them
- Do not disable SSE,SSE2,etc. According to OpenCV changelog,
it should be safe to leave these enabled.
- fix build on openSUSE 11.0
- Update to OpenCV 2.1.0:
* The whole OpenCV is now using exceptions instead of the old
libc-style mechanism
* Experimental "static" OpenCV configuration in CMake was
contributed by Jose Luis Blanco.
Pass "BUILD_SHARED_LIBS=OFF" to CMake to build OpenCV statically.
* new improved version of one-way descriptor is added
* User can now control the image areas visible after the stereo
rectification
* Fullscreen has been added (thanks to Yannick Verdie).
* Further info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- fix build with libpng14
- small spec file cleanup
- Moved to the KDE repositories to enable inclusion in kipi-plugins
- Initial package
OBS-URL: https://build.opensuse.org/request/show/714221
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/opencv?expand=0&rev=73
2019-07-17 13:13:58 +02:00
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Accepting request 714221 from science
- Update to version 4.1.0
* DNN module:
+ Reduced peak memory consumption for some models up to 30%.
+ Inference Engine
- Inference Engine 2018R3 is now a minimal supported version of IE.
- Myriad X (Intel® Neural Compute Stick 2) is now supported and tested.
- Automatic IR network reshaping for different inputs.
- Improved samples to work with models from OpenVINO Open Model Zoo
+ New networks from TensorFlow Object Detection API: Faster-RCNNs, SSDs
and Mask-RCNN with dilated convolutions, FPN SSD
* Performance improvements:
+ More optimization using AVX2 instruction set.
+ Automatic runtime dispatching is available for large set of functions
from core and imgproc modules.
* Other improvements:
+ Matplotlib Perceptually Uniform Sequential colormaps
+ Add keypoints matching visualization for real-time pose estimation tutorial
+ Add Hand-Eye calibration methods
+ Java: improved support for multidimensional arrays (Mat)
+ Dynamically loaded videoio backends (FFmpeg, GStreamer)
+ opencv_contrib: Robust local optical flow (RLOF) implementations
+ opencv_contrib: Implementation of Quasi Dense Stereo algorithm
+ opencv_contrib: New module: Image Quality Analysis (IQA) API
+ opencv_contrib: BRISQUE No Reference Image Quality Assessment (IQA) API
Check https://github.com/opencv/opencv/wiki/ChangeLog#version410
- Update to version 4.0.0
* A lot of C API from OpenCV 1.x has been removed. The affected modules are
objdetect, photo, video, videoio, imgcodecs, calib3d.
* Persistence (storing and loading structured data to/from XML, YAML or JSON)
in the core module has been completely reimplemented.
* OpenCV is now C++11 library and requires C++11-compliant compiler.
Thanks to the extended C++11 standard library, we could get rid of hand-crafted
cv::String and cv::Ptr. Now cv::String == std::string and cv::Ptr is a thin
wrapper on top of std::shared_ptr. Also, on Linux/BSD for cv::parallel_for_
we now use std::thread's instead of pthreads.
* DNN improvements
* Completely new module opencv_gapi has been added. It is the engine for very
efficient image processing, based on lazy evaluation and on-fly construction.
* Performance improvements
A few hundreds of basic kernels in OpenCV have been rewritten using so-called
"wide universal intrinsics". Those intrinsics map to SSE2, SSE4, AVX2, NEON or
VSX intrinsics, depending on the target platform and the compile flags.
* QR code detector and decoder have been added to opencv/objdetect module.
* The popular Kinect Fusion algorithm has been implemented, optimized for CPU and
GPU (OpenCL), and integrated into opencv_contrib/rgbd module.
* Very efficient and yet high-quality DIS dense optical flow algorithm has been
moved from opencv_contrib to opencv, video module. See the example.
* The slower TV L1 optical flow algorithm has been moved to opencv_contrib.
Check https://github.com/opencv/opencv/wiki/ChangeLog#version400
- Drop obsolete opencv-lib_suffix.patch
- Add 0001-Handle-absolute-OPENCV_INCLUDE_INSTALL_PATH-correctl.patch
- As this is a major version upgrade, the old 3.4.x package is still
available as opencv3
- Update to 3.4.3
* Compatibility fixes with python 3.7
* Added a new computational target DNN_TARGET_OPENCL_FP16
* Extended support of Intel's Inference Engine backend
* Enabled import of Intel's OpenVINO pre-trained networks from
intermediate representation (IR).
* tutorials improvements
Check https://github.com/opencv/opencv/wiki/ChangeLog#version343
for the complete changelog.
- Drop fix-build-i386-nosse.patch, build-workaround-issues-with-c.patch
(fixed upstream)
- Refresh patches
- Add patch to fix use of headers from C:
* build-workaround-issues-with-c.patch
- Update to 3.4.1:
* Added support for quantized TensorFlow networks
* OpenCV is now able to use Intel DL inference engine as DNN
acceleration backend
* Added AVX-512 acceleration to the performance-critical kernels
* For more information, read
https://github.com/opencv/opencv/wiki/ChangeLog#version341
- Update contrib modules to 3.4.1:
* No changelog available
- Change mechanism the contrib modules are built
- Include LICENSE of contrib tarball as well
- Build with python3 on >= 15
- Add patch to fix build on i386 without SSE:
* fix-build-i386-nosse.patch
- Refresh patches:
* fix_processor_detection_for_32bit_on_64bit.patch
* opencv-build-compare.patch
- Mention all libs explicitly
- Rebase 3.4.0 update from i@marguerite.su
- update to 3.4.0
* Added faster R-CNN support
* Javascript bindings have been extended to
cover DNN module
* DNN has been further accelerated for iGPU
using OpenCL
* On-disk caching of precompiled OpenCL
kernels has been finally implemented
* possible to load and run pre-compiled
OpenCL kernels via T-API
* Bit-exact 8-bit and 16-bit resize has been
implemented (currently supported only
bilinear interpolation)
- update face module to 3.4.0
- add opencv-lib_suffix.patch, remove LIB_SUFFIX
from OPENCV_LIB_INSTALL_PATH, as CMAKE_INSTALL
_LIBDIR is arch dependent.
- Add option to build without openblas
- Add conditionals for python2 and python3 to allow us enabling
only desired python variants when needed
- Do not depend on sphinx as py2 and py3 seem to collide there
- Readd opencv-gles.patch, it is *not* included upstream; otherwise
build breaks on all GLES Qt5 platforms (armv6l, armv7l, aarch64)
- add fix_processor_detection_for_32bit_on_64bit.patch
- Correctly set optimizations and dynamic dispatch on ARM, use
OpenCV 3.3 syntax on x86.
- Update licensing information
- change requires of python-numpy-devel to build in Leap and
to not break factory in future
- fix build error/unresolvable for Leap 42.2 and 42.3
- Update to version 3.3.1:
* Lots of various bugfixes
- Update source url
- Rename python subpackage to python2
- Do not explicitly require python-base for python subpackages
- Update to 3.3
- Dropped obsolete patches
* opencv-gcc6-fix-pch-support-PR8345.patch
* opencv-gles.patch
- Updated opencv-build-compare.patch
- Add 0001-Do-not-include-glx.h-when-using-GLES.patch
Fix build for 32bit ARM, including both GLES and desktop GL headers
causes incompatible pointer type errors
- Add conditional for the qt5/qt4 integration
* This is used only for gui tools, library is not affected
- Add provides/obsoletes for the qt5 packages to allow migration
- Drop patch opencv-qt5-sobump.diff
* Used only by the obsoleted qt5 variant
- Cleanup a bit with spec-cleaner
- Use %cmake macros
- Remove the conditions that are not really needed
- Add tests conditional disabled by default
* Many tests fail and there are missing testdata
- Switch to pkgconfig style dependencies
- Update to OpenCV 3.2.0
- Results from 11 GSoC 2016 projects have been submitted to the library:
+ sinusoidal patterns for structured light and phase unwrapping module
[Ambroise Moreau (Delia Passalacqua)]
+ DIS optical flow (excellent dense optical flow algorithm that is both
significantly better and significantly faster than Farneback’s algorithm –
our baseline), and learning-based color constancy algorithms implementation
[Alexander Bokov (Maksim Shabunin)]
+ CNN based tracking algorithm (GOTURN) [Tyan Vladimir (Antonella Cascitelli)]
+ PCAFlow and Global Patch Collider algorithms implementation
[Vladislav Samsonov (Ethan Rublee)]
+ Multi-language OpenCV Tutorials in Python, C++ and Java
[João Cartucho (Vincent Rabaud)]
+ New camera model and parallel processing for stitching pipeline
[Jiri Horner (Bo Li)]
+ Optimizations and improvements of dnn module
[Vitaliy Lyudvichenko (Anatoly Baksheev)]
+ Base64 and JSON support for file storage. Use names like
“myfilestorage.xml?base64” when writing file storage to store big chunks of
numerical data in base64-encoded form. [Iric Wu (Vadim Pisarevsky)]
+ tiny_dnn improvements and integration
[Edgar Riba (Manuele Tamburrano, Stefano Fabri)]
+ Quantization and semantic saliency detection with tiny_dnn
[Yida Wang (Manuele Tamburrano, Stefano Fabri)]
+ Word-spotting CNN based algorithm
[Anguelos Nicolaou (Lluis Gomez)]
- Contributions besides GSoC:
+ Greatly improved and accelerated dnn module in opencv_contrib:
- Many new layers, including deconvolution, LSTM etc.
- Support for semantic segmentation and SSD networks with samples.
- TensorFlow importer + sample that runs Inception net by Google.
+ More image formats and camera backends supported
+ Interactive camera calibration app
+ Multiple algorithms implemented in opencv_contrib
+ Supported latest OSes, including Ubuntu 16.04 LTS and OSX 10.12
+ Lot’s of optimizations for IA and ARM archs using parallelism, vector
instructions and new OpenCL kernels.
+ OpenCV now can use vendor-provided OpenVX and LAPACK/BLAS (including Intel MKL,
Apple’s Accelerate, OpenBLAS and Atlas) for acceleration
- Refreshed opencv-build-compare.patch
- Dropped upstream opencv-gcc5.patch
- Replace opencv-gcc6-disable-pch.patch with upstream patch
opencv-gcc6-fix-pch-support-PR8345.patch
- Enable TBB support (C++ threading library)
- Add dependency on openBLAS
- Enable ffmpeg support unconditional
- In case we build using GCC6 (or newer), add -mlra to CFLAGS to
workaround gcc bug
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=71294.
- Apply upstream patch opencv-gcc6-disable-pch.patch to disable
PCH for GCC6.
- Test for python versions greater than or equal to the current
version.
- Add python 3 support
- Added opencv_contrib_face-3.1.0.tar.bz2
* This tarball is created to take only the face module from the
contrib package. The Face module is required by libkface, which
in its turn is required by digikam.
- Added _constraints file to avoid random failures on small workers
(at least for builds on PMBS)
- Update to OpenCV 3.1.0
- A lot of new functionality has been introduced during Google
Summer of Code 2015:
+ “Omnidirectional Cameras Calibration and Stereo 3D
Reconstruction” – opencv_contrib/ccalib module
(Baisheng Lai, Bo Li)
+ “Structure From Motion” – opencv_contrib/sfm module
(Edgar Riba, Vincent Rabaud)
+ “Improved Deformable Part-based Models” – opencv_contrib/dpm
module (Jiaolong Xu, Bence Magyar)
+ “Real-time Multi-object Tracking using Kernelized Correlation
Filter” – opencv_contrib/tracking module
(Laksono Kurnianggoro, Fernando J. Iglesias Garcia)
+ “Improved and expanded Scene Text Detection” –
opencv_contrib/text module (Lluis Gomez, Vadim Pisarevsky)
+ “Stereo correspondence improvements” – opencv_contrib/stereo
module (Mircea Paul Muresan, Sergei Nosov)
+ “Structured-Light System Calibration” –
opencv_contrib/structured_light (Roberta Ravanelli,
Delia Passalacqua, Stefano Fabri, Claudia Rapuano)
+ “Chessboard+ArUco for camera calibration” –
opencv_contrib/aruco (Sergio Garrido, Prasanna, Gary Bradski)
+ “Implementation of universal interface for deep neural
network frameworks” – opencv_contrib/dnn module
(Vitaliy Lyudvichenko, Anatoly Baksheev)
+ “Recent advances in edge-aware filtering, improved SGBM
stereo algorithm” – opencv/calib3d and opencv_contrib/ximgproc
(Alexander Bokov, Maksim Shabunin)
+ “Improved ICF detector, waldboost implementation” –
opencv_contrib/xobjdetect (Vlad Shakhuro, Alexander Bovyrin)
+ “Multi-target TLD tracking” – opencv_contrib/tracking module
(Vladimir Tyan, Antonella Cascitelli)
+ “3D pose estimation using CNNs” – opencv_contrib/cnn_3dobj
(Yida Wang, Manuele Tamburrano, Stefano Fabri)
- Many great contributions made by the community, such as:
+ Support for HDF5 format
+ New/Improved optical flow algorithms
+ Multiple new image processing algorithms for filtering,
segmentation and feature detection
+ Superpixel segmentation and much more
- IPPICV is now based on IPP 9.0.1, which should make OpenCV
even faster on modern Intel chips
- opencv_contrib modules can now be included into the
opencv2.framework for iOS
- Newest operating systems are supported: Windows 10 and
OSX 10.11 (Visual Studio 2015 and XCode 7.1.1)
- Interoperability between T-API and OpenCL, OpenGL, DirectX and
Video Acceleration API on Linux, as well as Android 5 camera.
- HAL (Hardware Acceleration Layer) module functionality has been
moved into corresponding basic modules; the HAL replacement
mechanism has been implemented along with the examples
- Removed improve-sphinx-search.diff, opencv-altivec-vector.patch,
opencv-pkgconfig.patch and opencv-samples.patch, fixed upstream.
- Fixed opencv-qt5-sobump.diff, opencv-build-compare.patch,
opencv-gcc5.patch and opencv-gles.patch.
- Version OpenCV 3.0.0
+ ~1500 patches, submitted as PR @ github. All our patches go
the same route.
+ opencv_contrib (http://github.com/itseez/opencv_contrib)
repository has been added. A lot of new functionality is there
already! opencv_contrib is only compatible with 3.0/master,
not 2.4. Clone the repository and use “cmake …
-D OPENCV_EXTRA_MODULES_PATH=<path_to opencv_contrib/modules> …”
to build opencv and opencv_contrib together.
+ a subset of Intel IPP (IPPCV) is given to us and our users free
of charge, free of licensing fees, for commercial and
non-commerical use. It’s used by default in x86 and x64 builds
on Windows, Linux and Mac.
+ T-API (transparent API) has been introduced, this is transparent
GPU acceleration layer using OpenCL. It does not add any
compile-time or runtime dependency of OpenCL. When OpenCL is
available, it’s detected and used, but it can be disabled at
compile time or at runtime. It covers ~100 OpenCV functions.
This work has been done by contract and with generous support
from AMD and Intel companies.
+ ~40 OpenCV functions have been accelerated using NEON intrinsics
and because these are mostly basic functions, some higher-level
functions got accelerated as well.
+ There is also new OpenCV HAL layer that will simplifies creation
of NEON-optimized code and that should form a base for the
open-source and proprietary OpenCV accelerators.
+ The documentation is now in Doxygen: http://docs.opencv.org/master/
+ We cleaned up API of many high-level algorithms from features2d,
calib3d, objdetect etc. They now follow the uniform
“abstract interface – hidden implementation” pattern and make
extensive use of smart pointers (Ptr<>).
+ Greatly improved and extended Python & Java bindings (also,
see below on the Python bindings), newly introduced Matlab
bindings (still in alpha stage).
+ Improved Android support – now OpenCV Manager is in Java and
supports both 2.4 and 3.0.
+ Greatly improved WinRT support, including video capturing and
multi-threading capabilities. Thanks for Microsoft team for this!
+ Big thanks to Google who funded several successive GSoC programs
and let OpenCV in. The results of many successful GSoC 2013 and
2014 projects have been integrated in opencv 3.0 and
opencv_contrib (earlier results are also available in
OpenCV 2.4.x). We can name:
- text detection
- many computational photography algorithms (HDR, inpainting,
edge-aware filters, superpixels, …)
- tracking and optical flow algorithms
- new features, including line descriptors, KAZE/AKAZE
- general use optimization (hill climbing, linear programming)
- greatly improved Python support, including Python 3.0 support,
many new tutorials & samples on how to use OpenCV with Python.
- 2d shape matching module and 3d surface matching module
- RGB-D module
- VTK-based 3D visualization module
- etc.
+ Besides Google, we enjoyed (and hope that you will enjoy too)
many useful contributions from community, like:
- biologically inspired vision module
- DAISY features, LATCH descriptor, improved BRIEF
- image registration module
- etc.
- Reduce build-compare noise
opencv-build-compare.patch
- Remove BuildRequirement for python-sphinx in SLE12, since it's
not available there and it's not a mandatory requirement.
- Reduce differences between two spec files
- Use pkgconfig for ffmpeg BuildRequires
- Update improve-sphinx-search.diff for new python-Sphinx(1.3.1)
* now that sphinx-build disallow executing without arguments and
give you "Insufficient arguments" error, use "sphinx-build -h"
instead
* the default usages output ie. sphinx-build(or --help) no longer
are standard error but standard output, drop OUTPUT_QUIET and
add OUTPUT_VARIABLE throws the output to SPHINX_OUTPUT as well
- support gcc 5 (i.e. gcc versions without minor version):
opencv-gcc5.patch
- Update to OpenCV 2.4.11 - can't find NEWS or Changelog
merely collecting bug fixes while 3.0 is in the making, 2.4.11
didn't even make it on their web page, it's only on download
server
- remove opencv-underlinking.patch as obsolete
- remove upstream patch bomb_commit_gstreamer-1x-support.patch
- commenting out opencv-pkgconfig.patch - possibly it requires a rebase,
but the problem it tries to solve is unclear
- Add specific buildrequires for libpng15, so that we are
building against the system provided libpng.
- Update to OpenCV 2.4.9
More info at:
http://opencv.org/opencv-2-4-9-is-out.html
The brief list of changes:
* new 3D visualization module ‘viz’;
* performance fixes in ‘ocl’ module;
* fixes in Android Camera;
* improved CUDA support for mobile platforms;
* bugfixes from community;
* 55 reported bugs have been closed;
* 156 pull requests have been merged.
- Drop the BuildRequires on libucil and libunicap for Factory. This
stops us from getting ride of Gstreamer 0.10 and besides these two
libraries seem to be unmaintained upstream as that the latest
actions are from 2010
- Add upstream patch (3.0 version) to support Gstreamer 1.x
* bomb_commit_gstreamer-1x-support.patch
- Upstream now provides tarballs with source only as git tags
from github so update Source0 path.
- Add requires on various X extensions linked to opencv_ts module.
As those are present in the .pc file we need it anyway.
- Update to OpenCV 2.4.8
More info at:
http://opencv.org/opencv-2-4-8.html
The brief list of changes:
* NVidia CUDA support on Android devices with CUDA capable SoC and
CUDA sample;
* Concurrent kernel execution and user defined context support for
OpenCL;
* Integration with Intel Perceptual SDK and new depth sensors support
for Windows;
* 32 reported bugs have been closed;
* 139 pull requests have been merged;
- Fix build with altivec:
opencv-altivec-vector.patch
- Added opencv-pkgconfig.patch: make sure to provide link flags in
OpenCV pc file (bnc#853036)
- Update to OpenCV 2.4.7
More info at:
http://opencv.org/opencv-2-4-7-is-out.html
The brief list of changes:
* dynamic OpenCL runtime loading, setting default OpenCL device
via env var, many bug-fixes and some new optimization with OpenCL
* bug-fixes and new optimizations in CUDA stuff
* latest NDK and Android OS support, Native Android Camera tuning
* minor fixes, XAML sample and MS Certification compatibility
in WinRT stuff
* 382 pull requests have been merged
* 54 reported bugs have been fixed
- Added pkgconfig(glu) Requires to devel package, as per .pc file
- Make devel package provides also devel-static one
- Drop assume-Sphinx-is-there.diff, and add improve-sphinx-search.diff,
for properly finding sphinx with alphabetic chars in version
- Add patch assume-Sphinx-is-there.diff to fix building with
Sphinx versions that have alphanumeric characters in the version
(Only for factory builds at the moment)
- Use eigen3 instead of eigen2 as build requirement for openSUSE > 12.3.
- Enable compilation with libucil and libunicap.
- Removed dos2unix build requirement (not needed anymore).
- Update to OpenCV 2.4.6.1
More info at:
http://opencv.org/opencv-2-4-6-is-out.html
The brief list of changes:
* added video file i/o Windows RT and sample application using
camera, enabled parallelization with TBB or MS Concurrency
* added CUDA 5.5 support for desktop and ARM systems
* added Qt 5 support
* added many new OpenCL algorithms ports, included OpenCL binaries
into the Windows superpack
* iOS build scripts (together with Android ones) moved to
‘opencv/platforms’ directory
* added functions for UIImage <-> cv::Mat conversion
* correct front/back camera selection in Android app framework
* added Linaro NDK support and fixes for MIPS to Android CMake
toolchain
* stability has been improved by a lot, numerous bug-fixes across
all the library
- build with LFS_CFLAGS in 32 bit archs.
- Disable SSE3 for all architectures (bnc#814333)
- Disable SSE(2) on non x86_64 architectures, causes crashing
kde#276923, bnc#789173
- Update to OpenCV 2.4.5
More info at:
http://opencv.org/opencv-2-4-5-is-out.html
The brief list of changes:
* experimental WinRT support
* new video super-resolution module
* CLAHE (adaptive histogram equalization) algorithm on both CPU
and GPU
* further improvements and extensions in ocl module
(stereo block matching and belief propagation have been added,
fixed crashes on Intel HD4000)
* Visual Studio 2012 cv::Mat visualizer plugin debugger tutorial
from Microsoft Research
* OpenCV4Android SDK improvements
(NDK r8e support, native activity sample using OpenCV Manager,
bug-fixes)
* ~25 reported problems have been resolved since 2.4.4, ~78 pull
requests have been merged, thanks everybody who participated!
- Update to OpenCV 2.4.4
More info at:
http://opencv.org/opencv-2-4-4-is-out.html
The brief list of changes:
* OpenCV Java bindings are ported from Android to desktop Java!
Actually any JVM language will work, see Tutorial for details,
and Java or Scala code samples.
* Android application framework, samples, tutorials, and OpenCV
Manager are improved.
* Optimizations for the new NVIDIA Kepler architecture, CARMA
platform support and other new optimizations in CUDA.
* OpenCL module now builds successfully with various SDKs (from
AMD, NVIDIA, Intel and Apple) and runs well on different GPUs
(AMD, NVidia, Intel HD4000). A lot of new functionality has been
added, tons of bugs fixed, performance of many functions has
been significantly improved.
* 100+ reported problems have been resolved since 2.4.3, thanks
everybody who participated!
- Drop the buildrequire for libxine
- Update to OpenCV 2.4.3
More info at:
http://opencv.org/opencv-2-4-3-released.html
The nicely formatted changelog can be seen here:
http://code.opencv.org/projects/opencv/wiki/ChangeLog;
here are the highlights:
* A lot of good stuff from the Google Summer of Code 2012 has been
integrated; this was a very productive summer!
* Significantly improved and optimized Android and iOS ports.
* Greatly extended GPU (i.e. CUDA-based) module.
* The brand new ocl (OpenCL-based) module that unleashes GPU power
also for AMD and Intel GPU users. It’s not included into the
binary package, since there are different SDKs, and it’s not
turned on by default. You need to run CMake and turn on
“WITH_OPENCL”. Also, please note that this is very first version
of the module, so it may be not very stable and not very
functional.
* Much better performance on many-core systems out of the box. You
do not need TBB anymore on MacOSX, iOS and Windows. BTW, the
binary package for Windows is now built without TBB support.
Libraries and DLLs for Visual Studio 2010 use the Concurrency
framework.
* About 130 bugs have been fixed since 2.4.2.
* Since 2.4.3rc we fixed several more problems, in particular some
compile problems with iOS 6 SDK.
- buildrequire glu
- Update to OpenCV 2.4.2
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Drop opencv-datadir.patch to comply with upstream directory layout
- Update to OpenCV 2.4.1
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Update to OpenCV 2.4.0
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Add opencv-gcc47.patch: Fix build with gcc 4.7.
- Use Explicit Buildrequires on several needed libraries
future dependency cleanups may/will cause build to fail otherwise.
- Add upstream r6881 to fix clang compatibility
- uncomment libraries not in 12.1 for now
- Changed groups (fix for RPMLINT warning)
- Added check for duplicate files (fix for RPMLINT warning)
- Added py_requires macros and python-base dependencies (fix for RPMLINT warning)
- Escaped macros (fix for RPMLINT warning)
- Fixed end-of-line encoding problems (fix for RPMLINT warning)
- Added libeigen2-devel buildrequires
- Added libunicap and libucil buildrequires (libunicap supports requires libucil)
- Cleaned up spec file formatting
- Dropped opencv-2.3-ffmpeg.patch, applied upstream
- Revive opencv-2.3-ffmpeg.patch, needs rebase
- Tag all patches according to openSUSE packaging guidelines
- Removed opencv-2.3-cmake.patch, old cmake cannot be used any more.
- Python bindings cannot be built without NumPy any more.
- Update to OpenCV 2.3.1
- Update and readd opencv-2.3-underlinking.patch since it is still
necessary.
- Fix support for new ffmpeg versions
- Removed unnecessary patches
- Enable Python NumPy support on openSUSE 11.2
- Build Qt instead of Gtk GUI
- Fix cmake files for openSUSE 11.1
- No GStreamer support on openSUSE 11.1
- Update to OpenCV 2.3.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Fix build on openSUSE 11.2
- Add opencv-v4l-2.6.38.patch: use the new libv4l2 interface
- Enable Python NumPy support
- SWIG is not required any more
- Enable OpenEXR support
- Update to OpenCV 2.2.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Use system zlib, oh, and do not export ZLIB symbols to
other applications, clashes ensued.
- fix build with gcc 4.6
- add -underlinking patch
- devel package renamed to opencv-devel, so that switching between
OBS and packman opencv packages is easier
- fix gstreamer support
- fix xine support
- fix some rpmlint warnings
- fix shared libraries permissions
- Do not waste resources building the tests as we do not run them
- Do not disable SSE,SSE2,etc. According to OpenCV changelog,
it should be safe to leave these enabled.
- fix build on openSUSE 11.0
- Update to OpenCV 2.1.0:
* The whole OpenCV is now using exceptions instead of the old
libc-style mechanism
* Experimental "static" OpenCV configuration in CMake was
contributed by Jose Luis Blanco.
Pass "BUILD_SHARED_LIBS=OFF" to CMake to build OpenCV statically.
* new improved version of one-way descriptor is added
* User can now control the image areas visible after the stereo
rectification
* Fullscreen has been added (thanks to Yannick Verdie).
* Further info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- fix build with libpng14
- small spec file cleanup
- Moved to the KDE repositories to enable inclusion in kipi-plugins
- Initial package
OBS-URL: https://build.opensuse.org/request/show/714221
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/opencv?expand=0&rev=73
2019-07-17 13:13:58 +02:00
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2024-02-05 08:31:49 +01:00
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%else
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-DBUILD_opencv_python3=OFF \
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%endif
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-DPYTHON_DEFAULT_EXECUTABLE=%{_bindir}/python3 \
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Accepting request 814492 from home:StefanBruens:branches:science
- Update to 4.3.0
* DNN module:
+ Improved layers / activations / supported more models:
- ONNX: LSTM, Broadcasting, Algebra over constants, Slice with
multiple inputs
- DarkNet: grouped convolutions, sigmoid, swish, scale_channels
- MobileNet-SSD v3: #16760
+ New samples / demos:
- Clothes parts segmentation and CP-VTON
- DaSiamRPN tracker
Intel® Inference Engine backend (OpenVINO™):
- added support for custom layers through nGraph OpenVINO
API: #16628
- nGraph OpenVINO API is used by default: #16746
+ Many fixes and optimizations in CUDA backend (thanks to
@YashasSamaga)
+ OPEN AI LAB team submitted the patch that accelerates OpenCV
DNN on ARM using their Tengine library
* G-API module:
+ Introduced a new graph-level data type GOpaque<T>. This type
can be used to pass arbitrary user data types between G-API
nodes in the graph (supported for CPU/OpenCV backend only).
+ Introduced a way to declare G-API CPU (OpenCV) kernels in-place
+ Added a new sample "Privacy masking camera", combining Deep
Learning with traditional Image Processing (link)
+ Added more operations in the default library: WarpAffine,
WarpPerspective, NV12toGray.
* Performance improvements:
+ IPP-ICV library with CPU optimizations has been updated to
version 2020.0.0 Gold
+ SIMD intrinsics: integral, resize, (opencv_contrib) RLOF
implementation #2476
* And many other great contributions from OpenCV community:
+ (opencv_contrib) Computer Vision based Alpha Matting
(GSoC 2019) #2306
+ calib3d: findChessboardCornersSB improvements: #16625
+ calib3d: updated documentation for RT matrices: #16860
+ core: improved getNumberOfCPUs(): #16268
+ imgproc: new algorithm HOUGH_GRADIENT_ALT is added to
HoughCircles() function #16561. It has much better recall
and precision
+ imgcodecs: added initial support for OpenJPEG library
(version 2+): #16494
+ highgui(Qt): added Copy to clipboard: #16677
+ dnn: TensorFlow, Darknet and ONNX importers improvements
by @ashishkrshrivastava
+ (opencv_contrib) added rapid module for silhouette based 3D
object tracking: #2356
+ (opencv_contrib) SIFT detector is enabled by default due
patents expiration (without requirement of NONFREE build
option)
+ help materials: OpenCV Cheat Sheet in Python: #4875
* Changes that can potentially break compatibility:
+ image filtering functions throws exception on empty input
(voting results)
- Packaging changes:
* Stop mangling CMake diagnostic output, no dependency versions
end up in the packages anyway, drop opencv-build-compare.patch
* Set empty OPENCV_DOWNLOAD_TRIES_LIST, skip downloads even when
network is available during builds (e.g. local build).
* Drop upstream GLES patches:
+ 0001-Do-not-include-glx.h-when-using-GLES.patch
+ opencv-gles.patch
OBS-URL: https://build.opensuse.org/request/show/814492
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=15
2020-06-14 22:35:02 +02:00
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-DOPENCV_DOWNLOAD_TRIES_LIST:STRING="" \
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2020-01-28 12:15:26 +01:00
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-DWITH_JASPER=OFF \
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Accepting request 860308 from home:StefanBruens:branches:science
- update to 4.5.1, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version451
* Continued merging of GSoC 2020 results:
+ Develop OpenCV.js DNN modules for promising web use cases
together with their tutorials
+ OpenCV.js: WASM SIMD optimization 2.0
+ High Level API and Samples for Scene Text Detection and
Recognition
+ SIFT: SIMD optimization of GaussianBlur 16U
* DNN module:
+ Improved layers / activations / supported more models:
- optimized: 1D convolution, 1D pool
- fixed: Resize, ReduceMean, Gather with multiple outputs,
importing of Faster RCNN ONNX model
- added support: INT32 ONNX tensors
+ Intel® Inference Engine backend (OpenVINO):
- added support for OpenVINO 2021.2 release
- added preview support for HDDL
+ Fixes and optimizations in DNN CUDA backend (thanks to
@YashasSamaga)
* G-API Framework:
+ Introduced serialization for cv::RMat, including
serialization for user-defined memory adapters
+ Introduced desync, a new Operation for in-graph asynchronous
execution - to allow different parts of the graph run with
a different latency
+ Introduced a notion of "in-graph metadata", now various
media-related information can be accessed in graph directly
(currently only limited to timestamps and frame IDs)
+ Introduced a new generic task-based executor, based on
Threading Building Blocks (TBB)
+ Extended infer<>() API to accept a new cv::GFrame data
structure to allow handling of various media formats without
changes in the graph structure
+ Made copy() an intrinsic where real copy may not happen
(optimized out) based on graph structure, extended it to
support cv::GFrame
+ Various fixes, including addressig static analysis,
documentation, and test issues
* G-API Operations:
+ Introduced new operations morphologyEx, boundingRect,
fitLine, kmeans, Background Subtractor, Kalman filter
* G-API Intel® Inference Engine backend (OpenVINO):
+ Extended cv::gapi::ie::Params<> to import CNN networks (e.g.
pre-compiled ones) instead of passing .XML and .BIN files;
also enabled configuring Inference Engine plugins via
this structure
+ Added a new overload to infer<>() to run inference over a
single region of interest
+ Added support for cv::MediaFrame input data type (projected
from cv::GFrame) and handling for NV12 input image format
* G-API Python bindings:
+ Exposed G-API's Inference and Streaming APIs in the OpenCV
Python bindings
+ Added initial Python support for cv::GArray data structure
* Significant progress on RISC-V port.
- Updated constraints, bump memory to 5 GB
- Cleaned up spec file
OBS-URL: https://build.opensuse.org/request/show/860308
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=23
2021-01-04 20:56:22 +01:00
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%{nil}
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2017-12-03 10:10:30 +01:00
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2020-11-03 06:17:42 +01:00
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%cmake_build
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2024-02-05 08:31:49 +01:00
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popd
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%if %{with python3}
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mkdir pythonbuilds
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pushd pythonbuilds
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%define __sourcedir ../modules/python
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%{python_expand # Build all non-primary flavors (if any) "standalone".
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# cmake takes most of the config defined from
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# $(OpenCV_BINARY_DIR)/opencv_python_config.cmake written during the main build.
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if [ "py%{$python_version}" != "py%{python3_version}" ]; then
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pushd $PWD
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%cmake \
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-DOpenCV_BINARY_DIR=../../build/ \
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-DOPENCV_SKIP_PYTHON_LOADER=ON \
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-DOPENCV_PYTHON_VERSION=%{$python_version} \
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-DOPENCV_PYTHON_STANDALONE_INSTALL_PATH=%{$python_sitearch} \
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%{nil}
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%cmake_build
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popd
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fi
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}
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%endif
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2010-03-08 18:16:50 +01:00
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%install
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2017-07-11 08:24:11 +02:00
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%cmake_install
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2024-02-05 08:31:49 +01:00
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%if %{with python3}
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pushd pythonbuilds
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%{python_expand #
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if [ "py%{$python_version}" != "py%{python3_version}" ]; then
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%cmake_install
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fi
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}
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popd
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%endif
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2015-12-27 01:59:41 +01:00
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mkdir -p %{buildroot}%{_docdir}/%{name}-doc
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Accepting request 714221 from science
- Update to version 4.1.0
* DNN module:
+ Reduced peak memory consumption for some models up to 30%.
+ Inference Engine
- Inference Engine 2018R3 is now a minimal supported version of IE.
- Myriad X (Intel® Neural Compute Stick 2) is now supported and tested.
- Automatic IR network reshaping for different inputs.
- Improved samples to work with models from OpenVINO Open Model Zoo
+ New networks from TensorFlow Object Detection API: Faster-RCNNs, SSDs
and Mask-RCNN with dilated convolutions, FPN SSD
* Performance improvements:
+ More optimization using AVX2 instruction set.
+ Automatic runtime dispatching is available for large set of functions
from core and imgproc modules.
* Other improvements:
+ Matplotlib Perceptually Uniform Sequential colormaps
+ Add keypoints matching visualization for real-time pose estimation tutorial
+ Add Hand-Eye calibration methods
+ Java: improved support for multidimensional arrays (Mat)
+ Dynamically loaded videoio backends (FFmpeg, GStreamer)
+ opencv_contrib: Robust local optical flow (RLOF) implementations
+ opencv_contrib: Implementation of Quasi Dense Stereo algorithm
+ opencv_contrib: New module: Image Quality Analysis (IQA) API
+ opencv_contrib: BRISQUE No Reference Image Quality Assessment (IQA) API
Check https://github.com/opencv/opencv/wiki/ChangeLog#version410
- Update to version 4.0.0
* A lot of C API from OpenCV 1.x has been removed. The affected modules are
objdetect, photo, video, videoio, imgcodecs, calib3d.
* Persistence (storing and loading structured data to/from XML, YAML or JSON)
in the core module has been completely reimplemented.
* OpenCV is now C++11 library and requires C++11-compliant compiler.
Thanks to the extended C++11 standard library, we could get rid of hand-crafted
cv::String and cv::Ptr. Now cv::String == std::string and cv::Ptr is a thin
wrapper on top of std::shared_ptr. Also, on Linux/BSD for cv::parallel_for_
we now use std::thread's instead of pthreads.
* DNN improvements
* Completely new module opencv_gapi has been added. It is the engine for very
efficient image processing, based on lazy evaluation and on-fly construction.
* Performance improvements
A few hundreds of basic kernels in OpenCV have been rewritten using so-called
"wide universal intrinsics". Those intrinsics map to SSE2, SSE4, AVX2, NEON or
VSX intrinsics, depending on the target platform and the compile flags.
* QR code detector and decoder have been added to opencv/objdetect module.
* The popular Kinect Fusion algorithm has been implemented, optimized for CPU and
GPU (OpenCL), and integrated into opencv_contrib/rgbd module.
* Very efficient and yet high-quality DIS dense optical flow algorithm has been
moved from opencv_contrib to opencv, video module. See the example.
* The slower TV L1 optical flow algorithm has been moved to opencv_contrib.
Check https://github.com/opencv/opencv/wiki/ChangeLog#version400
- Drop obsolete opencv-lib_suffix.patch
- Add 0001-Handle-absolute-OPENCV_INCLUDE_INSTALL_PATH-correctl.patch
- As this is a major version upgrade, the old 3.4.x package is still
available as opencv3
- Update to 3.4.3
* Compatibility fixes with python 3.7
* Added a new computational target DNN_TARGET_OPENCL_FP16
* Extended support of Intel's Inference Engine backend
* Enabled import of Intel's OpenVINO pre-trained networks from
intermediate representation (IR).
* tutorials improvements
Check https://github.com/opencv/opencv/wiki/ChangeLog#version343
for the complete changelog.
- Drop fix-build-i386-nosse.patch, build-workaround-issues-with-c.patch
(fixed upstream)
- Refresh patches
- Add patch to fix use of headers from C:
* build-workaround-issues-with-c.patch
- Update to 3.4.1:
* Added support for quantized TensorFlow networks
* OpenCV is now able to use Intel DL inference engine as DNN
acceleration backend
* Added AVX-512 acceleration to the performance-critical kernels
* For more information, read
https://github.com/opencv/opencv/wiki/ChangeLog#version341
- Update contrib modules to 3.4.1:
* No changelog available
- Change mechanism the contrib modules are built
- Include LICENSE of contrib tarball as well
- Build with python3 on >= 15
- Add patch to fix build on i386 without SSE:
* fix-build-i386-nosse.patch
- Refresh patches:
* fix_processor_detection_for_32bit_on_64bit.patch
* opencv-build-compare.patch
- Mention all libs explicitly
- Rebase 3.4.0 update from i@marguerite.su
- update to 3.4.0
* Added faster R-CNN support
* Javascript bindings have been extended to
cover DNN module
* DNN has been further accelerated for iGPU
using OpenCL
* On-disk caching of precompiled OpenCL
kernels has been finally implemented
* possible to load and run pre-compiled
OpenCL kernels via T-API
* Bit-exact 8-bit and 16-bit resize has been
implemented (currently supported only
bilinear interpolation)
- update face module to 3.4.0
- add opencv-lib_suffix.patch, remove LIB_SUFFIX
from OPENCV_LIB_INSTALL_PATH, as CMAKE_INSTALL
_LIBDIR is arch dependent.
- Add option to build without openblas
- Add conditionals for python2 and python3 to allow us enabling
only desired python variants when needed
- Do not depend on sphinx as py2 and py3 seem to collide there
- Readd opencv-gles.patch, it is *not* included upstream; otherwise
build breaks on all GLES Qt5 platforms (armv6l, armv7l, aarch64)
- add fix_processor_detection_for_32bit_on_64bit.patch
- Correctly set optimizations and dynamic dispatch on ARM, use
OpenCV 3.3 syntax on x86.
- Update licensing information
- change requires of python-numpy-devel to build in Leap and
to not break factory in future
- fix build error/unresolvable for Leap 42.2 and 42.3
- Update to version 3.3.1:
* Lots of various bugfixes
- Update source url
- Rename python subpackage to python2
- Do not explicitly require python-base for python subpackages
- Update to 3.3
- Dropped obsolete patches
* opencv-gcc6-fix-pch-support-PR8345.patch
* opencv-gles.patch
- Updated opencv-build-compare.patch
- Add 0001-Do-not-include-glx.h-when-using-GLES.patch
Fix build for 32bit ARM, including both GLES and desktop GL headers
causes incompatible pointer type errors
- Add conditional for the qt5/qt4 integration
* This is used only for gui tools, library is not affected
- Add provides/obsoletes for the qt5 packages to allow migration
- Drop patch opencv-qt5-sobump.diff
* Used only by the obsoleted qt5 variant
- Cleanup a bit with spec-cleaner
- Use %cmake macros
- Remove the conditions that are not really needed
- Add tests conditional disabled by default
* Many tests fail and there are missing testdata
- Switch to pkgconfig style dependencies
- Update to OpenCV 3.2.0
- Results from 11 GSoC 2016 projects have been submitted to the library:
+ sinusoidal patterns for structured light and phase unwrapping module
[Ambroise Moreau (Delia Passalacqua)]
+ DIS optical flow (excellent dense optical flow algorithm that is both
significantly better and significantly faster than Farneback’s algorithm –
our baseline), and learning-based color constancy algorithms implementation
[Alexander Bokov (Maksim Shabunin)]
+ CNN based tracking algorithm (GOTURN) [Tyan Vladimir (Antonella Cascitelli)]
+ PCAFlow and Global Patch Collider algorithms implementation
[Vladislav Samsonov (Ethan Rublee)]
+ Multi-language OpenCV Tutorials in Python, C++ and Java
[João Cartucho (Vincent Rabaud)]
+ New camera model and parallel processing for stitching pipeline
[Jiri Horner (Bo Li)]
+ Optimizations and improvements of dnn module
[Vitaliy Lyudvichenko (Anatoly Baksheev)]
+ Base64 and JSON support for file storage. Use names like
“myfilestorage.xml?base64” when writing file storage to store big chunks of
numerical data in base64-encoded form. [Iric Wu (Vadim Pisarevsky)]
+ tiny_dnn improvements and integration
[Edgar Riba (Manuele Tamburrano, Stefano Fabri)]
+ Quantization and semantic saliency detection with tiny_dnn
[Yida Wang (Manuele Tamburrano, Stefano Fabri)]
+ Word-spotting CNN based algorithm
[Anguelos Nicolaou (Lluis Gomez)]
- Contributions besides GSoC:
+ Greatly improved and accelerated dnn module in opencv_contrib:
- Many new layers, including deconvolution, LSTM etc.
- Support for semantic segmentation and SSD networks with samples.
- TensorFlow importer + sample that runs Inception net by Google.
+ More image formats and camera backends supported
+ Interactive camera calibration app
+ Multiple algorithms implemented in opencv_contrib
+ Supported latest OSes, including Ubuntu 16.04 LTS and OSX 10.12
+ Lot’s of optimizations for IA and ARM archs using parallelism, vector
instructions and new OpenCL kernels.
+ OpenCV now can use vendor-provided OpenVX and LAPACK/BLAS (including Intel MKL,
Apple’s Accelerate, OpenBLAS and Atlas) for acceleration
- Refreshed opencv-build-compare.patch
- Dropped upstream opencv-gcc5.patch
- Replace opencv-gcc6-disable-pch.patch with upstream patch
opencv-gcc6-fix-pch-support-PR8345.patch
- Enable TBB support (C++ threading library)
- Add dependency on openBLAS
- Enable ffmpeg support unconditional
- In case we build using GCC6 (or newer), add -mlra to CFLAGS to
workaround gcc bug
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=71294.
- Apply upstream patch opencv-gcc6-disable-pch.patch to disable
PCH for GCC6.
- Test for python versions greater than or equal to the current
version.
- Add python 3 support
- Added opencv_contrib_face-3.1.0.tar.bz2
* This tarball is created to take only the face module from the
contrib package. The Face module is required by libkface, which
in its turn is required by digikam.
- Added _constraints file to avoid random failures on small workers
(at least for builds on PMBS)
- Update to OpenCV 3.1.0
- A lot of new functionality has been introduced during Google
Summer of Code 2015:
+ “Omnidirectional Cameras Calibration and Stereo 3D
Reconstruction” – opencv_contrib/ccalib module
(Baisheng Lai, Bo Li)
+ “Structure From Motion” – opencv_contrib/sfm module
(Edgar Riba, Vincent Rabaud)
+ “Improved Deformable Part-based Models” – opencv_contrib/dpm
module (Jiaolong Xu, Bence Magyar)
+ “Real-time Multi-object Tracking using Kernelized Correlation
Filter” – opencv_contrib/tracking module
(Laksono Kurnianggoro, Fernando J. Iglesias Garcia)
+ “Improved and expanded Scene Text Detection” –
opencv_contrib/text module (Lluis Gomez, Vadim Pisarevsky)
+ “Stereo correspondence improvements” – opencv_contrib/stereo
module (Mircea Paul Muresan, Sergei Nosov)
+ “Structured-Light System Calibration” –
opencv_contrib/structured_light (Roberta Ravanelli,
Delia Passalacqua, Stefano Fabri, Claudia Rapuano)
+ “Chessboard+ArUco for camera calibration” –
opencv_contrib/aruco (Sergio Garrido, Prasanna, Gary Bradski)
+ “Implementation of universal interface for deep neural
network frameworks” – opencv_contrib/dnn module
(Vitaliy Lyudvichenko, Anatoly Baksheev)
+ “Recent advances in edge-aware filtering, improved SGBM
stereo algorithm” – opencv/calib3d and opencv_contrib/ximgproc
(Alexander Bokov, Maksim Shabunin)
+ “Improved ICF detector, waldboost implementation” –
opencv_contrib/xobjdetect (Vlad Shakhuro, Alexander Bovyrin)
+ “Multi-target TLD tracking” – opencv_contrib/tracking module
(Vladimir Tyan, Antonella Cascitelli)
+ “3D pose estimation using CNNs” – opencv_contrib/cnn_3dobj
(Yida Wang, Manuele Tamburrano, Stefano Fabri)
- Many great contributions made by the community, such as:
+ Support for HDF5 format
+ New/Improved optical flow algorithms
+ Multiple new image processing algorithms for filtering,
segmentation and feature detection
+ Superpixel segmentation and much more
- IPPICV is now based on IPP 9.0.1, which should make OpenCV
even faster on modern Intel chips
- opencv_contrib modules can now be included into the
opencv2.framework for iOS
- Newest operating systems are supported: Windows 10 and
OSX 10.11 (Visual Studio 2015 and XCode 7.1.1)
- Interoperability between T-API and OpenCL, OpenGL, DirectX and
Video Acceleration API on Linux, as well as Android 5 camera.
- HAL (Hardware Acceleration Layer) module functionality has been
moved into corresponding basic modules; the HAL replacement
mechanism has been implemented along with the examples
- Removed improve-sphinx-search.diff, opencv-altivec-vector.patch,
opencv-pkgconfig.patch and opencv-samples.patch, fixed upstream.
- Fixed opencv-qt5-sobump.diff, opencv-build-compare.patch,
opencv-gcc5.patch and opencv-gles.patch.
- Version OpenCV 3.0.0
+ ~1500 patches, submitted as PR @ github. All our patches go
the same route.
+ opencv_contrib (http://github.com/itseez/opencv_contrib)
repository has been added. A lot of new functionality is there
already! opencv_contrib is only compatible with 3.0/master,
not 2.4. Clone the repository and use “cmake …
-D OPENCV_EXTRA_MODULES_PATH=<path_to opencv_contrib/modules> …”
to build opencv and opencv_contrib together.
+ a subset of Intel IPP (IPPCV) is given to us and our users free
of charge, free of licensing fees, for commercial and
non-commerical use. It’s used by default in x86 and x64 builds
on Windows, Linux and Mac.
+ T-API (transparent API) has been introduced, this is transparent
GPU acceleration layer using OpenCL. It does not add any
compile-time or runtime dependency of OpenCL. When OpenCL is
available, it’s detected and used, but it can be disabled at
compile time or at runtime. It covers ~100 OpenCV functions.
This work has been done by contract and with generous support
from AMD and Intel companies.
+ ~40 OpenCV functions have been accelerated using NEON intrinsics
and because these are mostly basic functions, some higher-level
functions got accelerated as well.
+ There is also new OpenCV HAL layer that will simplifies creation
of NEON-optimized code and that should form a base for the
open-source and proprietary OpenCV accelerators.
+ The documentation is now in Doxygen: http://docs.opencv.org/master/
+ We cleaned up API of many high-level algorithms from features2d,
calib3d, objdetect etc. They now follow the uniform
“abstract interface – hidden implementation” pattern and make
extensive use of smart pointers (Ptr<>).
+ Greatly improved and extended Python & Java bindings (also,
see below on the Python bindings), newly introduced Matlab
bindings (still in alpha stage).
+ Improved Android support – now OpenCV Manager is in Java and
supports both 2.4 and 3.0.
+ Greatly improved WinRT support, including video capturing and
multi-threading capabilities. Thanks for Microsoft team for this!
+ Big thanks to Google who funded several successive GSoC programs
and let OpenCV in. The results of many successful GSoC 2013 and
2014 projects have been integrated in opencv 3.0 and
opencv_contrib (earlier results are also available in
OpenCV 2.4.x). We can name:
- text detection
- many computational photography algorithms (HDR, inpainting,
edge-aware filters, superpixels, …)
- tracking and optical flow algorithms
- new features, including line descriptors, KAZE/AKAZE
- general use optimization (hill climbing, linear programming)
- greatly improved Python support, including Python 3.0 support,
many new tutorials & samples on how to use OpenCV with Python.
- 2d shape matching module and 3d surface matching module
- RGB-D module
- VTK-based 3D visualization module
- etc.
+ Besides Google, we enjoyed (and hope that you will enjoy too)
many useful contributions from community, like:
- biologically inspired vision module
- DAISY features, LATCH descriptor, improved BRIEF
- image registration module
- etc.
- Reduce build-compare noise
opencv-build-compare.patch
- Remove BuildRequirement for python-sphinx in SLE12, since it's
not available there and it's not a mandatory requirement.
- Reduce differences between two spec files
- Use pkgconfig for ffmpeg BuildRequires
- Update improve-sphinx-search.diff for new python-Sphinx(1.3.1)
* now that sphinx-build disallow executing without arguments and
give you "Insufficient arguments" error, use "sphinx-build -h"
instead
* the default usages output ie. sphinx-build(or --help) no longer
are standard error but standard output, drop OUTPUT_QUIET and
add OUTPUT_VARIABLE throws the output to SPHINX_OUTPUT as well
- support gcc 5 (i.e. gcc versions without minor version):
opencv-gcc5.patch
- Update to OpenCV 2.4.11 - can't find NEWS or Changelog
merely collecting bug fixes while 3.0 is in the making, 2.4.11
didn't even make it on their web page, it's only on download
server
- remove opencv-underlinking.patch as obsolete
- remove upstream patch bomb_commit_gstreamer-1x-support.patch
- commenting out opencv-pkgconfig.patch - possibly it requires a rebase,
but the problem it tries to solve is unclear
- Add specific buildrequires for libpng15, so that we are
building against the system provided libpng.
- Update to OpenCV 2.4.9
More info at:
http://opencv.org/opencv-2-4-9-is-out.html
The brief list of changes:
* new 3D visualization module ‘viz’;
* performance fixes in ‘ocl’ module;
* fixes in Android Camera;
* improved CUDA support for mobile platforms;
* bugfixes from community;
* 55 reported bugs have been closed;
* 156 pull requests have been merged.
- Drop the BuildRequires on libucil and libunicap for Factory. This
stops us from getting ride of Gstreamer 0.10 and besides these two
libraries seem to be unmaintained upstream as that the latest
actions are from 2010
- Add upstream patch (3.0 version) to support Gstreamer 1.x
* bomb_commit_gstreamer-1x-support.patch
- Upstream now provides tarballs with source only as git tags
from github so update Source0 path.
- Add requires on various X extensions linked to opencv_ts module.
As those are present in the .pc file we need it anyway.
- Update to OpenCV 2.4.8
More info at:
http://opencv.org/opencv-2-4-8.html
The brief list of changes:
* NVidia CUDA support on Android devices with CUDA capable SoC and
CUDA sample;
* Concurrent kernel execution and user defined context support for
OpenCL;
* Integration with Intel Perceptual SDK and new depth sensors support
for Windows;
* 32 reported bugs have been closed;
* 139 pull requests have been merged;
- Fix build with altivec:
opencv-altivec-vector.patch
- Added opencv-pkgconfig.patch: make sure to provide link flags in
OpenCV pc file (bnc#853036)
- Update to OpenCV 2.4.7
More info at:
http://opencv.org/opencv-2-4-7-is-out.html
The brief list of changes:
* dynamic OpenCL runtime loading, setting default OpenCL device
via env var, many bug-fixes and some new optimization with OpenCL
* bug-fixes and new optimizations in CUDA stuff
* latest NDK and Android OS support, Native Android Camera tuning
* minor fixes, XAML sample and MS Certification compatibility
in WinRT stuff
* 382 pull requests have been merged
* 54 reported bugs have been fixed
- Added pkgconfig(glu) Requires to devel package, as per .pc file
- Make devel package provides also devel-static one
- Drop assume-Sphinx-is-there.diff, and add improve-sphinx-search.diff,
for properly finding sphinx with alphabetic chars in version
- Add patch assume-Sphinx-is-there.diff to fix building with
Sphinx versions that have alphanumeric characters in the version
(Only for factory builds at the moment)
- Use eigen3 instead of eigen2 as build requirement for openSUSE > 12.3.
- Enable compilation with libucil and libunicap.
- Removed dos2unix build requirement (not needed anymore).
- Update to OpenCV 2.4.6.1
More info at:
http://opencv.org/opencv-2-4-6-is-out.html
The brief list of changes:
* added video file i/o Windows RT and sample application using
camera, enabled parallelization with TBB or MS Concurrency
* added CUDA 5.5 support for desktop and ARM systems
* added Qt 5 support
* added many new OpenCL algorithms ports, included OpenCL binaries
into the Windows superpack
* iOS build scripts (together with Android ones) moved to
‘opencv/platforms’ directory
* added functions for UIImage <-> cv::Mat conversion
* correct front/back camera selection in Android app framework
* added Linaro NDK support and fixes for MIPS to Android CMake
toolchain
* stability has been improved by a lot, numerous bug-fixes across
all the library
- build with LFS_CFLAGS in 32 bit archs.
- Disable SSE3 for all architectures (bnc#814333)
- Disable SSE(2) on non x86_64 architectures, causes crashing
kde#276923, bnc#789173
- Update to OpenCV 2.4.5
More info at:
http://opencv.org/opencv-2-4-5-is-out.html
The brief list of changes:
* experimental WinRT support
* new video super-resolution module
* CLAHE (adaptive histogram equalization) algorithm on both CPU
and GPU
* further improvements and extensions in ocl module
(stereo block matching and belief propagation have been added,
fixed crashes on Intel HD4000)
* Visual Studio 2012 cv::Mat visualizer plugin debugger tutorial
from Microsoft Research
* OpenCV4Android SDK improvements
(NDK r8e support, native activity sample using OpenCV Manager,
bug-fixes)
* ~25 reported problems have been resolved since 2.4.4, ~78 pull
requests have been merged, thanks everybody who participated!
- Update to OpenCV 2.4.4
More info at:
http://opencv.org/opencv-2-4-4-is-out.html
The brief list of changes:
* OpenCV Java bindings are ported from Android to desktop Java!
Actually any JVM language will work, see Tutorial for details,
and Java or Scala code samples.
* Android application framework, samples, tutorials, and OpenCV
Manager are improved.
* Optimizations for the new NVIDIA Kepler architecture, CARMA
platform support and other new optimizations in CUDA.
* OpenCL module now builds successfully with various SDKs (from
AMD, NVIDIA, Intel and Apple) and runs well on different GPUs
(AMD, NVidia, Intel HD4000). A lot of new functionality has been
added, tons of bugs fixed, performance of many functions has
been significantly improved.
* 100+ reported problems have been resolved since 2.4.3, thanks
everybody who participated!
- Drop the buildrequire for libxine
- Update to OpenCV 2.4.3
More info at:
http://opencv.org/opencv-2-4-3-released.html
The nicely formatted changelog can be seen here:
http://code.opencv.org/projects/opencv/wiki/ChangeLog;
here are the highlights:
* A lot of good stuff from the Google Summer of Code 2012 has been
integrated; this was a very productive summer!
* Significantly improved and optimized Android and iOS ports.
* Greatly extended GPU (i.e. CUDA-based) module.
* The brand new ocl (OpenCL-based) module that unleashes GPU power
also for AMD and Intel GPU users. It’s not included into the
binary package, since there are different SDKs, and it’s not
turned on by default. You need to run CMake and turn on
“WITH_OPENCL”. Also, please note that this is very first version
of the module, so it may be not very stable and not very
functional.
* Much better performance on many-core systems out of the box. You
do not need TBB anymore on MacOSX, iOS and Windows. BTW, the
binary package for Windows is now built without TBB support.
Libraries and DLLs for Visual Studio 2010 use the Concurrency
framework.
* About 130 bugs have been fixed since 2.4.2.
* Since 2.4.3rc we fixed several more problems, in particular some
compile problems with iOS 6 SDK.
- buildrequire glu
- Update to OpenCV 2.4.2
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Drop opencv-datadir.patch to comply with upstream directory layout
- Update to OpenCV 2.4.1
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Update to OpenCV 2.4.0
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Add opencv-gcc47.patch: Fix build with gcc 4.7.
- Use Explicit Buildrequires on several needed libraries
future dependency cleanups may/will cause build to fail otherwise.
- Add upstream r6881 to fix clang compatibility
- uncomment libraries not in 12.1 for now
- Changed groups (fix for RPMLINT warning)
- Added check for duplicate files (fix for RPMLINT warning)
- Added py_requires macros and python-base dependencies (fix for RPMLINT warning)
- Escaped macros (fix for RPMLINT warning)
- Fixed end-of-line encoding problems (fix for RPMLINT warning)
- Added libeigen2-devel buildrequires
- Added libunicap and libucil buildrequires (libunicap supports requires libucil)
- Cleaned up spec file formatting
- Dropped opencv-2.3-ffmpeg.patch, applied upstream
- Revive opencv-2.3-ffmpeg.patch, needs rebase
- Tag all patches according to openSUSE packaging guidelines
- Removed opencv-2.3-cmake.patch, old cmake cannot be used any more.
- Python bindings cannot be built without NumPy any more.
- Update to OpenCV 2.3.1
- Update and readd opencv-2.3-underlinking.patch since it is still
necessary.
- Fix support for new ffmpeg versions
- Removed unnecessary patches
- Enable Python NumPy support on openSUSE 11.2
- Build Qt instead of Gtk GUI
- Fix cmake files for openSUSE 11.1
- No GStreamer support on openSUSE 11.1
- Update to OpenCV 2.3.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Fix build on openSUSE 11.2
- Add opencv-v4l-2.6.38.patch: use the new libv4l2 interface
- Enable Python NumPy support
- SWIG is not required any more
- Enable OpenEXR support
- Update to OpenCV 2.2.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Use system zlib, oh, and do not export ZLIB symbols to
other applications, clashes ensued.
- fix build with gcc 4.6
- add -underlinking patch
- devel package renamed to opencv-devel, so that switching between
OBS and packman opencv packages is easier
- fix gstreamer support
- fix xine support
- fix some rpmlint warnings
- fix shared libraries permissions
- Do not waste resources building the tests as we do not run them
- Do not disable SSE,SSE2,etc. According to OpenCV changelog,
it should be safe to leave these enabled.
- fix build on openSUSE 11.0
- Update to OpenCV 2.1.0:
* The whole OpenCV is now using exceptions instead of the old
libc-style mechanism
* Experimental "static" OpenCV configuration in CMake was
contributed by Jose Luis Blanco.
Pass "BUILD_SHARED_LIBS=OFF" to CMake to build OpenCV statically.
* new improved version of one-way descriptor is added
* User can now control the image areas visible after the stereo
rectification
* Fullscreen has been added (thanks to Yannick Verdie).
* Further info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- fix build with libpng14
- small spec file cleanup
- Moved to the KDE repositories to enable inclusion in kipi-plugins
- Initial package
OBS-URL: https://build.opensuse.org/request/show/714221
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/opencv?expand=0&rev=73
2019-07-17 13:13:58 +02:00
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mv %{buildroot}%{_datadir}/opencv4/samples %{buildroot}%{_docdir}/%{name}-doc/examples
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2010-03-08 18:16:50 +01:00
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2013-08-01 15:56:40 +02:00
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# Fix rpmlint warning "doc-file-dependency"
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chmod 644 %{buildroot}%{_docdir}/%{name}-doc/examples/python/*.py
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2010-03-08 18:16:50 +01:00
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Accepting request 714221 from science
- Update to version 4.1.0
* DNN module:
+ Reduced peak memory consumption for some models up to 30%.
+ Inference Engine
- Inference Engine 2018R3 is now a minimal supported version of IE.
- Myriad X (Intel® Neural Compute Stick 2) is now supported and tested.
- Automatic IR network reshaping for different inputs.
- Improved samples to work with models from OpenVINO Open Model Zoo
+ New networks from TensorFlow Object Detection API: Faster-RCNNs, SSDs
and Mask-RCNN with dilated convolutions, FPN SSD
* Performance improvements:
+ More optimization using AVX2 instruction set.
+ Automatic runtime dispatching is available for large set of functions
from core and imgproc modules.
* Other improvements:
+ Matplotlib Perceptually Uniform Sequential colormaps
+ Add keypoints matching visualization for real-time pose estimation tutorial
+ Add Hand-Eye calibration methods
+ Java: improved support for multidimensional arrays (Mat)
+ Dynamically loaded videoio backends (FFmpeg, GStreamer)
+ opencv_contrib: Robust local optical flow (RLOF) implementations
+ opencv_contrib: Implementation of Quasi Dense Stereo algorithm
+ opencv_contrib: New module: Image Quality Analysis (IQA) API
+ opencv_contrib: BRISQUE No Reference Image Quality Assessment (IQA) API
Check https://github.com/opencv/opencv/wiki/ChangeLog#version410
- Update to version 4.0.0
* A lot of C API from OpenCV 1.x has been removed. The affected modules are
objdetect, photo, video, videoio, imgcodecs, calib3d.
* Persistence (storing and loading structured data to/from XML, YAML or JSON)
in the core module has been completely reimplemented.
* OpenCV is now C++11 library and requires C++11-compliant compiler.
Thanks to the extended C++11 standard library, we could get rid of hand-crafted
cv::String and cv::Ptr. Now cv::String == std::string and cv::Ptr is a thin
wrapper on top of std::shared_ptr. Also, on Linux/BSD for cv::parallel_for_
we now use std::thread's instead of pthreads.
* DNN improvements
* Completely new module opencv_gapi has been added. It is the engine for very
efficient image processing, based on lazy evaluation and on-fly construction.
* Performance improvements
A few hundreds of basic kernels in OpenCV have been rewritten using so-called
"wide universal intrinsics". Those intrinsics map to SSE2, SSE4, AVX2, NEON or
VSX intrinsics, depending on the target platform and the compile flags.
* QR code detector and decoder have been added to opencv/objdetect module.
* The popular Kinect Fusion algorithm has been implemented, optimized for CPU and
GPU (OpenCL), and integrated into opencv_contrib/rgbd module.
* Very efficient and yet high-quality DIS dense optical flow algorithm has been
moved from opencv_contrib to opencv, video module. See the example.
* The slower TV L1 optical flow algorithm has been moved to opencv_contrib.
Check https://github.com/opencv/opencv/wiki/ChangeLog#version400
- Drop obsolete opencv-lib_suffix.patch
- Add 0001-Handle-absolute-OPENCV_INCLUDE_INSTALL_PATH-correctl.patch
- As this is a major version upgrade, the old 3.4.x package is still
available as opencv3
- Update to 3.4.3
* Compatibility fixes with python 3.7
* Added a new computational target DNN_TARGET_OPENCL_FP16
* Extended support of Intel's Inference Engine backend
* Enabled import of Intel's OpenVINO pre-trained networks from
intermediate representation (IR).
* tutorials improvements
Check https://github.com/opencv/opencv/wiki/ChangeLog#version343
for the complete changelog.
- Drop fix-build-i386-nosse.patch, build-workaround-issues-with-c.patch
(fixed upstream)
- Refresh patches
- Add patch to fix use of headers from C:
* build-workaround-issues-with-c.patch
- Update to 3.4.1:
* Added support for quantized TensorFlow networks
* OpenCV is now able to use Intel DL inference engine as DNN
acceleration backend
* Added AVX-512 acceleration to the performance-critical kernels
* For more information, read
https://github.com/opencv/opencv/wiki/ChangeLog#version341
- Update contrib modules to 3.4.1:
* No changelog available
- Change mechanism the contrib modules are built
- Include LICENSE of contrib tarball as well
- Build with python3 on >= 15
- Add patch to fix build on i386 without SSE:
* fix-build-i386-nosse.patch
- Refresh patches:
* fix_processor_detection_for_32bit_on_64bit.patch
* opencv-build-compare.patch
- Mention all libs explicitly
- Rebase 3.4.0 update from i@marguerite.su
- update to 3.4.0
* Added faster R-CNN support
* Javascript bindings have been extended to
cover DNN module
* DNN has been further accelerated for iGPU
using OpenCL
* On-disk caching of precompiled OpenCL
kernels has been finally implemented
* possible to load and run pre-compiled
OpenCL kernels via T-API
* Bit-exact 8-bit and 16-bit resize has been
implemented (currently supported only
bilinear interpolation)
- update face module to 3.4.0
- add opencv-lib_suffix.patch, remove LIB_SUFFIX
from OPENCV_LIB_INSTALL_PATH, as CMAKE_INSTALL
_LIBDIR is arch dependent.
- Add option to build without openblas
- Add conditionals for python2 and python3 to allow us enabling
only desired python variants when needed
- Do not depend on sphinx as py2 and py3 seem to collide there
- Readd opencv-gles.patch, it is *not* included upstream; otherwise
build breaks on all GLES Qt5 platforms (armv6l, armv7l, aarch64)
- add fix_processor_detection_for_32bit_on_64bit.patch
- Correctly set optimizations and dynamic dispatch on ARM, use
OpenCV 3.3 syntax on x86.
- Update licensing information
- change requires of python-numpy-devel to build in Leap and
to not break factory in future
- fix build error/unresolvable for Leap 42.2 and 42.3
- Update to version 3.3.1:
* Lots of various bugfixes
- Update source url
- Rename python subpackage to python2
- Do not explicitly require python-base for python subpackages
- Update to 3.3
- Dropped obsolete patches
* opencv-gcc6-fix-pch-support-PR8345.patch
* opencv-gles.patch
- Updated opencv-build-compare.patch
- Add 0001-Do-not-include-glx.h-when-using-GLES.patch
Fix build for 32bit ARM, including both GLES and desktop GL headers
causes incompatible pointer type errors
- Add conditional for the qt5/qt4 integration
* This is used only for gui tools, library is not affected
- Add provides/obsoletes for the qt5 packages to allow migration
- Drop patch opencv-qt5-sobump.diff
* Used only by the obsoleted qt5 variant
- Cleanup a bit with spec-cleaner
- Use %cmake macros
- Remove the conditions that are not really needed
- Add tests conditional disabled by default
* Many tests fail and there are missing testdata
- Switch to pkgconfig style dependencies
- Update to OpenCV 3.2.0
- Results from 11 GSoC 2016 projects have been submitted to the library:
+ sinusoidal patterns for structured light and phase unwrapping module
[Ambroise Moreau (Delia Passalacqua)]
+ DIS optical flow (excellent dense optical flow algorithm that is both
significantly better and significantly faster than Farneback’s algorithm –
our baseline), and learning-based color constancy algorithms implementation
[Alexander Bokov (Maksim Shabunin)]
+ CNN based tracking algorithm (GOTURN) [Tyan Vladimir (Antonella Cascitelli)]
+ PCAFlow and Global Patch Collider algorithms implementation
[Vladislav Samsonov (Ethan Rublee)]
+ Multi-language OpenCV Tutorials in Python, C++ and Java
[João Cartucho (Vincent Rabaud)]
+ New camera model and parallel processing for stitching pipeline
[Jiri Horner (Bo Li)]
+ Optimizations and improvements of dnn module
[Vitaliy Lyudvichenko (Anatoly Baksheev)]
+ Base64 and JSON support for file storage. Use names like
“myfilestorage.xml?base64” when writing file storage to store big chunks of
numerical data in base64-encoded form. [Iric Wu (Vadim Pisarevsky)]
+ tiny_dnn improvements and integration
[Edgar Riba (Manuele Tamburrano, Stefano Fabri)]
+ Quantization and semantic saliency detection with tiny_dnn
[Yida Wang (Manuele Tamburrano, Stefano Fabri)]
+ Word-spotting CNN based algorithm
[Anguelos Nicolaou (Lluis Gomez)]
- Contributions besides GSoC:
+ Greatly improved and accelerated dnn module in opencv_contrib:
- Many new layers, including deconvolution, LSTM etc.
- Support for semantic segmentation and SSD networks with samples.
- TensorFlow importer + sample that runs Inception net by Google.
+ More image formats and camera backends supported
+ Interactive camera calibration app
+ Multiple algorithms implemented in opencv_contrib
+ Supported latest OSes, including Ubuntu 16.04 LTS and OSX 10.12
+ Lot’s of optimizations for IA and ARM archs using parallelism, vector
instructions and new OpenCL kernels.
+ OpenCV now can use vendor-provided OpenVX and LAPACK/BLAS (including Intel MKL,
Apple’s Accelerate, OpenBLAS and Atlas) for acceleration
- Refreshed opencv-build-compare.patch
- Dropped upstream opencv-gcc5.patch
- Replace opencv-gcc6-disable-pch.patch with upstream patch
opencv-gcc6-fix-pch-support-PR8345.patch
- Enable TBB support (C++ threading library)
- Add dependency on openBLAS
- Enable ffmpeg support unconditional
- In case we build using GCC6 (or newer), add -mlra to CFLAGS to
workaround gcc bug
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=71294.
- Apply upstream patch opencv-gcc6-disable-pch.patch to disable
PCH for GCC6.
- Test for python versions greater than or equal to the current
version.
- Add python 3 support
- Added opencv_contrib_face-3.1.0.tar.bz2
* This tarball is created to take only the face module from the
contrib package. The Face module is required by libkface, which
in its turn is required by digikam.
- Added _constraints file to avoid random failures on small workers
(at least for builds on PMBS)
- Update to OpenCV 3.1.0
- A lot of new functionality has been introduced during Google
Summer of Code 2015:
+ “Omnidirectional Cameras Calibration and Stereo 3D
Reconstruction” – opencv_contrib/ccalib module
(Baisheng Lai, Bo Li)
+ “Structure From Motion” – opencv_contrib/sfm module
(Edgar Riba, Vincent Rabaud)
+ “Improved Deformable Part-based Models” – opencv_contrib/dpm
module (Jiaolong Xu, Bence Magyar)
+ “Real-time Multi-object Tracking using Kernelized Correlation
Filter” – opencv_contrib/tracking module
(Laksono Kurnianggoro, Fernando J. Iglesias Garcia)
+ “Improved and expanded Scene Text Detection” –
opencv_contrib/text module (Lluis Gomez, Vadim Pisarevsky)
+ “Stereo correspondence improvements” – opencv_contrib/stereo
module (Mircea Paul Muresan, Sergei Nosov)
+ “Structured-Light System Calibration” –
opencv_contrib/structured_light (Roberta Ravanelli,
Delia Passalacqua, Stefano Fabri, Claudia Rapuano)
+ “Chessboard+ArUco for camera calibration” –
opencv_contrib/aruco (Sergio Garrido, Prasanna, Gary Bradski)
+ “Implementation of universal interface for deep neural
network frameworks” – opencv_contrib/dnn module
(Vitaliy Lyudvichenko, Anatoly Baksheev)
+ “Recent advances in edge-aware filtering, improved SGBM
stereo algorithm” – opencv/calib3d and opencv_contrib/ximgproc
(Alexander Bokov, Maksim Shabunin)
+ “Improved ICF detector, waldboost implementation” –
opencv_contrib/xobjdetect (Vlad Shakhuro, Alexander Bovyrin)
+ “Multi-target TLD tracking” – opencv_contrib/tracking module
(Vladimir Tyan, Antonella Cascitelli)
+ “3D pose estimation using CNNs” – opencv_contrib/cnn_3dobj
(Yida Wang, Manuele Tamburrano, Stefano Fabri)
- Many great contributions made by the community, such as:
+ Support for HDF5 format
+ New/Improved optical flow algorithms
+ Multiple new image processing algorithms for filtering,
segmentation and feature detection
+ Superpixel segmentation and much more
- IPPICV is now based on IPP 9.0.1, which should make OpenCV
even faster on modern Intel chips
- opencv_contrib modules can now be included into the
opencv2.framework for iOS
- Newest operating systems are supported: Windows 10 and
OSX 10.11 (Visual Studio 2015 and XCode 7.1.1)
- Interoperability between T-API and OpenCL, OpenGL, DirectX and
Video Acceleration API on Linux, as well as Android 5 camera.
- HAL (Hardware Acceleration Layer) module functionality has been
moved into corresponding basic modules; the HAL replacement
mechanism has been implemented along with the examples
- Removed improve-sphinx-search.diff, opencv-altivec-vector.patch,
opencv-pkgconfig.patch and opencv-samples.patch, fixed upstream.
- Fixed opencv-qt5-sobump.diff, opencv-build-compare.patch,
opencv-gcc5.patch and opencv-gles.patch.
- Version OpenCV 3.0.0
+ ~1500 patches, submitted as PR @ github. All our patches go
the same route.
+ opencv_contrib (http://github.com/itseez/opencv_contrib)
repository has been added. A lot of new functionality is there
already! opencv_contrib is only compatible with 3.0/master,
not 2.4. Clone the repository and use “cmake …
-D OPENCV_EXTRA_MODULES_PATH=<path_to opencv_contrib/modules> …”
to build opencv and opencv_contrib together.
+ a subset of Intel IPP (IPPCV) is given to us and our users free
of charge, free of licensing fees, for commercial and
non-commerical use. It’s used by default in x86 and x64 builds
on Windows, Linux and Mac.
+ T-API (transparent API) has been introduced, this is transparent
GPU acceleration layer using OpenCL. It does not add any
compile-time or runtime dependency of OpenCL. When OpenCL is
available, it’s detected and used, but it can be disabled at
compile time or at runtime. It covers ~100 OpenCV functions.
This work has been done by contract and with generous support
from AMD and Intel companies.
+ ~40 OpenCV functions have been accelerated using NEON intrinsics
and because these are mostly basic functions, some higher-level
functions got accelerated as well.
+ There is also new OpenCV HAL layer that will simplifies creation
of NEON-optimized code and that should form a base for the
open-source and proprietary OpenCV accelerators.
+ The documentation is now in Doxygen: http://docs.opencv.org/master/
+ We cleaned up API of many high-level algorithms from features2d,
calib3d, objdetect etc. They now follow the uniform
“abstract interface – hidden implementation” pattern and make
extensive use of smart pointers (Ptr<>).
+ Greatly improved and extended Python & Java bindings (also,
see below on the Python bindings), newly introduced Matlab
bindings (still in alpha stage).
+ Improved Android support – now OpenCV Manager is in Java and
supports both 2.4 and 3.0.
+ Greatly improved WinRT support, including video capturing and
multi-threading capabilities. Thanks for Microsoft team for this!
+ Big thanks to Google who funded several successive GSoC programs
and let OpenCV in. The results of many successful GSoC 2013 and
2014 projects have been integrated in opencv 3.0 and
opencv_contrib (earlier results are also available in
OpenCV 2.4.x). We can name:
- text detection
- many computational photography algorithms (HDR, inpainting,
edge-aware filters, superpixels, …)
- tracking and optical flow algorithms
- new features, including line descriptors, KAZE/AKAZE
- general use optimization (hill climbing, linear programming)
- greatly improved Python support, including Python 3.0 support,
many new tutorials & samples on how to use OpenCV with Python.
- 2d shape matching module and 3d surface matching module
- RGB-D module
- VTK-based 3D visualization module
- etc.
+ Besides Google, we enjoyed (and hope that you will enjoy too)
many useful contributions from community, like:
- biologically inspired vision module
- DAISY features, LATCH descriptor, improved BRIEF
- image registration module
- etc.
- Reduce build-compare noise
opencv-build-compare.patch
- Remove BuildRequirement for python-sphinx in SLE12, since it's
not available there and it's not a mandatory requirement.
- Reduce differences between two spec files
- Use pkgconfig for ffmpeg BuildRequires
- Update improve-sphinx-search.diff for new python-Sphinx(1.3.1)
* now that sphinx-build disallow executing without arguments and
give you "Insufficient arguments" error, use "sphinx-build -h"
instead
* the default usages output ie. sphinx-build(or --help) no longer
are standard error but standard output, drop OUTPUT_QUIET and
add OUTPUT_VARIABLE throws the output to SPHINX_OUTPUT as well
- support gcc 5 (i.e. gcc versions without minor version):
opencv-gcc5.patch
- Update to OpenCV 2.4.11 - can't find NEWS or Changelog
merely collecting bug fixes while 3.0 is in the making, 2.4.11
didn't even make it on their web page, it's only on download
server
- remove opencv-underlinking.patch as obsolete
- remove upstream patch bomb_commit_gstreamer-1x-support.patch
- commenting out opencv-pkgconfig.patch - possibly it requires a rebase,
but the problem it tries to solve is unclear
- Add specific buildrequires for libpng15, so that we are
building against the system provided libpng.
- Update to OpenCV 2.4.9
More info at:
http://opencv.org/opencv-2-4-9-is-out.html
The brief list of changes:
* new 3D visualization module ‘viz’;
* performance fixes in ‘ocl’ module;
* fixes in Android Camera;
* improved CUDA support for mobile platforms;
* bugfixes from community;
* 55 reported bugs have been closed;
* 156 pull requests have been merged.
- Drop the BuildRequires on libucil and libunicap for Factory. This
stops us from getting ride of Gstreamer 0.10 and besides these two
libraries seem to be unmaintained upstream as that the latest
actions are from 2010
- Add upstream patch (3.0 version) to support Gstreamer 1.x
* bomb_commit_gstreamer-1x-support.patch
- Upstream now provides tarballs with source only as git tags
from github so update Source0 path.
- Add requires on various X extensions linked to opencv_ts module.
As those are present in the .pc file we need it anyway.
- Update to OpenCV 2.4.8
More info at:
http://opencv.org/opencv-2-4-8.html
The brief list of changes:
* NVidia CUDA support on Android devices with CUDA capable SoC and
CUDA sample;
* Concurrent kernel execution and user defined context support for
OpenCL;
* Integration with Intel Perceptual SDK and new depth sensors support
for Windows;
* 32 reported bugs have been closed;
* 139 pull requests have been merged;
- Fix build with altivec:
opencv-altivec-vector.patch
- Added opencv-pkgconfig.patch: make sure to provide link flags in
OpenCV pc file (bnc#853036)
- Update to OpenCV 2.4.7
More info at:
http://opencv.org/opencv-2-4-7-is-out.html
The brief list of changes:
* dynamic OpenCL runtime loading, setting default OpenCL device
via env var, many bug-fixes and some new optimization with OpenCL
* bug-fixes and new optimizations in CUDA stuff
* latest NDK and Android OS support, Native Android Camera tuning
* minor fixes, XAML sample and MS Certification compatibility
in WinRT stuff
* 382 pull requests have been merged
* 54 reported bugs have been fixed
- Added pkgconfig(glu) Requires to devel package, as per .pc file
- Make devel package provides also devel-static one
- Drop assume-Sphinx-is-there.diff, and add improve-sphinx-search.diff,
for properly finding sphinx with alphabetic chars in version
- Add patch assume-Sphinx-is-there.diff to fix building with
Sphinx versions that have alphanumeric characters in the version
(Only for factory builds at the moment)
- Use eigen3 instead of eigen2 as build requirement for openSUSE > 12.3.
- Enable compilation with libucil and libunicap.
- Removed dos2unix build requirement (not needed anymore).
- Update to OpenCV 2.4.6.1
More info at:
http://opencv.org/opencv-2-4-6-is-out.html
The brief list of changes:
* added video file i/o Windows RT and sample application using
camera, enabled parallelization with TBB or MS Concurrency
* added CUDA 5.5 support for desktop and ARM systems
* added Qt 5 support
* added many new OpenCL algorithms ports, included OpenCL binaries
into the Windows superpack
* iOS build scripts (together with Android ones) moved to
‘opencv/platforms’ directory
* added functions for UIImage <-> cv::Mat conversion
* correct front/back camera selection in Android app framework
* added Linaro NDK support and fixes for MIPS to Android CMake
toolchain
* stability has been improved by a lot, numerous bug-fixes across
all the library
- build with LFS_CFLAGS in 32 bit archs.
- Disable SSE3 for all architectures (bnc#814333)
- Disable SSE(2) on non x86_64 architectures, causes crashing
kde#276923, bnc#789173
- Update to OpenCV 2.4.5
More info at:
http://opencv.org/opencv-2-4-5-is-out.html
The brief list of changes:
* experimental WinRT support
* new video super-resolution module
* CLAHE (adaptive histogram equalization) algorithm on both CPU
and GPU
* further improvements and extensions in ocl module
(stereo block matching and belief propagation have been added,
fixed crashes on Intel HD4000)
* Visual Studio 2012 cv::Mat visualizer plugin debugger tutorial
from Microsoft Research
* OpenCV4Android SDK improvements
(NDK r8e support, native activity sample using OpenCV Manager,
bug-fixes)
* ~25 reported problems have been resolved since 2.4.4, ~78 pull
requests have been merged, thanks everybody who participated!
- Update to OpenCV 2.4.4
More info at:
http://opencv.org/opencv-2-4-4-is-out.html
The brief list of changes:
* OpenCV Java bindings are ported from Android to desktop Java!
Actually any JVM language will work, see Tutorial for details,
and Java or Scala code samples.
* Android application framework, samples, tutorials, and OpenCV
Manager are improved.
* Optimizations for the new NVIDIA Kepler architecture, CARMA
platform support and other new optimizations in CUDA.
* OpenCL module now builds successfully with various SDKs (from
AMD, NVIDIA, Intel and Apple) and runs well on different GPUs
(AMD, NVidia, Intel HD4000). A lot of new functionality has been
added, tons of bugs fixed, performance of many functions has
been significantly improved.
* 100+ reported problems have been resolved since 2.4.3, thanks
everybody who participated!
- Drop the buildrequire for libxine
- Update to OpenCV 2.4.3
More info at:
http://opencv.org/opencv-2-4-3-released.html
The nicely formatted changelog can be seen here:
http://code.opencv.org/projects/opencv/wiki/ChangeLog;
here are the highlights:
* A lot of good stuff from the Google Summer of Code 2012 has been
integrated; this was a very productive summer!
* Significantly improved and optimized Android and iOS ports.
* Greatly extended GPU (i.e. CUDA-based) module.
* The brand new ocl (OpenCL-based) module that unleashes GPU power
also for AMD and Intel GPU users. It’s not included into the
binary package, since there are different SDKs, and it’s not
turned on by default. You need to run CMake and turn on
“WITH_OPENCL”. Also, please note that this is very first version
of the module, so it may be not very stable and not very
functional.
* Much better performance on many-core systems out of the box. You
do not need TBB anymore on MacOSX, iOS and Windows. BTW, the
binary package for Windows is now built without TBB support.
Libraries and DLLs for Visual Studio 2010 use the Concurrency
framework.
* About 130 bugs have been fixed since 2.4.2.
* Since 2.4.3rc we fixed several more problems, in particular some
compile problems with iOS 6 SDK.
- buildrequire glu
- Update to OpenCV 2.4.2
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Drop opencv-datadir.patch to comply with upstream directory layout
- Update to OpenCV 2.4.1
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Update to OpenCV 2.4.0
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Add opencv-gcc47.patch: Fix build with gcc 4.7.
- Use Explicit Buildrequires on several needed libraries
future dependency cleanups may/will cause build to fail otherwise.
- Add upstream r6881 to fix clang compatibility
- uncomment libraries not in 12.1 for now
- Changed groups (fix for RPMLINT warning)
- Added check for duplicate files (fix for RPMLINT warning)
- Added py_requires macros and python-base dependencies (fix for RPMLINT warning)
- Escaped macros (fix for RPMLINT warning)
- Fixed end-of-line encoding problems (fix for RPMLINT warning)
- Added libeigen2-devel buildrequires
- Added libunicap and libucil buildrequires (libunicap supports requires libucil)
- Cleaned up spec file formatting
- Dropped opencv-2.3-ffmpeg.patch, applied upstream
- Revive opencv-2.3-ffmpeg.patch, needs rebase
- Tag all patches according to openSUSE packaging guidelines
- Removed opencv-2.3-cmake.patch, old cmake cannot be used any more.
- Python bindings cannot be built without NumPy any more.
- Update to OpenCV 2.3.1
- Update and readd opencv-2.3-underlinking.patch since it is still
necessary.
- Fix support for new ffmpeg versions
- Removed unnecessary patches
- Enable Python NumPy support on openSUSE 11.2
- Build Qt instead of Gtk GUI
- Fix cmake files for openSUSE 11.1
- No GStreamer support on openSUSE 11.1
- Update to OpenCV 2.3.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Fix build on openSUSE 11.2
- Add opencv-v4l-2.6.38.patch: use the new libv4l2 interface
- Enable Python NumPy support
- SWIG is not required any more
- Enable OpenEXR support
- Update to OpenCV 2.2.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Use system zlib, oh, and do not export ZLIB symbols to
other applications, clashes ensued.
- fix build with gcc 4.6
- add -underlinking patch
- devel package renamed to opencv-devel, so that switching between
OBS and packman opencv packages is easier
- fix gstreamer support
- fix xine support
- fix some rpmlint warnings
- fix shared libraries permissions
- Do not waste resources building the tests as we do not run them
- Do not disable SSE,SSE2,etc. According to OpenCV changelog,
it should be safe to leave these enabled.
- fix build on openSUSE 11.0
- Update to OpenCV 2.1.0:
* The whole OpenCV is now using exceptions instead of the old
libc-style mechanism
* Experimental "static" OpenCV configuration in CMake was
contributed by Jose Luis Blanco.
Pass "BUILD_SHARED_LIBS=OFF" to CMake to build OpenCV statically.
* new improved version of one-way descriptor is added
* User can now control the image areas visible after the stereo
rectification
* Fullscreen has been added (thanks to Yannick Verdie).
* Further info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- fix build with libpng14
- small spec file cleanup
- Moved to the KDE repositories to enable inclusion in kipi-plugins
- Initial package
OBS-URL: https://build.opensuse.org/request/show/714221
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/opencv?expand=0&rev=73
2019-07-17 13:13:58 +02:00
|
|
|
# Remove LD_LIBRARY_PATH wrapper script, we install into proper library dirs
|
|
|
|
|
rm %{buildroot}%{_bindir}/setup_vars_opencv4.sh
|
|
|
|
|
|
2019-08-28 18:57:07 +02:00
|
|
|
# Fix duplicated install prefix in pkg-config file
|
Accepting request 983700 from home:StefanBruens:branches:science
- update to 4.6.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version460
* OpenCV project infrastructure migrating on GitHub Actions
workflows for CI and release purposes
* Added support for GCC 12, Clang 15
* Added support for FFmpeg 5.0
* DNN module patches:
+ Improved layers / activations / supported more models:
- LSTM (+CUDA), resize (+ONNX13), Sign, Shrink, Reciprocal,
depth2space, space2depth
- fixes in Reduce, Slice, Expand
+ Disabled floating-point denormals processing #21521
+ Changed layer names in ONNX importer to support "output"
entities properly
+ Added TIM-VX NPU backend support:
https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU
+ Added Softmax parameter to ClassificationModel
+ Added audio speech recognition sample (C++) #21458
+ Intel® Inference Engine backend (OpenVINO):
- added initial support for OpenVINO 2022.1 release
- removed support of legacy API (dropped since 2020.3)
* G-API module:
+ G-API framework:
- Introduced a Grayscale image format support for
cv::MediaFrame: #21511;
- Enabeled .reshape() support in the CPU backend: #21669;
- Fixed possible hang in streaming execution mode with constant
inputs: #21567;
- Introduced proper error/exception propagation in the
asynchronous streaming execution mode: #21660;
- Fixed new stream event handling: #21731.
+ Fluid backend:
- Fixed horizontal pass in the Resize kernel, fixed Valgrind
issues: #21144;
- Extended Resize kernel with F32 version: #21678,
added AVX: #21728.
- Enabled dynamic dispatch for Split4 kernel: #21520;
- Enabled dynamic dispatch for Merge3 kernel: #21529;
- Added a SIMD version for DivC kernel: #21474;
- Added a SIMD version for DivRC kernel: #21530;
- Enabled dynamic dispatch for Add kernel: #21686;
- Enabled dynamic dispatch for Sub kernel: #21746;
- Added a SIMD version for ConvertTo kernel: #21777;
- Fixed kernel matrix size for Sobel kernel: #21613.
+ Intel® OpenVINO™ inference backend:
- Fixed NV12 format support for remote memory when OpenVINO
remote context is used: #21424.
- Implemented correct error handling in the backend: #21579.
- Fixed ngraph warnings #21362.
+ OpenCV AI Kit backend:
- Introduced a new backend to program OpenCV AI Kit boards via
G-API. Currently the backend is in experimental state, but allows
to build Camera+NN pipeline and supports heterogeneity (mixing
with host-side code): #20785, #21504.
+ Media integration:
- Enabled GPU inference with oneVPL and DirectX11 on Windows in
Intel OpenVINO inference backend: #21232, #21618, #21658, #21687,
#21688. Now GPU textures decoded by oneVPL decoder can be
preprocessed and inferred on GPU with no extra host processing.
- Enabled oneVPL support on Linux: #21883.
- Extended GStreamer pipeline source with Grayscale image format
support: #21560.
+ Python bindings:
- Exposed GStreamer pipeline source in Python bindings: #20832.
- Fixed Python bindings for CudaBufferPool, cudacodec and cudastereo
modules in OpenCV Contrib.
+ Samples:
- Introduced a pipeline modelling tool for cascaded model
benchmarking: #21477, #21636, #21719. The tool supports a
declarative YAML-based config to describe pipelines with simulated
pre-/post-processing. The tool collects and reports latency and
throughput information for the modelled pipeline.
+ Other changes and fixes:
- Moved GKernelPackage into cv:: namespace by default, its cv::gapi::
alias remain for compatibility: #21318;
- Moved Resize kernel from core to imgproc kernel packages for
CPU, OpenCL, and Fluid backends: #21157. Also moved tests
appropriately: #21475;
- Avoided sporadic test failures in DivC: #21626;
- Fixed 1D Mat handling in the framework: #21782;
- Reduced the number of G-API generated accuracy tests: #21909.
- Drop upstream patches:
* 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
* videoio_initial_FFmpeg_5_0_support.patch
* videoio_ffmpeg_avoid_memory_leaks.patch
OBS-URL: https://build.opensuse.org/request/show/983700
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=33
2022-06-27 18:05:05 +02:00
|
|
|
cat %{buildroot}%{_libdir}/pkgconfig/opencv4.pc
|
2019-08-28 18:57:07 +02:00
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sed -i -e 's|//usr||g' %{buildroot}%{_libdir}/pkgconfig/opencv4.pc
|
|
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2013-08-01 15:56:40 +02:00
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%fdupes -s %{buildroot}%{_docdir}/%{name}-doc/examples
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%fdupes -s %{buildroot}%{_includedir}
|
2010-03-08 18:16:50 +01:00
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|
Accepting request 860308 from home:StefanBruens:branches:science
- update to 4.5.1, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version451
* Continued merging of GSoC 2020 results:
+ Develop OpenCV.js DNN modules for promising web use cases
together with their tutorials
+ OpenCV.js: WASM SIMD optimization 2.0
+ High Level API and Samples for Scene Text Detection and
Recognition
+ SIFT: SIMD optimization of GaussianBlur 16U
* DNN module:
+ Improved layers / activations / supported more models:
- optimized: 1D convolution, 1D pool
- fixed: Resize, ReduceMean, Gather with multiple outputs,
importing of Faster RCNN ONNX model
- added support: INT32 ONNX tensors
+ Intel® Inference Engine backend (OpenVINO):
- added support for OpenVINO 2021.2 release
- added preview support for HDDL
+ Fixes and optimizations in DNN CUDA backend (thanks to
@YashasSamaga)
* G-API Framework:
+ Introduced serialization for cv::RMat, including
serialization for user-defined memory adapters
+ Introduced desync, a new Operation for in-graph asynchronous
execution - to allow different parts of the graph run with
a different latency
+ Introduced a notion of "in-graph metadata", now various
media-related information can be accessed in graph directly
(currently only limited to timestamps and frame IDs)
+ Introduced a new generic task-based executor, based on
Threading Building Blocks (TBB)
+ Extended infer<>() API to accept a new cv::GFrame data
structure to allow handling of various media formats without
changes in the graph structure
+ Made copy() an intrinsic where real copy may not happen
(optimized out) based on graph structure, extended it to
support cv::GFrame
+ Various fixes, including addressig static analysis,
documentation, and test issues
* G-API Operations:
+ Introduced new operations morphologyEx, boundingRect,
fitLine, kmeans, Background Subtractor, Kalman filter
* G-API Intel® Inference Engine backend (OpenVINO):
+ Extended cv::gapi::ie::Params<> to import CNN networks (e.g.
pre-compiled ones) instead of passing .XML and .BIN files;
also enabled configuring Inference Engine plugins via
this structure
+ Added a new overload to infer<>() to run inference over a
single region of interest
+ Added support for cv::MediaFrame input data type (projected
from cv::GFrame) and handling for NV12 input image format
* G-API Python bindings:
+ Exposed G-API's Inference and Streaming APIs in the OpenCV
Python bindings
+ Added initial Python support for cv::GArray data structure
* Significant progress on RISC-V port.
- Updated constraints, bump memory to 5 GB
- Cleaned up spec file
OBS-URL: https://build.opensuse.org/request/show/860308
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=23
2021-01-04 20:56:22 +01:00
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|
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%check
|
|
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|
|
%if %{with tests}
|
|
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|
|
export LD_LIBRARY_PATH=$(pwd)/build/lib:$LD_LIBRARY_PATH
|
|
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|
|
%ctest
|
|
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|
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|
# Diagnostics:
|
|
|
|
|
%{buildroot}%{_bindir}/opencv_version -v
|
|
|
|
|
%{buildroot}%{_bindir}/opencv_version -hw
|
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|
grep -E 'model|stepping|flags' /proc/cpuinfo | head -n4
|
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%endif
|
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2013-08-01 15:56:40 +02:00
|
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%post -n %{libname}%{soname} -p /sbin/ldconfig
|
|
|
|
|
%postun -n %{libname}%{soname} -p /sbin/ldconfig
|
2021-02-22 20:10:19 +01:00
|
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%post -n libopencv_aruco%{soname} -p /sbin/ldconfig
|
|
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|
|
%postun -n libopencv_aruco%{soname} -p /sbin/ldconfig
|
2020-11-03 06:17:42 +01:00
|
|
|
%post -n libopencv_face%{soname} -p /sbin/ldconfig
|
|
|
|
|
%postun -n libopencv_face%{soname} -p /sbin/ldconfig
|
Accepting request 983700 from home:StefanBruens:branches:science
- update to 4.6.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version460
* OpenCV project infrastructure migrating on GitHub Actions
workflows for CI and release purposes
* Added support for GCC 12, Clang 15
* Added support for FFmpeg 5.0
* DNN module patches:
+ Improved layers / activations / supported more models:
- LSTM (+CUDA), resize (+ONNX13), Sign, Shrink, Reciprocal,
depth2space, space2depth
- fixes in Reduce, Slice, Expand
+ Disabled floating-point denormals processing #21521
+ Changed layer names in ONNX importer to support "output"
entities properly
+ Added TIM-VX NPU backend support:
https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU
+ Added Softmax parameter to ClassificationModel
+ Added audio speech recognition sample (C++) #21458
+ Intel® Inference Engine backend (OpenVINO):
- added initial support for OpenVINO 2022.1 release
- removed support of legacy API (dropped since 2020.3)
* G-API module:
+ G-API framework:
- Introduced a Grayscale image format support for
cv::MediaFrame: #21511;
- Enabeled .reshape() support in the CPU backend: #21669;
- Fixed possible hang in streaming execution mode with constant
inputs: #21567;
- Introduced proper error/exception propagation in the
asynchronous streaming execution mode: #21660;
- Fixed new stream event handling: #21731.
+ Fluid backend:
- Fixed horizontal pass in the Resize kernel, fixed Valgrind
issues: #21144;
- Extended Resize kernel with F32 version: #21678,
added AVX: #21728.
- Enabled dynamic dispatch for Split4 kernel: #21520;
- Enabled dynamic dispatch for Merge3 kernel: #21529;
- Added a SIMD version for DivC kernel: #21474;
- Added a SIMD version for DivRC kernel: #21530;
- Enabled dynamic dispatch for Add kernel: #21686;
- Enabled dynamic dispatch for Sub kernel: #21746;
- Added a SIMD version for ConvertTo kernel: #21777;
- Fixed kernel matrix size for Sobel kernel: #21613.
+ Intel® OpenVINO™ inference backend:
- Fixed NV12 format support for remote memory when OpenVINO
remote context is used: #21424.
- Implemented correct error handling in the backend: #21579.
- Fixed ngraph warnings #21362.
+ OpenCV AI Kit backend:
- Introduced a new backend to program OpenCV AI Kit boards via
G-API. Currently the backend is in experimental state, but allows
to build Camera+NN pipeline and supports heterogeneity (mixing
with host-side code): #20785, #21504.
+ Media integration:
- Enabled GPU inference with oneVPL and DirectX11 on Windows in
Intel OpenVINO inference backend: #21232, #21618, #21658, #21687,
#21688. Now GPU textures decoded by oneVPL decoder can be
preprocessed and inferred on GPU with no extra host processing.
- Enabled oneVPL support on Linux: #21883.
- Extended GStreamer pipeline source with Grayscale image format
support: #21560.
+ Python bindings:
- Exposed GStreamer pipeline source in Python bindings: #20832.
- Fixed Python bindings for CudaBufferPool, cudacodec and cudastereo
modules in OpenCV Contrib.
+ Samples:
- Introduced a pipeline modelling tool for cascaded model
benchmarking: #21477, #21636, #21719. The tool supports a
declarative YAML-based config to describe pipelines with simulated
pre-/post-processing. The tool collects and reports latency and
throughput information for the modelled pipeline.
+ Other changes and fixes:
- Moved GKernelPackage into cv:: namespace by default, its cv::gapi::
alias remain for compatibility: #21318;
- Moved Resize kernel from core to imgproc kernel packages for
CPU, OpenCL, and Fluid backends: #21157. Also moved tests
appropriately: #21475;
- Avoided sporadic test failures in DivC: #21626;
- Fixed 1D Mat handling in the framework: #21782;
- Reduced the number of G-API generated accuracy tests: #21909.
- Drop upstream patches:
* 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
* videoio_initial_FFmpeg_5_0_support.patch
* videoio_ffmpeg_avoid_memory_leaks.patch
OBS-URL: https://build.opensuse.org/request/show/983700
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=33
2022-06-27 18:05:05 +02:00
|
|
|
%post -n libopencv_gapi%{soname} -p /sbin/ldconfig
|
|
|
|
|
%postun -n libopencv_gapi%{soname} -p /sbin/ldconfig
|
2020-11-03 06:17:42 +01:00
|
|
|
%post -n libopencv_highgui%{soname} -p /sbin/ldconfig
|
|
|
|
|
%postun -n libopencv_highgui%{soname} -p /sbin/ldconfig
|
|
|
|
|
%post -n libopencv_imgcodecs%{soname} -p /sbin/ldconfig
|
|
|
|
|
%postun -n libopencv_imgcodecs%{soname} -p /sbin/ldconfig
|
|
|
|
|
%post -n libopencv_objdetect%{soname} -p /sbin/ldconfig
|
|
|
|
|
%postun -n libopencv_objdetect%{soname} -p /sbin/ldconfig
|
Accepting request 983700 from home:StefanBruens:branches:science
- update to 4.6.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version460
* OpenCV project infrastructure migrating on GitHub Actions
workflows for CI and release purposes
* Added support for GCC 12, Clang 15
* Added support for FFmpeg 5.0
* DNN module patches:
+ Improved layers / activations / supported more models:
- LSTM (+CUDA), resize (+ONNX13), Sign, Shrink, Reciprocal,
depth2space, space2depth
- fixes in Reduce, Slice, Expand
+ Disabled floating-point denormals processing #21521
+ Changed layer names in ONNX importer to support "output"
entities properly
+ Added TIM-VX NPU backend support:
https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU
+ Added Softmax parameter to ClassificationModel
+ Added audio speech recognition sample (C++) #21458
+ Intel® Inference Engine backend (OpenVINO):
- added initial support for OpenVINO 2022.1 release
- removed support of legacy API (dropped since 2020.3)
* G-API module:
+ G-API framework:
- Introduced a Grayscale image format support for
cv::MediaFrame: #21511;
- Enabeled .reshape() support in the CPU backend: #21669;
- Fixed possible hang in streaming execution mode with constant
inputs: #21567;
- Introduced proper error/exception propagation in the
asynchronous streaming execution mode: #21660;
- Fixed new stream event handling: #21731.
+ Fluid backend:
- Fixed horizontal pass in the Resize kernel, fixed Valgrind
issues: #21144;
- Extended Resize kernel with F32 version: #21678,
added AVX: #21728.
- Enabled dynamic dispatch for Split4 kernel: #21520;
- Enabled dynamic dispatch for Merge3 kernel: #21529;
- Added a SIMD version for DivC kernel: #21474;
- Added a SIMD version for DivRC kernel: #21530;
- Enabled dynamic dispatch for Add kernel: #21686;
- Enabled dynamic dispatch for Sub kernel: #21746;
- Added a SIMD version for ConvertTo kernel: #21777;
- Fixed kernel matrix size for Sobel kernel: #21613.
+ Intel® OpenVINO™ inference backend:
- Fixed NV12 format support for remote memory when OpenVINO
remote context is used: #21424.
- Implemented correct error handling in the backend: #21579.
- Fixed ngraph warnings #21362.
+ OpenCV AI Kit backend:
- Introduced a new backend to program OpenCV AI Kit boards via
G-API. Currently the backend is in experimental state, but allows
to build Camera+NN pipeline and supports heterogeneity (mixing
with host-side code): #20785, #21504.
+ Media integration:
- Enabled GPU inference with oneVPL and DirectX11 on Windows in
Intel OpenVINO inference backend: #21232, #21618, #21658, #21687,
#21688. Now GPU textures decoded by oneVPL decoder can be
preprocessed and inferred on GPU with no extra host processing.
- Enabled oneVPL support on Linux: #21883.
- Extended GStreamer pipeline source with Grayscale image format
support: #21560.
+ Python bindings:
- Exposed GStreamer pipeline source in Python bindings: #20832.
- Fixed Python bindings for CudaBufferPool, cudacodec and cudastereo
modules in OpenCV Contrib.
+ Samples:
- Introduced a pipeline modelling tool for cascaded model
benchmarking: #21477, #21636, #21719. The tool supports a
declarative YAML-based config to describe pipelines with simulated
pre-/post-processing. The tool collects and reports latency and
throughput information for the modelled pipeline.
+ Other changes and fixes:
- Moved GKernelPackage into cv:: namespace by default, its cv::gapi::
alias remain for compatibility: #21318;
- Moved Resize kernel from core to imgproc kernel packages for
CPU, OpenCL, and Fluid backends: #21157. Also moved tests
appropriately: #21475;
- Avoided sporadic test failures in DivC: #21626;
- Fixed 1D Mat handling in the framework: #21782;
- Reduced the number of G-API generated accuracy tests: #21909.
- Drop upstream patches:
* 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
* videoio_initial_FFmpeg_5_0_support.patch
* videoio_ffmpeg_avoid_memory_leaks.patch
OBS-URL: https://build.opensuse.org/request/show/983700
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=33
2022-06-27 18:05:05 +02:00
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2010-03-08 18:16:50 +01:00
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%license LICENSE LICENSE.contrib
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Accepting request 714221 from science
- Update to version 4.1.0
* DNN module:
+ Reduced peak memory consumption for some models up to 30%.
+ Inference Engine
- Inference Engine 2018R3 is now a minimal supported version of IE.
- Myriad X (Intel® Neural Compute Stick 2) is now supported and tested.
- Automatic IR network reshaping for different inputs.
- Improved samples to work with models from OpenVINO Open Model Zoo
+ New networks from TensorFlow Object Detection API: Faster-RCNNs, SSDs
and Mask-RCNN with dilated convolutions, FPN SSD
* Performance improvements:
+ More optimization using AVX2 instruction set.
+ Automatic runtime dispatching is available for large set of functions
from core and imgproc modules.
* Other improvements:
+ Matplotlib Perceptually Uniform Sequential colormaps
+ Add keypoints matching visualization for real-time pose estimation tutorial
+ Add Hand-Eye calibration methods
+ Java: improved support for multidimensional arrays (Mat)
+ Dynamically loaded videoio backends (FFmpeg, GStreamer)
+ opencv_contrib: Robust local optical flow (RLOF) implementations
+ opencv_contrib: Implementation of Quasi Dense Stereo algorithm
+ opencv_contrib: New module: Image Quality Analysis (IQA) API
+ opencv_contrib: BRISQUE No Reference Image Quality Assessment (IQA) API
Check https://github.com/opencv/opencv/wiki/ChangeLog#version410
- Update to version 4.0.0
* A lot of C API from OpenCV 1.x has been removed. The affected modules are
objdetect, photo, video, videoio, imgcodecs, calib3d.
* Persistence (storing and loading structured data to/from XML, YAML or JSON)
in the core module has been completely reimplemented.
* OpenCV is now C++11 library and requires C++11-compliant compiler.
Thanks to the extended C++11 standard library, we could get rid of hand-crafted
cv::String and cv::Ptr. Now cv::String == std::string and cv::Ptr is a thin
wrapper on top of std::shared_ptr. Also, on Linux/BSD for cv::parallel_for_
we now use std::thread's instead of pthreads.
* DNN improvements
* Completely new module opencv_gapi has been added. It is the engine for very
efficient image processing, based on lazy evaluation and on-fly construction.
* Performance improvements
A few hundreds of basic kernels in OpenCV have been rewritten using so-called
"wide universal intrinsics". Those intrinsics map to SSE2, SSE4, AVX2, NEON or
VSX intrinsics, depending on the target platform and the compile flags.
* QR code detector and decoder have been added to opencv/objdetect module.
* The popular Kinect Fusion algorithm has been implemented, optimized for CPU and
GPU (OpenCL), and integrated into opencv_contrib/rgbd module.
* Very efficient and yet high-quality DIS dense optical flow algorithm has been
moved from opencv_contrib to opencv, video module. See the example.
* The slower TV L1 optical flow algorithm has been moved to opencv_contrib.
Check https://github.com/opencv/opencv/wiki/ChangeLog#version400
- Drop obsolete opencv-lib_suffix.patch
- Add 0001-Handle-absolute-OPENCV_INCLUDE_INSTALL_PATH-correctl.patch
- As this is a major version upgrade, the old 3.4.x package is still
available as opencv3
- Update to 3.4.3
* Compatibility fixes with python 3.7
* Added a new computational target DNN_TARGET_OPENCL_FP16
* Extended support of Intel's Inference Engine backend
* Enabled import of Intel's OpenVINO pre-trained networks from
intermediate representation (IR).
* tutorials improvements
Check https://github.com/opencv/opencv/wiki/ChangeLog#version343
for the complete changelog.
- Drop fix-build-i386-nosse.patch, build-workaround-issues-with-c.patch
(fixed upstream)
- Refresh patches
- Add patch to fix use of headers from C:
* build-workaround-issues-with-c.patch
- Update to 3.4.1:
* Added support for quantized TensorFlow networks
* OpenCV is now able to use Intel DL inference engine as DNN
acceleration backend
* Added AVX-512 acceleration to the performance-critical kernels
* For more information, read
https://github.com/opencv/opencv/wiki/ChangeLog#version341
- Update contrib modules to 3.4.1:
* No changelog available
- Change mechanism the contrib modules are built
- Include LICENSE of contrib tarball as well
- Build with python3 on >= 15
- Add patch to fix build on i386 without SSE:
* fix-build-i386-nosse.patch
- Refresh patches:
* fix_processor_detection_for_32bit_on_64bit.patch
* opencv-build-compare.patch
- Mention all libs explicitly
- Rebase 3.4.0 update from i@marguerite.su
- update to 3.4.0
* Added faster R-CNN support
* Javascript bindings have been extended to
cover DNN module
* DNN has been further accelerated for iGPU
using OpenCL
* On-disk caching of precompiled OpenCL
kernels has been finally implemented
* possible to load and run pre-compiled
OpenCL kernels via T-API
* Bit-exact 8-bit and 16-bit resize has been
implemented (currently supported only
bilinear interpolation)
- update face module to 3.4.0
- add opencv-lib_suffix.patch, remove LIB_SUFFIX
from OPENCV_LIB_INSTALL_PATH, as CMAKE_INSTALL
_LIBDIR is arch dependent.
- Add option to build without openblas
- Add conditionals for python2 and python3 to allow us enabling
only desired python variants when needed
- Do not depend on sphinx as py2 and py3 seem to collide there
- Readd opencv-gles.patch, it is *not* included upstream; otherwise
build breaks on all GLES Qt5 platforms (armv6l, armv7l, aarch64)
- add fix_processor_detection_for_32bit_on_64bit.patch
- Correctly set optimizations and dynamic dispatch on ARM, use
OpenCV 3.3 syntax on x86.
- Update licensing information
- change requires of python-numpy-devel to build in Leap and
to not break factory in future
- fix build error/unresolvable for Leap 42.2 and 42.3
- Update to version 3.3.1:
* Lots of various bugfixes
- Update source url
- Rename python subpackage to python2
- Do not explicitly require python-base for python subpackages
- Update to 3.3
- Dropped obsolete patches
* opencv-gcc6-fix-pch-support-PR8345.patch
* opencv-gles.patch
- Updated opencv-build-compare.patch
- Add 0001-Do-not-include-glx.h-when-using-GLES.patch
Fix build for 32bit ARM, including both GLES and desktop GL headers
causes incompatible pointer type errors
- Add conditional for the qt5/qt4 integration
* This is used only for gui tools, library is not affected
- Add provides/obsoletes for the qt5 packages to allow migration
- Drop patch opencv-qt5-sobump.diff
* Used only by the obsoleted qt5 variant
- Cleanup a bit with spec-cleaner
- Use %cmake macros
- Remove the conditions that are not really needed
- Add tests conditional disabled by default
* Many tests fail and there are missing testdata
- Switch to pkgconfig style dependencies
- Update to OpenCV 3.2.0
- Results from 11 GSoC 2016 projects have been submitted to the library:
+ sinusoidal patterns for structured light and phase unwrapping module
[Ambroise Moreau (Delia Passalacqua)]
+ DIS optical flow (excellent dense optical flow algorithm that is both
significantly better and significantly faster than Farneback’s algorithm –
our baseline), and learning-based color constancy algorithms implementation
[Alexander Bokov (Maksim Shabunin)]
+ CNN based tracking algorithm (GOTURN) [Tyan Vladimir (Antonella Cascitelli)]
+ PCAFlow and Global Patch Collider algorithms implementation
[Vladislav Samsonov (Ethan Rublee)]
+ Multi-language OpenCV Tutorials in Python, C++ and Java
[João Cartucho (Vincent Rabaud)]
+ New camera model and parallel processing for stitching pipeline
[Jiri Horner (Bo Li)]
+ Optimizations and improvements of dnn module
[Vitaliy Lyudvichenko (Anatoly Baksheev)]
+ Base64 and JSON support for file storage. Use names like
“myfilestorage.xml?base64” when writing file storage to store big chunks of
numerical data in base64-encoded form. [Iric Wu (Vadim Pisarevsky)]
+ tiny_dnn improvements and integration
[Edgar Riba (Manuele Tamburrano, Stefano Fabri)]
+ Quantization and semantic saliency detection with tiny_dnn
[Yida Wang (Manuele Tamburrano, Stefano Fabri)]
+ Word-spotting CNN based algorithm
[Anguelos Nicolaou (Lluis Gomez)]
- Contributions besides GSoC:
+ Greatly improved and accelerated dnn module in opencv_contrib:
- Many new layers, including deconvolution, LSTM etc.
- Support for semantic segmentation and SSD networks with samples.
- TensorFlow importer + sample that runs Inception net by Google.
+ More image formats and camera backends supported
+ Interactive camera calibration app
+ Multiple algorithms implemented in opencv_contrib
+ Supported latest OSes, including Ubuntu 16.04 LTS and OSX 10.12
+ Lot’s of optimizations for IA and ARM archs using parallelism, vector
instructions and new OpenCL kernels.
+ OpenCV now can use vendor-provided OpenVX and LAPACK/BLAS (including Intel MKL,
Apple’s Accelerate, OpenBLAS and Atlas) for acceleration
- Refreshed opencv-build-compare.patch
- Dropped upstream opencv-gcc5.patch
- Replace opencv-gcc6-disable-pch.patch with upstream patch
opencv-gcc6-fix-pch-support-PR8345.patch
- Enable TBB support (C++ threading library)
- Add dependency on openBLAS
- Enable ffmpeg support unconditional
- In case we build using GCC6 (or newer), add -mlra to CFLAGS to
workaround gcc bug
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=71294.
- Apply upstream patch opencv-gcc6-disable-pch.patch to disable
PCH for GCC6.
- Test for python versions greater than or equal to the current
version.
- Add python 3 support
- Added opencv_contrib_face-3.1.0.tar.bz2
* This tarball is created to take only the face module from the
contrib package. The Face module is required by libkface, which
in its turn is required by digikam.
- Added _constraints file to avoid random failures on small workers
(at least for builds on PMBS)
- Update to OpenCV 3.1.0
- A lot of new functionality has been introduced during Google
Summer of Code 2015:
+ “Omnidirectional Cameras Calibration and Stereo 3D
Reconstruction” – opencv_contrib/ccalib module
(Baisheng Lai, Bo Li)
+ “Structure From Motion” – opencv_contrib/sfm module
(Edgar Riba, Vincent Rabaud)
+ “Improved Deformable Part-based Models” – opencv_contrib/dpm
module (Jiaolong Xu, Bence Magyar)
+ “Real-time Multi-object Tracking using Kernelized Correlation
Filter” – opencv_contrib/tracking module
(Laksono Kurnianggoro, Fernando J. Iglesias Garcia)
+ “Improved and expanded Scene Text Detection” –
opencv_contrib/text module (Lluis Gomez, Vadim Pisarevsky)
+ “Stereo correspondence improvements” – opencv_contrib/stereo
module (Mircea Paul Muresan, Sergei Nosov)
+ “Structured-Light System Calibration” –
opencv_contrib/structured_light (Roberta Ravanelli,
Delia Passalacqua, Stefano Fabri, Claudia Rapuano)
+ “Chessboard+ArUco for camera calibration” –
opencv_contrib/aruco (Sergio Garrido, Prasanna, Gary Bradski)
+ “Implementation of universal interface for deep neural
network frameworks” – opencv_contrib/dnn module
(Vitaliy Lyudvichenko, Anatoly Baksheev)
+ “Recent advances in edge-aware filtering, improved SGBM
stereo algorithm” – opencv/calib3d and opencv_contrib/ximgproc
(Alexander Bokov, Maksim Shabunin)
+ “Improved ICF detector, waldboost implementation” –
opencv_contrib/xobjdetect (Vlad Shakhuro, Alexander Bovyrin)
+ “Multi-target TLD tracking” – opencv_contrib/tracking module
(Vladimir Tyan, Antonella Cascitelli)
+ “3D pose estimation using CNNs” – opencv_contrib/cnn_3dobj
(Yida Wang, Manuele Tamburrano, Stefano Fabri)
- Many great contributions made by the community, such as:
+ Support for HDF5 format
+ New/Improved optical flow algorithms
+ Multiple new image processing algorithms for filtering,
segmentation and feature detection
+ Superpixel segmentation and much more
- IPPICV is now based on IPP 9.0.1, which should make OpenCV
even faster on modern Intel chips
- opencv_contrib modules can now be included into the
opencv2.framework for iOS
- Newest operating systems are supported: Windows 10 and
OSX 10.11 (Visual Studio 2015 and XCode 7.1.1)
- Interoperability between T-API and OpenCL, OpenGL, DirectX and
Video Acceleration API on Linux, as well as Android 5 camera.
- HAL (Hardware Acceleration Layer) module functionality has been
moved into corresponding basic modules; the HAL replacement
mechanism has been implemented along with the examples
- Removed improve-sphinx-search.diff, opencv-altivec-vector.patch,
opencv-pkgconfig.patch and opencv-samples.patch, fixed upstream.
- Fixed opencv-qt5-sobump.diff, opencv-build-compare.patch,
opencv-gcc5.patch and opencv-gles.patch.
- Version OpenCV 3.0.0
+ ~1500 patches, submitted as PR @ github. All our patches go
the same route.
+ opencv_contrib (http://github.com/itseez/opencv_contrib)
repository has been added. A lot of new functionality is there
already! opencv_contrib is only compatible with 3.0/master,
not 2.4. Clone the repository and use “cmake …
-D OPENCV_EXTRA_MODULES_PATH=<path_to opencv_contrib/modules> …”
to build opencv and opencv_contrib together.
+ a subset of Intel IPP (IPPCV) is given to us and our users free
of charge, free of licensing fees, for commercial and
non-commerical use. It’s used by default in x86 and x64 builds
on Windows, Linux and Mac.
+ T-API (transparent API) has been introduced, this is transparent
GPU acceleration layer using OpenCL. It does not add any
compile-time or runtime dependency of OpenCL. When OpenCL is
available, it’s detected and used, but it can be disabled at
compile time or at runtime. It covers ~100 OpenCV functions.
This work has been done by contract and with generous support
from AMD and Intel companies.
+ ~40 OpenCV functions have been accelerated using NEON intrinsics
and because these are mostly basic functions, some higher-level
functions got accelerated as well.
+ There is also new OpenCV HAL layer that will simplifies creation
of NEON-optimized code and that should form a base for the
open-source and proprietary OpenCV accelerators.
+ The documentation is now in Doxygen: http://docs.opencv.org/master/
+ We cleaned up API of many high-level algorithms from features2d,
calib3d, objdetect etc. They now follow the uniform
“abstract interface – hidden implementation” pattern and make
extensive use of smart pointers (Ptr<>).
+ Greatly improved and extended Python & Java bindings (also,
see below on the Python bindings), newly introduced Matlab
bindings (still in alpha stage).
+ Improved Android support – now OpenCV Manager is in Java and
supports both 2.4 and 3.0.
+ Greatly improved WinRT support, including video capturing and
multi-threading capabilities. Thanks for Microsoft team for this!
+ Big thanks to Google who funded several successive GSoC programs
and let OpenCV in. The results of many successful GSoC 2013 and
2014 projects have been integrated in opencv 3.0 and
opencv_contrib (earlier results are also available in
OpenCV 2.4.x). We can name:
- text detection
- many computational photography algorithms (HDR, inpainting,
edge-aware filters, superpixels, …)
- tracking and optical flow algorithms
- new features, including line descriptors, KAZE/AKAZE
- general use optimization (hill climbing, linear programming)
- greatly improved Python support, including Python 3.0 support,
many new tutorials & samples on how to use OpenCV with Python.
- 2d shape matching module and 3d surface matching module
- RGB-D module
- VTK-based 3D visualization module
- etc.
+ Besides Google, we enjoyed (and hope that you will enjoy too)
many useful contributions from community, like:
- biologically inspired vision module
- DAISY features, LATCH descriptor, improved BRIEF
- image registration module
- etc.
- Reduce build-compare noise
opencv-build-compare.patch
- Remove BuildRequirement for python-sphinx in SLE12, since it's
not available there and it's not a mandatory requirement.
- Reduce differences between two spec files
- Use pkgconfig for ffmpeg BuildRequires
- Update improve-sphinx-search.diff for new python-Sphinx(1.3.1)
* now that sphinx-build disallow executing without arguments and
give you "Insufficient arguments" error, use "sphinx-build -h"
instead
* the default usages output ie. sphinx-build(or --help) no longer
are standard error but standard output, drop OUTPUT_QUIET and
add OUTPUT_VARIABLE throws the output to SPHINX_OUTPUT as well
- support gcc 5 (i.e. gcc versions without minor version):
opencv-gcc5.patch
- Update to OpenCV 2.4.11 - can't find NEWS or Changelog
merely collecting bug fixes while 3.0 is in the making, 2.4.11
didn't even make it on their web page, it's only on download
server
- remove opencv-underlinking.patch as obsolete
- remove upstream patch bomb_commit_gstreamer-1x-support.patch
- commenting out opencv-pkgconfig.patch - possibly it requires a rebase,
but the problem it tries to solve is unclear
- Add specific buildrequires for libpng15, so that we are
building against the system provided libpng.
- Update to OpenCV 2.4.9
More info at:
http://opencv.org/opencv-2-4-9-is-out.html
The brief list of changes:
* new 3D visualization module ‘viz’;
* performance fixes in ‘ocl’ module;
* fixes in Android Camera;
* improved CUDA support for mobile platforms;
* bugfixes from community;
* 55 reported bugs have been closed;
* 156 pull requests have been merged.
- Drop the BuildRequires on libucil and libunicap for Factory. This
stops us from getting ride of Gstreamer 0.10 and besides these two
libraries seem to be unmaintained upstream as that the latest
actions are from 2010
- Add upstream patch (3.0 version) to support Gstreamer 1.x
* bomb_commit_gstreamer-1x-support.patch
- Upstream now provides tarballs with source only as git tags
from github so update Source0 path.
- Add requires on various X extensions linked to opencv_ts module.
As those are present in the .pc file we need it anyway.
- Update to OpenCV 2.4.8
More info at:
http://opencv.org/opencv-2-4-8.html
The brief list of changes:
* NVidia CUDA support on Android devices with CUDA capable SoC and
CUDA sample;
* Concurrent kernel execution and user defined context support for
OpenCL;
* Integration with Intel Perceptual SDK and new depth sensors support
for Windows;
* 32 reported bugs have been closed;
* 139 pull requests have been merged;
- Fix build with altivec:
opencv-altivec-vector.patch
- Added opencv-pkgconfig.patch: make sure to provide link flags in
OpenCV pc file (bnc#853036)
- Update to OpenCV 2.4.7
More info at:
http://opencv.org/opencv-2-4-7-is-out.html
The brief list of changes:
* dynamic OpenCL runtime loading, setting default OpenCL device
via env var, many bug-fixes and some new optimization with OpenCL
* bug-fixes and new optimizations in CUDA stuff
* latest NDK and Android OS support, Native Android Camera tuning
* minor fixes, XAML sample and MS Certification compatibility
in WinRT stuff
* 382 pull requests have been merged
* 54 reported bugs have been fixed
- Added pkgconfig(glu) Requires to devel package, as per .pc file
- Make devel package provides also devel-static one
- Drop assume-Sphinx-is-there.diff, and add improve-sphinx-search.diff,
for properly finding sphinx with alphabetic chars in version
- Add patch assume-Sphinx-is-there.diff to fix building with
Sphinx versions that have alphanumeric characters in the version
(Only for factory builds at the moment)
- Use eigen3 instead of eigen2 as build requirement for openSUSE > 12.3.
- Enable compilation with libucil and libunicap.
- Removed dos2unix build requirement (not needed anymore).
- Update to OpenCV 2.4.6.1
More info at:
http://opencv.org/opencv-2-4-6-is-out.html
The brief list of changes:
* added video file i/o Windows RT and sample application using
camera, enabled parallelization with TBB or MS Concurrency
* added CUDA 5.5 support for desktop and ARM systems
* added Qt 5 support
* added many new OpenCL algorithms ports, included OpenCL binaries
into the Windows superpack
* iOS build scripts (together with Android ones) moved to
‘opencv/platforms’ directory
* added functions for UIImage <-> cv::Mat conversion
* correct front/back camera selection in Android app framework
* added Linaro NDK support and fixes for MIPS to Android CMake
toolchain
* stability has been improved by a lot, numerous bug-fixes across
all the library
- build with LFS_CFLAGS in 32 bit archs.
- Disable SSE3 for all architectures (bnc#814333)
- Disable SSE(2) on non x86_64 architectures, causes crashing
kde#276923, bnc#789173
- Update to OpenCV 2.4.5
More info at:
http://opencv.org/opencv-2-4-5-is-out.html
The brief list of changes:
* experimental WinRT support
* new video super-resolution module
* CLAHE (adaptive histogram equalization) algorithm on both CPU
and GPU
* further improvements and extensions in ocl module
(stereo block matching and belief propagation have been added,
fixed crashes on Intel HD4000)
* Visual Studio 2012 cv::Mat visualizer plugin debugger tutorial
from Microsoft Research
* OpenCV4Android SDK improvements
(NDK r8e support, native activity sample using OpenCV Manager,
bug-fixes)
* ~25 reported problems have been resolved since 2.4.4, ~78 pull
requests have been merged, thanks everybody who participated!
- Update to OpenCV 2.4.4
More info at:
http://opencv.org/opencv-2-4-4-is-out.html
The brief list of changes:
* OpenCV Java bindings are ported from Android to desktop Java!
Actually any JVM language will work, see Tutorial for details,
and Java or Scala code samples.
* Android application framework, samples, tutorials, and OpenCV
Manager are improved.
* Optimizations for the new NVIDIA Kepler architecture, CARMA
platform support and other new optimizations in CUDA.
* OpenCL module now builds successfully with various SDKs (from
AMD, NVIDIA, Intel and Apple) and runs well on different GPUs
(AMD, NVidia, Intel HD4000). A lot of new functionality has been
added, tons of bugs fixed, performance of many functions has
been significantly improved.
* 100+ reported problems have been resolved since 2.4.3, thanks
everybody who participated!
- Drop the buildrequire for libxine
- Update to OpenCV 2.4.3
More info at:
http://opencv.org/opencv-2-4-3-released.html
The nicely formatted changelog can be seen here:
http://code.opencv.org/projects/opencv/wiki/ChangeLog;
here are the highlights:
* A lot of good stuff from the Google Summer of Code 2012 has been
integrated; this was a very productive summer!
* Significantly improved and optimized Android and iOS ports.
* Greatly extended GPU (i.e. CUDA-based) module.
* The brand new ocl (OpenCL-based) module that unleashes GPU power
also for AMD and Intel GPU users. It’s not included into the
binary package, since there are different SDKs, and it’s not
turned on by default. You need to run CMake and turn on
“WITH_OPENCL”. Also, please note that this is very first version
of the module, so it may be not very stable and not very
functional.
* Much better performance on many-core systems out of the box. You
do not need TBB anymore on MacOSX, iOS and Windows. BTW, the
binary package for Windows is now built without TBB support.
Libraries and DLLs for Visual Studio 2010 use the Concurrency
framework.
* About 130 bugs have been fixed since 2.4.2.
* Since 2.4.3rc we fixed several more problems, in particular some
compile problems with iOS 6 SDK.
- buildrequire glu
- Update to OpenCV 2.4.2
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Drop opencv-datadir.patch to comply with upstream directory layout
- Update to OpenCV 2.4.1
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Update to OpenCV 2.4.0
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Add opencv-gcc47.patch: Fix build with gcc 4.7.
- Use Explicit Buildrequires on several needed libraries
future dependency cleanups may/will cause build to fail otherwise.
- Add upstream r6881 to fix clang compatibility
- uncomment libraries not in 12.1 for now
- Changed groups (fix for RPMLINT warning)
- Added check for duplicate files (fix for RPMLINT warning)
- Added py_requires macros and python-base dependencies (fix for RPMLINT warning)
- Escaped macros (fix for RPMLINT warning)
- Fixed end-of-line encoding problems (fix for RPMLINT warning)
- Added libeigen2-devel buildrequires
- Added libunicap and libucil buildrequires (libunicap supports requires libucil)
- Cleaned up spec file formatting
- Dropped opencv-2.3-ffmpeg.patch, applied upstream
- Revive opencv-2.3-ffmpeg.patch, needs rebase
- Tag all patches according to openSUSE packaging guidelines
- Removed opencv-2.3-cmake.patch, old cmake cannot be used any more.
- Python bindings cannot be built without NumPy any more.
- Update to OpenCV 2.3.1
- Update and readd opencv-2.3-underlinking.patch since it is still
necessary.
- Fix support for new ffmpeg versions
- Removed unnecessary patches
- Enable Python NumPy support on openSUSE 11.2
- Build Qt instead of Gtk GUI
- Fix cmake files for openSUSE 11.1
- No GStreamer support on openSUSE 11.1
- Update to OpenCV 2.3.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Fix build on openSUSE 11.2
- Add opencv-v4l-2.6.38.patch: use the new libv4l2 interface
- Enable Python NumPy support
- SWIG is not required any more
- Enable OpenEXR support
- Update to OpenCV 2.2.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Use system zlib, oh, and do not export ZLIB symbols to
other applications, clashes ensued.
- fix build with gcc 4.6
- add -underlinking patch
- devel package renamed to opencv-devel, so that switching between
OBS and packman opencv packages is easier
- fix gstreamer support
- fix xine support
- fix some rpmlint warnings
- fix shared libraries permissions
- Do not waste resources building the tests as we do not run them
- Do not disable SSE,SSE2,etc. According to OpenCV changelog,
it should be safe to leave these enabled.
- fix build on openSUSE 11.0
- Update to OpenCV 2.1.0:
* The whole OpenCV is now using exceptions instead of the old
libc-style mechanism
* Experimental "static" OpenCV configuration in CMake was
contributed by Jose Luis Blanco.
Pass "BUILD_SHARED_LIBS=OFF" to CMake to build OpenCV statically.
* new improved version of one-way descriptor is added
* User can now control the image areas visible after the stereo
rectification
* Fullscreen has been added (thanks to Yannick Verdie).
* Further info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- fix build with libpng14
- small spec file cleanup
- Moved to the KDE repositories to enable inclusion in kipi-plugins
- Initial package
OBS-URL: https://build.opensuse.org/request/show/714221
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/opencv?expand=0&rev=73
2019-07-17 13:13:58 +02:00
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|
|
%license %{_licensedir}/opencv/*
|
2015-12-16 17:41:36 +01:00
|
|
|
%{_bindir}/opencv_*
|
2020-11-03 06:17:42 +01:00
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%dir %{_datadir}/opencv4
|
Accepting request 714221 from science
- Update to version 4.1.0
* DNN module:
+ Reduced peak memory consumption for some models up to 30%.
+ Inference Engine
- Inference Engine 2018R3 is now a minimal supported version of IE.
- Myriad X (Intel® Neural Compute Stick 2) is now supported and tested.
- Automatic IR network reshaping for different inputs.
- Improved samples to work with models from OpenVINO Open Model Zoo
+ New networks from TensorFlow Object Detection API: Faster-RCNNs, SSDs
and Mask-RCNN with dilated convolutions, FPN SSD
* Performance improvements:
+ More optimization using AVX2 instruction set.
+ Automatic runtime dispatching is available for large set of functions
from core and imgproc modules.
* Other improvements:
+ Matplotlib Perceptually Uniform Sequential colormaps
+ Add keypoints matching visualization for real-time pose estimation tutorial
+ Add Hand-Eye calibration methods
+ Java: improved support for multidimensional arrays (Mat)
+ Dynamically loaded videoio backends (FFmpeg, GStreamer)
+ opencv_contrib: Robust local optical flow (RLOF) implementations
+ opencv_contrib: Implementation of Quasi Dense Stereo algorithm
+ opencv_contrib: New module: Image Quality Analysis (IQA) API
+ opencv_contrib: BRISQUE No Reference Image Quality Assessment (IQA) API
Check https://github.com/opencv/opencv/wiki/ChangeLog#version410
- Update to version 4.0.0
* A lot of C API from OpenCV 1.x has been removed. The affected modules are
objdetect, photo, video, videoio, imgcodecs, calib3d.
* Persistence (storing and loading structured data to/from XML, YAML or JSON)
in the core module has been completely reimplemented.
* OpenCV is now C++11 library and requires C++11-compliant compiler.
Thanks to the extended C++11 standard library, we could get rid of hand-crafted
cv::String and cv::Ptr. Now cv::String == std::string and cv::Ptr is a thin
wrapper on top of std::shared_ptr. Also, on Linux/BSD for cv::parallel_for_
we now use std::thread's instead of pthreads.
* DNN improvements
* Completely new module opencv_gapi has been added. It is the engine for very
efficient image processing, based on lazy evaluation and on-fly construction.
* Performance improvements
A few hundreds of basic kernels in OpenCV have been rewritten using so-called
"wide universal intrinsics". Those intrinsics map to SSE2, SSE4, AVX2, NEON or
VSX intrinsics, depending on the target platform and the compile flags.
* QR code detector and decoder have been added to opencv/objdetect module.
* The popular Kinect Fusion algorithm has been implemented, optimized for CPU and
GPU (OpenCL), and integrated into opencv_contrib/rgbd module.
* Very efficient and yet high-quality DIS dense optical flow algorithm has been
moved from opencv_contrib to opencv, video module. See the example.
* The slower TV L1 optical flow algorithm has been moved to opencv_contrib.
Check https://github.com/opencv/opencv/wiki/ChangeLog#version400
- Drop obsolete opencv-lib_suffix.patch
- Add 0001-Handle-absolute-OPENCV_INCLUDE_INSTALL_PATH-correctl.patch
- As this is a major version upgrade, the old 3.4.x package is still
available as opencv3
- Update to 3.4.3
* Compatibility fixes with python 3.7
* Added a new computational target DNN_TARGET_OPENCL_FP16
* Extended support of Intel's Inference Engine backend
* Enabled import of Intel's OpenVINO pre-trained networks from
intermediate representation (IR).
* tutorials improvements
Check https://github.com/opencv/opencv/wiki/ChangeLog#version343
for the complete changelog.
- Drop fix-build-i386-nosse.patch, build-workaround-issues-with-c.patch
(fixed upstream)
- Refresh patches
- Add patch to fix use of headers from C:
* build-workaround-issues-with-c.patch
- Update to 3.4.1:
* Added support for quantized TensorFlow networks
* OpenCV is now able to use Intel DL inference engine as DNN
acceleration backend
* Added AVX-512 acceleration to the performance-critical kernels
* For more information, read
https://github.com/opencv/opencv/wiki/ChangeLog#version341
- Update contrib modules to 3.4.1:
* No changelog available
- Change mechanism the contrib modules are built
- Include LICENSE of contrib tarball as well
- Build with python3 on >= 15
- Add patch to fix build on i386 without SSE:
* fix-build-i386-nosse.patch
- Refresh patches:
* fix_processor_detection_for_32bit_on_64bit.patch
* opencv-build-compare.patch
- Mention all libs explicitly
- Rebase 3.4.0 update from i@marguerite.su
- update to 3.4.0
* Added faster R-CNN support
* Javascript bindings have been extended to
cover DNN module
* DNN has been further accelerated for iGPU
using OpenCL
* On-disk caching of precompiled OpenCL
kernels has been finally implemented
* possible to load and run pre-compiled
OpenCL kernels via T-API
* Bit-exact 8-bit and 16-bit resize has been
implemented (currently supported only
bilinear interpolation)
- update face module to 3.4.0
- add opencv-lib_suffix.patch, remove LIB_SUFFIX
from OPENCV_LIB_INSTALL_PATH, as CMAKE_INSTALL
_LIBDIR is arch dependent.
- Add option to build without openblas
- Add conditionals for python2 and python3 to allow us enabling
only desired python variants when needed
- Do not depend on sphinx as py2 and py3 seem to collide there
- Readd opencv-gles.patch, it is *not* included upstream; otherwise
build breaks on all GLES Qt5 platforms (armv6l, armv7l, aarch64)
- add fix_processor_detection_for_32bit_on_64bit.patch
- Correctly set optimizations and dynamic dispatch on ARM, use
OpenCV 3.3 syntax on x86.
- Update licensing information
- change requires of python-numpy-devel to build in Leap and
to not break factory in future
- fix build error/unresolvable for Leap 42.2 and 42.3
- Update to version 3.3.1:
* Lots of various bugfixes
- Update source url
- Rename python subpackage to python2
- Do not explicitly require python-base for python subpackages
- Update to 3.3
- Dropped obsolete patches
* opencv-gcc6-fix-pch-support-PR8345.patch
* opencv-gles.patch
- Updated opencv-build-compare.patch
- Add 0001-Do-not-include-glx.h-when-using-GLES.patch
Fix build for 32bit ARM, including both GLES and desktop GL headers
causes incompatible pointer type errors
- Add conditional for the qt5/qt4 integration
* This is used only for gui tools, library is not affected
- Add provides/obsoletes for the qt5 packages to allow migration
- Drop patch opencv-qt5-sobump.diff
* Used only by the obsoleted qt5 variant
- Cleanup a bit with spec-cleaner
- Use %cmake macros
- Remove the conditions that are not really needed
- Add tests conditional disabled by default
* Many tests fail and there are missing testdata
- Switch to pkgconfig style dependencies
- Update to OpenCV 3.2.0
- Results from 11 GSoC 2016 projects have been submitted to the library:
+ sinusoidal patterns for structured light and phase unwrapping module
[Ambroise Moreau (Delia Passalacqua)]
+ DIS optical flow (excellent dense optical flow algorithm that is both
significantly better and significantly faster than Farneback’s algorithm –
our baseline), and learning-based color constancy algorithms implementation
[Alexander Bokov (Maksim Shabunin)]
+ CNN based tracking algorithm (GOTURN) [Tyan Vladimir (Antonella Cascitelli)]
+ PCAFlow and Global Patch Collider algorithms implementation
[Vladislav Samsonov (Ethan Rublee)]
+ Multi-language OpenCV Tutorials in Python, C++ and Java
[João Cartucho (Vincent Rabaud)]
+ New camera model and parallel processing for stitching pipeline
[Jiri Horner (Bo Li)]
+ Optimizations and improvements of dnn module
[Vitaliy Lyudvichenko (Anatoly Baksheev)]
+ Base64 and JSON support for file storage. Use names like
“myfilestorage.xml?base64” when writing file storage to store big chunks of
numerical data in base64-encoded form. [Iric Wu (Vadim Pisarevsky)]
+ tiny_dnn improvements and integration
[Edgar Riba (Manuele Tamburrano, Stefano Fabri)]
+ Quantization and semantic saliency detection with tiny_dnn
[Yida Wang (Manuele Tamburrano, Stefano Fabri)]
+ Word-spotting CNN based algorithm
[Anguelos Nicolaou (Lluis Gomez)]
- Contributions besides GSoC:
+ Greatly improved and accelerated dnn module in opencv_contrib:
- Many new layers, including deconvolution, LSTM etc.
- Support for semantic segmentation and SSD networks with samples.
- TensorFlow importer + sample that runs Inception net by Google.
+ More image formats and camera backends supported
+ Interactive camera calibration app
+ Multiple algorithms implemented in opencv_contrib
+ Supported latest OSes, including Ubuntu 16.04 LTS and OSX 10.12
+ Lot’s of optimizations for IA and ARM archs using parallelism, vector
instructions and new OpenCL kernels.
+ OpenCV now can use vendor-provided OpenVX and LAPACK/BLAS (including Intel MKL,
Apple’s Accelerate, OpenBLAS and Atlas) for acceleration
- Refreshed opencv-build-compare.patch
- Dropped upstream opencv-gcc5.patch
- Replace opencv-gcc6-disable-pch.patch with upstream patch
opencv-gcc6-fix-pch-support-PR8345.patch
- Enable TBB support (C++ threading library)
- Add dependency on openBLAS
- Enable ffmpeg support unconditional
- In case we build using GCC6 (or newer), add -mlra to CFLAGS to
workaround gcc bug
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=71294.
- Apply upstream patch opencv-gcc6-disable-pch.patch to disable
PCH for GCC6.
- Test for python versions greater than or equal to the current
version.
- Add python 3 support
- Added opencv_contrib_face-3.1.0.tar.bz2
* This tarball is created to take only the face module from the
contrib package. The Face module is required by libkface, which
in its turn is required by digikam.
- Added _constraints file to avoid random failures on small workers
(at least for builds on PMBS)
- Update to OpenCV 3.1.0
- A lot of new functionality has been introduced during Google
Summer of Code 2015:
+ “Omnidirectional Cameras Calibration and Stereo 3D
Reconstruction” – opencv_contrib/ccalib module
(Baisheng Lai, Bo Li)
+ “Structure From Motion” – opencv_contrib/sfm module
(Edgar Riba, Vincent Rabaud)
+ “Improved Deformable Part-based Models” – opencv_contrib/dpm
module (Jiaolong Xu, Bence Magyar)
+ “Real-time Multi-object Tracking using Kernelized Correlation
Filter” – opencv_contrib/tracking module
(Laksono Kurnianggoro, Fernando J. Iglesias Garcia)
+ “Improved and expanded Scene Text Detection” –
opencv_contrib/text module (Lluis Gomez, Vadim Pisarevsky)
+ “Stereo correspondence improvements” – opencv_contrib/stereo
module (Mircea Paul Muresan, Sergei Nosov)
+ “Structured-Light System Calibration” –
opencv_contrib/structured_light (Roberta Ravanelli,
Delia Passalacqua, Stefano Fabri, Claudia Rapuano)
+ “Chessboard+ArUco for camera calibration” –
opencv_contrib/aruco (Sergio Garrido, Prasanna, Gary Bradski)
+ “Implementation of universal interface for deep neural
network frameworks” – opencv_contrib/dnn module
(Vitaliy Lyudvichenko, Anatoly Baksheev)
+ “Recent advances in edge-aware filtering, improved SGBM
stereo algorithm” – opencv/calib3d and opencv_contrib/ximgproc
(Alexander Bokov, Maksim Shabunin)
+ “Improved ICF detector, waldboost implementation” –
opencv_contrib/xobjdetect (Vlad Shakhuro, Alexander Bovyrin)
+ “Multi-target TLD tracking” – opencv_contrib/tracking module
(Vladimir Tyan, Antonella Cascitelli)
+ “3D pose estimation using CNNs” – opencv_contrib/cnn_3dobj
(Yida Wang, Manuele Tamburrano, Stefano Fabri)
- Many great contributions made by the community, such as:
+ Support for HDF5 format
+ New/Improved optical flow algorithms
+ Multiple new image processing algorithms for filtering,
segmentation and feature detection
+ Superpixel segmentation and much more
- IPPICV is now based on IPP 9.0.1, which should make OpenCV
even faster on modern Intel chips
- opencv_contrib modules can now be included into the
opencv2.framework for iOS
- Newest operating systems are supported: Windows 10 and
OSX 10.11 (Visual Studio 2015 and XCode 7.1.1)
- Interoperability between T-API and OpenCL, OpenGL, DirectX and
Video Acceleration API on Linux, as well as Android 5 camera.
- HAL (Hardware Acceleration Layer) module functionality has been
moved into corresponding basic modules; the HAL replacement
mechanism has been implemented along with the examples
- Removed improve-sphinx-search.diff, opencv-altivec-vector.patch,
opencv-pkgconfig.patch and opencv-samples.patch, fixed upstream.
- Fixed opencv-qt5-sobump.diff, opencv-build-compare.patch,
opencv-gcc5.patch and opencv-gles.patch.
- Version OpenCV 3.0.0
+ ~1500 patches, submitted as PR @ github. All our patches go
the same route.
+ opencv_contrib (http://github.com/itseez/opencv_contrib)
repository has been added. A lot of new functionality is there
already! opencv_contrib is only compatible with 3.0/master,
not 2.4. Clone the repository and use “cmake …
-D OPENCV_EXTRA_MODULES_PATH=<path_to opencv_contrib/modules> …”
to build opencv and opencv_contrib together.
+ a subset of Intel IPP (IPPCV) is given to us and our users free
of charge, free of licensing fees, for commercial and
non-commerical use. It’s used by default in x86 and x64 builds
on Windows, Linux and Mac.
+ T-API (transparent API) has been introduced, this is transparent
GPU acceleration layer using OpenCL. It does not add any
compile-time or runtime dependency of OpenCL. When OpenCL is
available, it’s detected and used, but it can be disabled at
compile time or at runtime. It covers ~100 OpenCV functions.
This work has been done by contract and with generous support
from AMD and Intel companies.
+ ~40 OpenCV functions have been accelerated using NEON intrinsics
and because these are mostly basic functions, some higher-level
functions got accelerated as well.
+ There is also new OpenCV HAL layer that will simplifies creation
of NEON-optimized code and that should form a base for the
open-source and proprietary OpenCV accelerators.
+ The documentation is now in Doxygen: http://docs.opencv.org/master/
+ We cleaned up API of many high-level algorithms from features2d,
calib3d, objdetect etc. They now follow the uniform
“abstract interface – hidden implementation” pattern and make
extensive use of smart pointers (Ptr<>).
+ Greatly improved and extended Python & Java bindings (also,
see below on the Python bindings), newly introduced Matlab
bindings (still in alpha stage).
+ Improved Android support – now OpenCV Manager is in Java and
supports both 2.4 and 3.0.
+ Greatly improved WinRT support, including video capturing and
multi-threading capabilities. Thanks for Microsoft team for this!
+ Big thanks to Google who funded several successive GSoC programs
and let OpenCV in. The results of many successful GSoC 2013 and
2014 projects have been integrated in opencv 3.0 and
opencv_contrib (earlier results are also available in
OpenCV 2.4.x). We can name:
- text detection
- many computational photography algorithms (HDR, inpainting,
edge-aware filters, superpixels, …)
- tracking and optical flow algorithms
- new features, including line descriptors, KAZE/AKAZE
- general use optimization (hill climbing, linear programming)
- greatly improved Python support, including Python 3.0 support,
many new tutorials & samples on how to use OpenCV with Python.
- 2d shape matching module and 3d surface matching module
- RGB-D module
- VTK-based 3D visualization module
- etc.
+ Besides Google, we enjoyed (and hope that you will enjoy too)
many useful contributions from community, like:
- biologically inspired vision module
- DAISY features, LATCH descriptor, improved BRIEF
- image registration module
- etc.
- Reduce build-compare noise
opencv-build-compare.patch
- Remove BuildRequirement for python-sphinx in SLE12, since it's
not available there and it's not a mandatory requirement.
- Reduce differences between two spec files
- Use pkgconfig for ffmpeg BuildRequires
- Update improve-sphinx-search.diff for new python-Sphinx(1.3.1)
* now that sphinx-build disallow executing without arguments and
give you "Insufficient arguments" error, use "sphinx-build -h"
instead
* the default usages output ie. sphinx-build(or --help) no longer
are standard error but standard output, drop OUTPUT_QUIET and
add OUTPUT_VARIABLE throws the output to SPHINX_OUTPUT as well
- support gcc 5 (i.e. gcc versions without minor version):
opencv-gcc5.patch
- Update to OpenCV 2.4.11 - can't find NEWS or Changelog
merely collecting bug fixes while 3.0 is in the making, 2.4.11
didn't even make it on their web page, it's only on download
server
- remove opencv-underlinking.patch as obsolete
- remove upstream patch bomb_commit_gstreamer-1x-support.patch
- commenting out opencv-pkgconfig.patch - possibly it requires a rebase,
but the problem it tries to solve is unclear
- Add specific buildrequires for libpng15, so that we are
building against the system provided libpng.
- Update to OpenCV 2.4.9
More info at:
http://opencv.org/opencv-2-4-9-is-out.html
The brief list of changes:
* new 3D visualization module ‘viz’;
* performance fixes in ‘ocl’ module;
* fixes in Android Camera;
* improved CUDA support for mobile platforms;
* bugfixes from community;
* 55 reported bugs have been closed;
* 156 pull requests have been merged.
- Drop the BuildRequires on libucil and libunicap for Factory. This
stops us from getting ride of Gstreamer 0.10 and besides these two
libraries seem to be unmaintained upstream as that the latest
actions are from 2010
- Add upstream patch (3.0 version) to support Gstreamer 1.x
* bomb_commit_gstreamer-1x-support.patch
- Upstream now provides tarballs with source only as git tags
from github so update Source0 path.
- Add requires on various X extensions linked to opencv_ts module.
As those are present in the .pc file we need it anyway.
- Update to OpenCV 2.4.8
More info at:
http://opencv.org/opencv-2-4-8.html
The brief list of changes:
* NVidia CUDA support on Android devices with CUDA capable SoC and
CUDA sample;
* Concurrent kernel execution and user defined context support for
OpenCL;
* Integration with Intel Perceptual SDK and new depth sensors support
for Windows;
* 32 reported bugs have been closed;
* 139 pull requests have been merged;
- Fix build with altivec:
opencv-altivec-vector.patch
- Added opencv-pkgconfig.patch: make sure to provide link flags in
OpenCV pc file (bnc#853036)
- Update to OpenCV 2.4.7
More info at:
http://opencv.org/opencv-2-4-7-is-out.html
The brief list of changes:
* dynamic OpenCL runtime loading, setting default OpenCL device
via env var, many bug-fixes and some new optimization with OpenCL
* bug-fixes and new optimizations in CUDA stuff
* latest NDK and Android OS support, Native Android Camera tuning
* minor fixes, XAML sample and MS Certification compatibility
in WinRT stuff
* 382 pull requests have been merged
* 54 reported bugs have been fixed
- Added pkgconfig(glu) Requires to devel package, as per .pc file
- Make devel package provides also devel-static one
- Drop assume-Sphinx-is-there.diff, and add improve-sphinx-search.diff,
for properly finding sphinx with alphabetic chars in version
- Add patch assume-Sphinx-is-there.diff to fix building with
Sphinx versions that have alphanumeric characters in the version
(Only for factory builds at the moment)
- Use eigen3 instead of eigen2 as build requirement for openSUSE > 12.3.
- Enable compilation with libucil and libunicap.
- Removed dos2unix build requirement (not needed anymore).
- Update to OpenCV 2.4.6.1
More info at:
http://opencv.org/opencv-2-4-6-is-out.html
The brief list of changes:
* added video file i/o Windows RT and sample application using
camera, enabled parallelization with TBB or MS Concurrency
* added CUDA 5.5 support for desktop and ARM systems
* added Qt 5 support
* added many new OpenCL algorithms ports, included OpenCL binaries
into the Windows superpack
* iOS build scripts (together with Android ones) moved to
‘opencv/platforms’ directory
* added functions for UIImage <-> cv::Mat conversion
* correct front/back camera selection in Android app framework
* added Linaro NDK support and fixes for MIPS to Android CMake
toolchain
* stability has been improved by a lot, numerous bug-fixes across
all the library
- build with LFS_CFLAGS in 32 bit archs.
- Disable SSE3 for all architectures (bnc#814333)
- Disable SSE(2) on non x86_64 architectures, causes crashing
kde#276923, bnc#789173
- Update to OpenCV 2.4.5
More info at:
http://opencv.org/opencv-2-4-5-is-out.html
The brief list of changes:
* experimental WinRT support
* new video super-resolution module
* CLAHE (adaptive histogram equalization) algorithm on both CPU
and GPU
* further improvements and extensions in ocl module
(stereo block matching and belief propagation have been added,
fixed crashes on Intel HD4000)
* Visual Studio 2012 cv::Mat visualizer plugin debugger tutorial
from Microsoft Research
* OpenCV4Android SDK improvements
(NDK r8e support, native activity sample using OpenCV Manager,
bug-fixes)
* ~25 reported problems have been resolved since 2.4.4, ~78 pull
requests have been merged, thanks everybody who participated!
- Update to OpenCV 2.4.4
More info at:
http://opencv.org/opencv-2-4-4-is-out.html
The brief list of changes:
* OpenCV Java bindings are ported from Android to desktop Java!
Actually any JVM language will work, see Tutorial for details,
and Java or Scala code samples.
* Android application framework, samples, tutorials, and OpenCV
Manager are improved.
* Optimizations for the new NVIDIA Kepler architecture, CARMA
platform support and other new optimizations in CUDA.
* OpenCL module now builds successfully with various SDKs (from
AMD, NVIDIA, Intel and Apple) and runs well on different GPUs
(AMD, NVidia, Intel HD4000). A lot of new functionality has been
added, tons of bugs fixed, performance of many functions has
been significantly improved.
* 100+ reported problems have been resolved since 2.4.3, thanks
everybody who participated!
- Drop the buildrequire for libxine
- Update to OpenCV 2.4.3
More info at:
http://opencv.org/opencv-2-4-3-released.html
The nicely formatted changelog can be seen here:
http://code.opencv.org/projects/opencv/wiki/ChangeLog;
here are the highlights:
* A lot of good stuff from the Google Summer of Code 2012 has been
integrated; this was a very productive summer!
* Significantly improved and optimized Android and iOS ports.
* Greatly extended GPU (i.e. CUDA-based) module.
* The brand new ocl (OpenCL-based) module that unleashes GPU power
also for AMD and Intel GPU users. It’s not included into the
binary package, since there are different SDKs, and it’s not
turned on by default. You need to run CMake and turn on
“WITH_OPENCL”. Also, please note that this is very first version
of the module, so it may be not very stable and not very
functional.
* Much better performance on many-core systems out of the box. You
do not need TBB anymore on MacOSX, iOS and Windows. BTW, the
binary package for Windows is now built without TBB support.
Libraries and DLLs for Visual Studio 2010 use the Concurrency
framework.
* About 130 bugs have been fixed since 2.4.2.
* Since 2.4.3rc we fixed several more problems, in particular some
compile problems with iOS 6 SDK.
- buildrequire glu
- Update to OpenCV 2.4.2
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Drop opencv-datadir.patch to comply with upstream directory layout
- Update to OpenCV 2.4.1
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Update to OpenCV 2.4.0
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Add opencv-gcc47.patch: Fix build with gcc 4.7.
- Use Explicit Buildrequires on several needed libraries
future dependency cleanups may/will cause build to fail otherwise.
- Add upstream r6881 to fix clang compatibility
- uncomment libraries not in 12.1 for now
- Changed groups (fix for RPMLINT warning)
- Added check for duplicate files (fix for RPMLINT warning)
- Added py_requires macros and python-base dependencies (fix for RPMLINT warning)
- Escaped macros (fix for RPMLINT warning)
- Fixed end-of-line encoding problems (fix for RPMLINT warning)
- Added libeigen2-devel buildrequires
- Added libunicap and libucil buildrequires (libunicap supports requires libucil)
- Cleaned up spec file formatting
- Dropped opencv-2.3-ffmpeg.patch, applied upstream
- Revive opencv-2.3-ffmpeg.patch, needs rebase
- Tag all patches according to openSUSE packaging guidelines
- Removed opencv-2.3-cmake.patch, old cmake cannot be used any more.
- Python bindings cannot be built without NumPy any more.
- Update to OpenCV 2.3.1
- Update and readd opencv-2.3-underlinking.patch since it is still
necessary.
- Fix support for new ffmpeg versions
- Removed unnecessary patches
- Enable Python NumPy support on openSUSE 11.2
- Build Qt instead of Gtk GUI
- Fix cmake files for openSUSE 11.1
- No GStreamer support on openSUSE 11.1
- Update to OpenCV 2.3.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Fix build on openSUSE 11.2
- Add opencv-v4l-2.6.38.patch: use the new libv4l2 interface
- Enable Python NumPy support
- SWIG is not required any more
- Enable OpenEXR support
- Update to OpenCV 2.2.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Use system zlib, oh, and do not export ZLIB symbols to
other applications, clashes ensued.
- fix build with gcc 4.6
- add -underlinking patch
- devel package renamed to opencv-devel, so that switching between
OBS and packman opencv packages is easier
- fix gstreamer support
- fix xine support
- fix some rpmlint warnings
- fix shared libraries permissions
- Do not waste resources building the tests as we do not run them
- Do not disable SSE,SSE2,etc. According to OpenCV changelog,
it should be safe to leave these enabled.
- fix build on openSUSE 11.0
- Update to OpenCV 2.1.0:
* The whole OpenCV is now using exceptions instead of the old
libc-style mechanism
* Experimental "static" OpenCV configuration in CMake was
contributed by Jose Luis Blanco.
Pass "BUILD_SHARED_LIBS=OFF" to CMake to build OpenCV statically.
* new improved version of one-way descriptor is added
* User can now control the image areas visible after the stereo
rectification
* Fullscreen has been added (thanks to Yannick Verdie).
* Further info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- fix build with libpng14
- small spec file cleanup
- Moved to the KDE repositories to enable inclusion in kipi-plugins
- Initial package
OBS-URL: https://build.opensuse.org/request/show/714221
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/opencv?expand=0&rev=73
2019-07-17 13:13:58 +02:00
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%exclude %{_datadir}/opencv4/valgrind*
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2010-03-08 18:16:50 +01:00
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2020-11-03 06:51:22 +01:00
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%files -n %{name}4-cascades-data
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2020-11-03 06:17:42 +01:00
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%{_datadir}/opencv4/*cascades
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2013-08-01 15:56:40 +02:00
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%files -n %{libname}%{soname}
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2018-06-02 11:53:10 +02:00
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%license LICENSE LICENSE.contrib
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%{_libdir}/libopencv_calib3d.so.*
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%{_libdir}/libopencv_core.so.*
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%{_libdir}/libopencv_dnn.so.*
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%{_libdir}/libopencv_features2d.so.*
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%{_libdir}/libopencv_flann.so.*
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%{_libdir}/libopencv_imgproc.so.*
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%{_libdir}/libopencv_ml.so.*
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%{_libdir}/libopencv_photo.so.*
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%{_libdir}/libopencv_plot.so.*
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%{_libdir}/libopencv_shape.so.*
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%{_libdir}/libopencv_stitching.so.*
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%{_libdir}/libopencv_tracking.so.*
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%{_libdir}/libopencv_video.so.*
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2020-11-03 06:17:42 +01:00
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2021-02-22 20:10:19 +01:00
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%files -n libopencv_aruco%{soname}
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%{_libdir}/libopencv_aruco.so.*
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2020-11-03 06:17:42 +01:00
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%files -n libopencv_face%{soname}
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%{_libdir}/libopencv_face.so.*
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Accepting request 983700 from home:StefanBruens:branches:science
- update to 4.6.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version460
* OpenCV project infrastructure migrating on GitHub Actions
workflows for CI and release purposes
* Added support for GCC 12, Clang 15
* Added support for FFmpeg 5.0
* DNN module patches:
+ Improved layers / activations / supported more models:
- LSTM (+CUDA), resize (+ONNX13), Sign, Shrink, Reciprocal,
depth2space, space2depth
- fixes in Reduce, Slice, Expand
+ Disabled floating-point denormals processing #21521
+ Changed layer names in ONNX importer to support "output"
entities properly
+ Added TIM-VX NPU backend support:
https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU
+ Added Softmax parameter to ClassificationModel
+ Added audio speech recognition sample (C++) #21458
+ Intel® Inference Engine backend (OpenVINO):
- added initial support for OpenVINO 2022.1 release
- removed support of legacy API (dropped since 2020.3)
* G-API module:
+ G-API framework:
- Introduced a Grayscale image format support for
cv::MediaFrame: #21511;
- Enabeled .reshape() support in the CPU backend: #21669;
- Fixed possible hang in streaming execution mode with constant
inputs: #21567;
- Introduced proper error/exception propagation in the
asynchronous streaming execution mode: #21660;
- Fixed new stream event handling: #21731.
+ Fluid backend:
- Fixed horizontal pass in the Resize kernel, fixed Valgrind
issues: #21144;
- Extended Resize kernel with F32 version: #21678,
added AVX: #21728.
- Enabled dynamic dispatch for Split4 kernel: #21520;
- Enabled dynamic dispatch for Merge3 kernel: #21529;
- Added a SIMD version for DivC kernel: #21474;
- Added a SIMD version for DivRC kernel: #21530;
- Enabled dynamic dispatch for Add kernel: #21686;
- Enabled dynamic dispatch for Sub kernel: #21746;
- Added a SIMD version for ConvertTo kernel: #21777;
- Fixed kernel matrix size for Sobel kernel: #21613.
+ Intel® OpenVINO™ inference backend:
- Fixed NV12 format support for remote memory when OpenVINO
remote context is used: #21424.
- Implemented correct error handling in the backend: #21579.
- Fixed ngraph warnings #21362.
+ OpenCV AI Kit backend:
- Introduced a new backend to program OpenCV AI Kit boards via
G-API. Currently the backend is in experimental state, but allows
to build Camera+NN pipeline and supports heterogeneity (mixing
with host-side code): #20785, #21504.
+ Media integration:
- Enabled GPU inference with oneVPL and DirectX11 on Windows in
Intel OpenVINO inference backend: #21232, #21618, #21658, #21687,
#21688. Now GPU textures decoded by oneVPL decoder can be
preprocessed and inferred on GPU with no extra host processing.
- Enabled oneVPL support on Linux: #21883.
- Extended GStreamer pipeline source with Grayscale image format
support: #21560.
+ Python bindings:
- Exposed GStreamer pipeline source in Python bindings: #20832.
- Fixed Python bindings for CudaBufferPool, cudacodec and cudastereo
modules in OpenCV Contrib.
+ Samples:
- Introduced a pipeline modelling tool for cascaded model
benchmarking: #21477, #21636, #21719. The tool supports a
declarative YAML-based config to describe pipelines with simulated
pre-/post-processing. The tool collects and reports latency and
throughput information for the modelled pipeline.
+ Other changes and fixes:
- Moved GKernelPackage into cv:: namespace by default, its cv::gapi::
alias remain for compatibility: #21318;
- Moved Resize kernel from core to imgproc kernel packages for
CPU, OpenCL, and Fluid backends: #21157. Also moved tests
appropriately: #21475;
- Avoided sporadic test failures in DivC: #21626;
- Fixed 1D Mat handling in the framework: #21782;
- Reduced the number of G-API generated accuracy tests: #21909.
- Drop upstream patches:
* 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
* videoio_initial_FFmpeg_5_0_support.patch
* videoio_ffmpeg_avoid_memory_leaks.patch
OBS-URL: https://build.opensuse.org/request/show/983700
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=33
2022-06-27 18:05:05 +02:00
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%if %{with gapi}
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%files -n libopencv_gapi%{soname}
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%{_libdir}/libopencv_gapi.so.*
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%endif
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2020-11-03 06:17:42 +01:00
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%files -n libopencv_highgui%{soname}
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%{_libdir}/libopencv_highgui.so.*
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%files -n libopencv_imgcodecs%{soname}
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%{_libdir}/libopencv_imgcodecs.so.*
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%files -n libopencv_objdetect%{soname}
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%{_libdir}/libopencv_objdetect.so.*
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Accepting request 983700 from home:StefanBruens:branches:science
- update to 4.6.0, highlights below, for details check
https://github.com/opencv/opencv/wiki/ChangeLog#version460
* OpenCV project infrastructure migrating on GitHub Actions
workflows for CI and release purposes
* Added support for GCC 12, Clang 15
* Added support for FFmpeg 5.0
* DNN module patches:
+ Improved layers / activations / supported more models:
- LSTM (+CUDA), resize (+ONNX13), Sign, Shrink, Reciprocal,
depth2space, space2depth
- fixes in Reduce, Slice, Expand
+ Disabled floating-point denormals processing #21521
+ Changed layer names in ONNX importer to support "output"
entities properly
+ Added TIM-VX NPU backend support:
https://github.com/opencv/opencv/wiki/TIM-VX-Backend-For-Running-OpenCV-On-NPU
+ Added Softmax parameter to ClassificationModel
+ Added audio speech recognition sample (C++) #21458
+ Intel® Inference Engine backend (OpenVINO):
- added initial support for OpenVINO 2022.1 release
- removed support of legacy API (dropped since 2020.3)
* G-API module:
+ G-API framework:
- Introduced a Grayscale image format support for
cv::MediaFrame: #21511;
- Enabeled .reshape() support in the CPU backend: #21669;
- Fixed possible hang in streaming execution mode with constant
inputs: #21567;
- Introduced proper error/exception propagation in the
asynchronous streaming execution mode: #21660;
- Fixed new stream event handling: #21731.
+ Fluid backend:
- Fixed horizontal pass in the Resize kernel, fixed Valgrind
issues: #21144;
- Extended Resize kernel with F32 version: #21678,
added AVX: #21728.
- Enabled dynamic dispatch for Split4 kernel: #21520;
- Enabled dynamic dispatch for Merge3 kernel: #21529;
- Added a SIMD version for DivC kernel: #21474;
- Added a SIMD version for DivRC kernel: #21530;
- Enabled dynamic dispatch for Add kernel: #21686;
- Enabled dynamic dispatch for Sub kernel: #21746;
- Added a SIMD version for ConvertTo kernel: #21777;
- Fixed kernel matrix size for Sobel kernel: #21613.
+ Intel® OpenVINO™ inference backend:
- Fixed NV12 format support for remote memory when OpenVINO
remote context is used: #21424.
- Implemented correct error handling in the backend: #21579.
- Fixed ngraph warnings #21362.
+ OpenCV AI Kit backend:
- Introduced a new backend to program OpenCV AI Kit boards via
G-API. Currently the backend is in experimental state, but allows
to build Camera+NN pipeline and supports heterogeneity (mixing
with host-side code): #20785, #21504.
+ Media integration:
- Enabled GPU inference with oneVPL and DirectX11 on Windows in
Intel OpenVINO inference backend: #21232, #21618, #21658, #21687,
#21688. Now GPU textures decoded by oneVPL decoder can be
preprocessed and inferred on GPU with no extra host processing.
- Enabled oneVPL support on Linux: #21883.
- Extended GStreamer pipeline source with Grayscale image format
support: #21560.
+ Python bindings:
- Exposed GStreamer pipeline source in Python bindings: #20832.
- Fixed Python bindings for CudaBufferPool, cudacodec and cudastereo
modules in OpenCV Contrib.
+ Samples:
- Introduced a pipeline modelling tool for cascaded model
benchmarking: #21477, #21636, #21719. The tool supports a
declarative YAML-based config to describe pipelines with simulated
pre-/post-processing. The tool collects and reports latency and
throughput information for the modelled pipeline.
+ Other changes and fixes:
- Moved GKernelPackage into cv:: namespace by default, its cv::gapi::
alias remain for compatibility: #21318;
- Moved Resize kernel from core to imgproc kernel packages for
CPU, OpenCL, and Fluid backends: #21157. Also moved tests
appropriately: #21475;
- Avoided sporadic test failures in DivC: #21626;
- Fixed 1D Mat handling in the framework: #21782;
- Reduced the number of G-API generated accuracy tests: #21909.
- Drop upstream patches:
* 0001-highgui-Fix-unresolved-OpenGL-functions-for-Qt-backe.patch
* videoio_initial_FFmpeg_5_0_support.patch
* videoio_ffmpeg_avoid_memory_leaks.patch
OBS-URL: https://build.opensuse.org/request/show/983700
OBS-URL: https://build.opensuse.org/package/show/science/opencv?expand=0&rev=33
2022-06-27 18:05:05 +02:00
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%files -n libopencv_optflow%{soname}
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%{_libdir}/libopencv_optflow.so.*
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2020-11-03 06:17:42 +01:00
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%files -n libopencv_superres%{soname}
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%{_libdir}/libopencv_superres.so.*
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%files -n libopencv_videoio%{soname}
|
2018-06-02 11:53:10 +02:00
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%{_libdir}/libopencv_videoio.so.*
|
2020-11-03 06:17:42 +01:00
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%files -n libopencv_videostab%{soname}
|
2018-06-02 11:53:10 +02:00
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|
%{_libdir}/libopencv_videostab.so.*
|
2020-11-03 06:17:42 +01:00
|
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%files -n libopencv_ximgproc%{soname}
|
Accepting request 714221 from science
- Update to version 4.1.0
* DNN module:
+ Reduced peak memory consumption for some models up to 30%.
+ Inference Engine
- Inference Engine 2018R3 is now a minimal supported version of IE.
- Myriad X (Intel® Neural Compute Stick 2) is now supported and tested.
- Automatic IR network reshaping for different inputs.
- Improved samples to work with models from OpenVINO Open Model Zoo
+ New networks from TensorFlow Object Detection API: Faster-RCNNs, SSDs
and Mask-RCNN with dilated convolutions, FPN SSD
* Performance improvements:
+ More optimization using AVX2 instruction set.
+ Automatic runtime dispatching is available for large set of functions
from core and imgproc modules.
* Other improvements:
+ Matplotlib Perceptually Uniform Sequential colormaps
+ Add keypoints matching visualization for real-time pose estimation tutorial
+ Add Hand-Eye calibration methods
+ Java: improved support for multidimensional arrays (Mat)
+ Dynamically loaded videoio backends (FFmpeg, GStreamer)
+ opencv_contrib: Robust local optical flow (RLOF) implementations
+ opencv_contrib: Implementation of Quasi Dense Stereo algorithm
+ opencv_contrib: New module: Image Quality Analysis (IQA) API
+ opencv_contrib: BRISQUE No Reference Image Quality Assessment (IQA) API
Check https://github.com/opencv/opencv/wiki/ChangeLog#version410
- Update to version 4.0.0
* A lot of C API from OpenCV 1.x has been removed. The affected modules are
objdetect, photo, video, videoio, imgcodecs, calib3d.
* Persistence (storing and loading structured data to/from XML, YAML or JSON)
in the core module has been completely reimplemented.
* OpenCV is now C++11 library and requires C++11-compliant compiler.
Thanks to the extended C++11 standard library, we could get rid of hand-crafted
cv::String and cv::Ptr. Now cv::String == std::string and cv::Ptr is a thin
wrapper on top of std::shared_ptr. Also, on Linux/BSD for cv::parallel_for_
we now use std::thread's instead of pthreads.
* DNN improvements
* Completely new module opencv_gapi has been added. It is the engine for very
efficient image processing, based on lazy evaluation and on-fly construction.
* Performance improvements
A few hundreds of basic kernels in OpenCV have been rewritten using so-called
"wide universal intrinsics". Those intrinsics map to SSE2, SSE4, AVX2, NEON or
VSX intrinsics, depending on the target platform and the compile flags.
* QR code detector and decoder have been added to opencv/objdetect module.
* The popular Kinect Fusion algorithm has been implemented, optimized for CPU and
GPU (OpenCL), and integrated into opencv_contrib/rgbd module.
* Very efficient and yet high-quality DIS dense optical flow algorithm has been
moved from opencv_contrib to opencv, video module. See the example.
* The slower TV L1 optical flow algorithm has been moved to opencv_contrib.
Check https://github.com/opencv/opencv/wiki/ChangeLog#version400
- Drop obsolete opencv-lib_suffix.patch
- Add 0001-Handle-absolute-OPENCV_INCLUDE_INSTALL_PATH-correctl.patch
- As this is a major version upgrade, the old 3.4.x package is still
available as opencv3
- Update to 3.4.3
* Compatibility fixes with python 3.7
* Added a new computational target DNN_TARGET_OPENCL_FP16
* Extended support of Intel's Inference Engine backend
* Enabled import of Intel's OpenVINO pre-trained networks from
intermediate representation (IR).
* tutorials improvements
Check https://github.com/opencv/opencv/wiki/ChangeLog#version343
for the complete changelog.
- Drop fix-build-i386-nosse.patch, build-workaround-issues-with-c.patch
(fixed upstream)
- Refresh patches
- Add patch to fix use of headers from C:
* build-workaround-issues-with-c.patch
- Update to 3.4.1:
* Added support for quantized TensorFlow networks
* OpenCV is now able to use Intel DL inference engine as DNN
acceleration backend
* Added AVX-512 acceleration to the performance-critical kernels
* For more information, read
https://github.com/opencv/opencv/wiki/ChangeLog#version341
- Update contrib modules to 3.4.1:
* No changelog available
- Change mechanism the contrib modules are built
- Include LICENSE of contrib tarball as well
- Build with python3 on >= 15
- Add patch to fix build on i386 without SSE:
* fix-build-i386-nosse.patch
- Refresh patches:
* fix_processor_detection_for_32bit_on_64bit.patch
* opencv-build-compare.patch
- Mention all libs explicitly
- Rebase 3.4.0 update from i@marguerite.su
- update to 3.4.0
* Added faster R-CNN support
* Javascript bindings have been extended to
cover DNN module
* DNN has been further accelerated for iGPU
using OpenCL
* On-disk caching of precompiled OpenCL
kernels has been finally implemented
* possible to load and run pre-compiled
OpenCL kernels via T-API
* Bit-exact 8-bit and 16-bit resize has been
implemented (currently supported only
bilinear interpolation)
- update face module to 3.4.0
- add opencv-lib_suffix.patch, remove LIB_SUFFIX
from OPENCV_LIB_INSTALL_PATH, as CMAKE_INSTALL
_LIBDIR is arch dependent.
- Add option to build without openblas
- Add conditionals for python2 and python3 to allow us enabling
only desired python variants when needed
- Do not depend on sphinx as py2 and py3 seem to collide there
- Readd opencv-gles.patch, it is *not* included upstream; otherwise
build breaks on all GLES Qt5 platforms (armv6l, armv7l, aarch64)
- add fix_processor_detection_for_32bit_on_64bit.patch
- Correctly set optimizations and dynamic dispatch on ARM, use
OpenCV 3.3 syntax on x86.
- Update licensing information
- change requires of python-numpy-devel to build in Leap and
to not break factory in future
- fix build error/unresolvable for Leap 42.2 and 42.3
- Update to version 3.3.1:
* Lots of various bugfixes
- Update source url
- Rename python subpackage to python2
- Do not explicitly require python-base for python subpackages
- Update to 3.3
- Dropped obsolete patches
* opencv-gcc6-fix-pch-support-PR8345.patch
* opencv-gles.patch
- Updated opencv-build-compare.patch
- Add 0001-Do-not-include-glx.h-when-using-GLES.patch
Fix build for 32bit ARM, including both GLES and desktop GL headers
causes incompatible pointer type errors
- Add conditional for the qt5/qt4 integration
* This is used only for gui tools, library is not affected
- Add provides/obsoletes for the qt5 packages to allow migration
- Drop patch opencv-qt5-sobump.diff
* Used only by the obsoleted qt5 variant
- Cleanup a bit with spec-cleaner
- Use %cmake macros
- Remove the conditions that are not really needed
- Add tests conditional disabled by default
* Many tests fail and there are missing testdata
- Switch to pkgconfig style dependencies
- Update to OpenCV 3.2.0
- Results from 11 GSoC 2016 projects have been submitted to the library:
+ sinusoidal patterns for structured light and phase unwrapping module
[Ambroise Moreau (Delia Passalacqua)]
+ DIS optical flow (excellent dense optical flow algorithm that is both
significantly better and significantly faster than Farneback’s algorithm –
our baseline), and learning-based color constancy algorithms implementation
[Alexander Bokov (Maksim Shabunin)]
+ CNN based tracking algorithm (GOTURN) [Tyan Vladimir (Antonella Cascitelli)]
+ PCAFlow and Global Patch Collider algorithms implementation
[Vladislav Samsonov (Ethan Rublee)]
+ Multi-language OpenCV Tutorials in Python, C++ and Java
[João Cartucho (Vincent Rabaud)]
+ New camera model and parallel processing for stitching pipeline
[Jiri Horner (Bo Li)]
+ Optimizations and improvements of dnn module
[Vitaliy Lyudvichenko (Anatoly Baksheev)]
+ Base64 and JSON support for file storage. Use names like
“myfilestorage.xml?base64” when writing file storage to store big chunks of
numerical data in base64-encoded form. [Iric Wu (Vadim Pisarevsky)]
+ tiny_dnn improvements and integration
[Edgar Riba (Manuele Tamburrano, Stefano Fabri)]
+ Quantization and semantic saliency detection with tiny_dnn
[Yida Wang (Manuele Tamburrano, Stefano Fabri)]
+ Word-spotting CNN based algorithm
[Anguelos Nicolaou (Lluis Gomez)]
- Contributions besides GSoC:
+ Greatly improved and accelerated dnn module in opencv_contrib:
- Many new layers, including deconvolution, LSTM etc.
- Support for semantic segmentation and SSD networks with samples.
- TensorFlow importer + sample that runs Inception net by Google.
+ More image formats and camera backends supported
+ Interactive camera calibration app
+ Multiple algorithms implemented in opencv_contrib
+ Supported latest OSes, including Ubuntu 16.04 LTS and OSX 10.12
+ Lot’s of optimizations for IA and ARM archs using parallelism, vector
instructions and new OpenCL kernels.
+ OpenCV now can use vendor-provided OpenVX and LAPACK/BLAS (including Intel MKL,
Apple’s Accelerate, OpenBLAS and Atlas) for acceleration
- Refreshed opencv-build-compare.patch
- Dropped upstream opencv-gcc5.patch
- Replace opencv-gcc6-disable-pch.patch with upstream patch
opencv-gcc6-fix-pch-support-PR8345.patch
- Enable TBB support (C++ threading library)
- Add dependency on openBLAS
- Enable ffmpeg support unconditional
- In case we build using GCC6 (or newer), add -mlra to CFLAGS to
workaround gcc bug
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=71294.
- Apply upstream patch opencv-gcc6-disable-pch.patch to disable
PCH for GCC6.
- Test for python versions greater than or equal to the current
version.
- Add python 3 support
- Added opencv_contrib_face-3.1.0.tar.bz2
* This tarball is created to take only the face module from the
contrib package. The Face module is required by libkface, which
in its turn is required by digikam.
- Added _constraints file to avoid random failures on small workers
(at least for builds on PMBS)
- Update to OpenCV 3.1.0
- A lot of new functionality has been introduced during Google
Summer of Code 2015:
+ “Omnidirectional Cameras Calibration and Stereo 3D
Reconstruction” – opencv_contrib/ccalib module
(Baisheng Lai, Bo Li)
+ “Structure From Motion” – opencv_contrib/sfm module
(Edgar Riba, Vincent Rabaud)
+ “Improved Deformable Part-based Models” – opencv_contrib/dpm
module (Jiaolong Xu, Bence Magyar)
+ “Real-time Multi-object Tracking using Kernelized Correlation
Filter” – opencv_contrib/tracking module
(Laksono Kurnianggoro, Fernando J. Iglesias Garcia)
+ “Improved and expanded Scene Text Detection” –
opencv_contrib/text module (Lluis Gomez, Vadim Pisarevsky)
+ “Stereo correspondence improvements” – opencv_contrib/stereo
module (Mircea Paul Muresan, Sergei Nosov)
+ “Structured-Light System Calibration” –
opencv_contrib/structured_light (Roberta Ravanelli,
Delia Passalacqua, Stefano Fabri, Claudia Rapuano)
+ “Chessboard+ArUco for camera calibration” –
opencv_contrib/aruco (Sergio Garrido, Prasanna, Gary Bradski)
+ “Implementation of universal interface for deep neural
network frameworks” – opencv_contrib/dnn module
(Vitaliy Lyudvichenko, Anatoly Baksheev)
+ “Recent advances in edge-aware filtering, improved SGBM
stereo algorithm” – opencv/calib3d and opencv_contrib/ximgproc
(Alexander Bokov, Maksim Shabunin)
+ “Improved ICF detector, waldboost implementation” –
opencv_contrib/xobjdetect (Vlad Shakhuro, Alexander Bovyrin)
+ “Multi-target TLD tracking” – opencv_contrib/tracking module
(Vladimir Tyan, Antonella Cascitelli)
+ “3D pose estimation using CNNs” – opencv_contrib/cnn_3dobj
(Yida Wang, Manuele Tamburrano, Stefano Fabri)
- Many great contributions made by the community, such as:
+ Support for HDF5 format
+ New/Improved optical flow algorithms
+ Multiple new image processing algorithms for filtering,
segmentation and feature detection
+ Superpixel segmentation and much more
- IPPICV is now based on IPP 9.0.1, which should make OpenCV
even faster on modern Intel chips
- opencv_contrib modules can now be included into the
opencv2.framework for iOS
- Newest operating systems are supported: Windows 10 and
OSX 10.11 (Visual Studio 2015 and XCode 7.1.1)
- Interoperability between T-API and OpenCL, OpenGL, DirectX and
Video Acceleration API on Linux, as well as Android 5 camera.
- HAL (Hardware Acceleration Layer) module functionality has been
moved into corresponding basic modules; the HAL replacement
mechanism has been implemented along with the examples
- Removed improve-sphinx-search.diff, opencv-altivec-vector.patch,
opencv-pkgconfig.patch and opencv-samples.patch, fixed upstream.
- Fixed opencv-qt5-sobump.diff, opencv-build-compare.patch,
opencv-gcc5.patch and opencv-gles.patch.
- Version OpenCV 3.0.0
+ ~1500 patches, submitted as PR @ github. All our patches go
the same route.
+ opencv_contrib (http://github.com/itseez/opencv_contrib)
repository has been added. A lot of new functionality is there
already! opencv_contrib is only compatible with 3.0/master,
not 2.4. Clone the repository and use “cmake …
-D OPENCV_EXTRA_MODULES_PATH=<path_to opencv_contrib/modules> …”
to build opencv and opencv_contrib together.
+ a subset of Intel IPP (IPPCV) is given to us and our users free
of charge, free of licensing fees, for commercial and
non-commerical use. It’s used by default in x86 and x64 builds
on Windows, Linux and Mac.
+ T-API (transparent API) has been introduced, this is transparent
GPU acceleration layer using OpenCL. It does not add any
compile-time or runtime dependency of OpenCL. When OpenCL is
available, it’s detected and used, but it can be disabled at
compile time or at runtime. It covers ~100 OpenCV functions.
This work has been done by contract and with generous support
from AMD and Intel companies.
+ ~40 OpenCV functions have been accelerated using NEON intrinsics
and because these are mostly basic functions, some higher-level
functions got accelerated as well.
+ There is also new OpenCV HAL layer that will simplifies creation
of NEON-optimized code and that should form a base for the
open-source and proprietary OpenCV accelerators.
+ The documentation is now in Doxygen: http://docs.opencv.org/master/
+ We cleaned up API of many high-level algorithms from features2d,
calib3d, objdetect etc. They now follow the uniform
“abstract interface – hidden implementation” pattern and make
extensive use of smart pointers (Ptr<>).
+ Greatly improved and extended Python & Java bindings (also,
see below on the Python bindings), newly introduced Matlab
bindings (still in alpha stage).
+ Improved Android support – now OpenCV Manager is in Java and
supports both 2.4 and 3.0.
+ Greatly improved WinRT support, including video capturing and
multi-threading capabilities. Thanks for Microsoft team for this!
+ Big thanks to Google who funded several successive GSoC programs
and let OpenCV in. The results of many successful GSoC 2013 and
2014 projects have been integrated in opencv 3.0 and
opencv_contrib (earlier results are also available in
OpenCV 2.4.x). We can name:
- text detection
- many computational photography algorithms (HDR, inpainting,
edge-aware filters, superpixels, …)
- tracking and optical flow algorithms
- new features, including line descriptors, KAZE/AKAZE
- general use optimization (hill climbing, linear programming)
- greatly improved Python support, including Python 3.0 support,
many new tutorials & samples on how to use OpenCV with Python.
- 2d shape matching module and 3d surface matching module
- RGB-D module
- VTK-based 3D visualization module
- etc.
+ Besides Google, we enjoyed (and hope that you will enjoy too)
many useful contributions from community, like:
- biologically inspired vision module
- DAISY features, LATCH descriptor, improved BRIEF
- image registration module
- etc.
- Reduce build-compare noise
opencv-build-compare.patch
- Remove BuildRequirement for python-sphinx in SLE12, since it's
not available there and it's not a mandatory requirement.
- Reduce differences between two spec files
- Use pkgconfig for ffmpeg BuildRequires
- Update improve-sphinx-search.diff for new python-Sphinx(1.3.1)
* now that sphinx-build disallow executing without arguments and
give you "Insufficient arguments" error, use "sphinx-build -h"
instead
* the default usages output ie. sphinx-build(or --help) no longer
are standard error but standard output, drop OUTPUT_QUIET and
add OUTPUT_VARIABLE throws the output to SPHINX_OUTPUT as well
- support gcc 5 (i.e. gcc versions without minor version):
opencv-gcc5.patch
- Update to OpenCV 2.4.11 - can't find NEWS or Changelog
merely collecting bug fixes while 3.0 is in the making, 2.4.11
didn't even make it on their web page, it's only on download
server
- remove opencv-underlinking.patch as obsolete
- remove upstream patch bomb_commit_gstreamer-1x-support.patch
- commenting out opencv-pkgconfig.patch - possibly it requires a rebase,
but the problem it tries to solve is unclear
- Add specific buildrequires for libpng15, so that we are
building against the system provided libpng.
- Update to OpenCV 2.4.9
More info at:
http://opencv.org/opencv-2-4-9-is-out.html
The brief list of changes:
* new 3D visualization module ‘viz’;
* performance fixes in ‘ocl’ module;
* fixes in Android Camera;
* improved CUDA support for mobile platforms;
* bugfixes from community;
* 55 reported bugs have been closed;
* 156 pull requests have been merged.
- Drop the BuildRequires on libucil and libunicap for Factory. This
stops us from getting ride of Gstreamer 0.10 and besides these two
libraries seem to be unmaintained upstream as that the latest
actions are from 2010
- Add upstream patch (3.0 version) to support Gstreamer 1.x
* bomb_commit_gstreamer-1x-support.patch
- Upstream now provides tarballs with source only as git tags
from github so update Source0 path.
- Add requires on various X extensions linked to opencv_ts module.
As those are present in the .pc file we need it anyway.
- Update to OpenCV 2.4.8
More info at:
http://opencv.org/opencv-2-4-8.html
The brief list of changes:
* NVidia CUDA support on Android devices with CUDA capable SoC and
CUDA sample;
* Concurrent kernel execution and user defined context support for
OpenCL;
* Integration with Intel Perceptual SDK and new depth sensors support
for Windows;
* 32 reported bugs have been closed;
* 139 pull requests have been merged;
- Fix build with altivec:
opencv-altivec-vector.patch
- Added opencv-pkgconfig.patch: make sure to provide link flags in
OpenCV pc file (bnc#853036)
- Update to OpenCV 2.4.7
More info at:
http://opencv.org/opencv-2-4-7-is-out.html
The brief list of changes:
* dynamic OpenCL runtime loading, setting default OpenCL device
via env var, many bug-fixes and some new optimization with OpenCL
* bug-fixes and new optimizations in CUDA stuff
* latest NDK and Android OS support, Native Android Camera tuning
* minor fixes, XAML sample and MS Certification compatibility
in WinRT stuff
* 382 pull requests have been merged
* 54 reported bugs have been fixed
- Added pkgconfig(glu) Requires to devel package, as per .pc file
- Make devel package provides also devel-static one
- Drop assume-Sphinx-is-there.diff, and add improve-sphinx-search.diff,
for properly finding sphinx with alphabetic chars in version
- Add patch assume-Sphinx-is-there.diff to fix building with
Sphinx versions that have alphanumeric characters in the version
(Only for factory builds at the moment)
- Use eigen3 instead of eigen2 as build requirement for openSUSE > 12.3.
- Enable compilation with libucil and libunicap.
- Removed dos2unix build requirement (not needed anymore).
- Update to OpenCV 2.4.6.1
More info at:
http://opencv.org/opencv-2-4-6-is-out.html
The brief list of changes:
* added video file i/o Windows RT and sample application using
camera, enabled parallelization with TBB or MS Concurrency
* added CUDA 5.5 support for desktop and ARM systems
* added Qt 5 support
* added many new OpenCL algorithms ports, included OpenCL binaries
into the Windows superpack
* iOS build scripts (together with Android ones) moved to
‘opencv/platforms’ directory
* added functions for UIImage <-> cv::Mat conversion
* correct front/back camera selection in Android app framework
* added Linaro NDK support and fixes for MIPS to Android CMake
toolchain
* stability has been improved by a lot, numerous bug-fixes across
all the library
- build with LFS_CFLAGS in 32 bit archs.
- Disable SSE3 for all architectures (bnc#814333)
- Disable SSE(2) on non x86_64 architectures, causes crashing
kde#276923, bnc#789173
- Update to OpenCV 2.4.5
More info at:
http://opencv.org/opencv-2-4-5-is-out.html
The brief list of changes:
* experimental WinRT support
* new video super-resolution module
* CLAHE (adaptive histogram equalization) algorithm on both CPU
and GPU
* further improvements and extensions in ocl module
(stereo block matching and belief propagation have been added,
fixed crashes on Intel HD4000)
* Visual Studio 2012 cv::Mat visualizer plugin debugger tutorial
from Microsoft Research
* OpenCV4Android SDK improvements
(NDK r8e support, native activity sample using OpenCV Manager,
bug-fixes)
* ~25 reported problems have been resolved since 2.4.4, ~78 pull
requests have been merged, thanks everybody who participated!
- Update to OpenCV 2.4.4
More info at:
http://opencv.org/opencv-2-4-4-is-out.html
The brief list of changes:
* OpenCV Java bindings are ported from Android to desktop Java!
Actually any JVM language will work, see Tutorial for details,
and Java or Scala code samples.
* Android application framework, samples, tutorials, and OpenCV
Manager are improved.
* Optimizations for the new NVIDIA Kepler architecture, CARMA
platform support and other new optimizations in CUDA.
* OpenCL module now builds successfully with various SDKs (from
AMD, NVIDIA, Intel and Apple) and runs well on different GPUs
(AMD, NVidia, Intel HD4000). A lot of new functionality has been
added, tons of bugs fixed, performance of many functions has
been significantly improved.
* 100+ reported problems have been resolved since 2.4.3, thanks
everybody who participated!
- Drop the buildrequire for libxine
- Update to OpenCV 2.4.3
More info at:
http://opencv.org/opencv-2-4-3-released.html
The nicely formatted changelog can be seen here:
http://code.opencv.org/projects/opencv/wiki/ChangeLog;
here are the highlights:
* A lot of good stuff from the Google Summer of Code 2012 has been
integrated; this was a very productive summer!
* Significantly improved and optimized Android and iOS ports.
* Greatly extended GPU (i.e. CUDA-based) module.
* The brand new ocl (OpenCL-based) module that unleashes GPU power
also for AMD and Intel GPU users. It’s not included into the
binary package, since there are different SDKs, and it’s not
turned on by default. You need to run CMake and turn on
“WITH_OPENCL”. Also, please note that this is very first version
of the module, so it may be not very stable and not very
functional.
* Much better performance on many-core systems out of the box. You
do not need TBB anymore on MacOSX, iOS and Windows. BTW, the
binary package for Windows is now built without TBB support.
Libraries and DLLs for Visual Studio 2010 use the Concurrency
framework.
* About 130 bugs have been fixed since 2.4.2.
* Since 2.4.3rc we fixed several more problems, in particular some
compile problems with iOS 6 SDK.
- buildrequire glu
- Update to OpenCV 2.4.2
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Drop opencv-datadir.patch to comply with upstream directory layout
- Update to OpenCV 2.4.1
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Update to OpenCV 2.4.0
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Add opencv-gcc47.patch: Fix build with gcc 4.7.
- Use Explicit Buildrequires on several needed libraries
future dependency cleanups may/will cause build to fail otherwise.
- Add upstream r6881 to fix clang compatibility
- uncomment libraries not in 12.1 for now
- Changed groups (fix for RPMLINT warning)
- Added check for duplicate files (fix for RPMLINT warning)
- Added py_requires macros and python-base dependencies (fix for RPMLINT warning)
- Escaped macros (fix for RPMLINT warning)
- Fixed end-of-line encoding problems (fix for RPMLINT warning)
- Added libeigen2-devel buildrequires
- Added libunicap and libucil buildrequires (libunicap supports requires libucil)
- Cleaned up spec file formatting
- Dropped opencv-2.3-ffmpeg.patch, applied upstream
- Revive opencv-2.3-ffmpeg.patch, needs rebase
- Tag all patches according to openSUSE packaging guidelines
- Removed opencv-2.3-cmake.patch, old cmake cannot be used any more.
- Python bindings cannot be built without NumPy any more.
- Update to OpenCV 2.3.1
- Update and readd opencv-2.3-underlinking.patch since it is still
necessary.
- Fix support for new ffmpeg versions
- Removed unnecessary patches
- Enable Python NumPy support on openSUSE 11.2
- Build Qt instead of Gtk GUI
- Fix cmake files for openSUSE 11.1
- No GStreamer support on openSUSE 11.1
- Update to OpenCV 2.3.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Fix build on openSUSE 11.2
- Add opencv-v4l-2.6.38.patch: use the new libv4l2 interface
- Enable Python NumPy support
- SWIG is not required any more
- Enable OpenEXR support
- Update to OpenCV 2.2.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Use system zlib, oh, and do not export ZLIB symbols to
other applications, clashes ensued.
- fix build with gcc 4.6
- add -underlinking patch
- devel package renamed to opencv-devel, so that switching between
OBS and packman opencv packages is easier
- fix gstreamer support
- fix xine support
- fix some rpmlint warnings
- fix shared libraries permissions
- Do not waste resources building the tests as we do not run them
- Do not disable SSE,SSE2,etc. According to OpenCV changelog,
it should be safe to leave these enabled.
- fix build on openSUSE 11.0
- Update to OpenCV 2.1.0:
* The whole OpenCV is now using exceptions instead of the old
libc-style mechanism
* Experimental "static" OpenCV configuration in CMake was
contributed by Jose Luis Blanco.
Pass "BUILD_SHARED_LIBS=OFF" to CMake to build OpenCV statically.
* new improved version of one-way descriptor is added
* User can now control the image areas visible after the stereo
rectification
* Fullscreen has been added (thanks to Yannick Verdie).
* Further info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- fix build with libpng14
- small spec file cleanup
- Moved to the KDE repositories to enable inclusion in kipi-plugins
- Initial package
OBS-URL: https://build.opensuse.org/request/show/714221
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/opencv?expand=0&rev=73
2019-07-17 13:13:58 +02:00
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%{_libdir}/pkgconfig/opencv4.pc
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Accepting request 714221 from science
- Update to version 4.1.0
* DNN module:
+ Reduced peak memory consumption for some models up to 30%.
+ Inference Engine
- Inference Engine 2018R3 is now a minimal supported version of IE.
- Myriad X (Intel® Neural Compute Stick 2) is now supported and tested.
- Automatic IR network reshaping for different inputs.
- Improved samples to work with models from OpenVINO Open Model Zoo
+ New networks from TensorFlow Object Detection API: Faster-RCNNs, SSDs
and Mask-RCNN with dilated convolutions, FPN SSD
* Performance improvements:
+ More optimization using AVX2 instruction set.
+ Automatic runtime dispatching is available for large set of functions
from core and imgproc modules.
* Other improvements:
+ Matplotlib Perceptually Uniform Sequential colormaps
+ Add keypoints matching visualization for real-time pose estimation tutorial
+ Add Hand-Eye calibration methods
+ Java: improved support for multidimensional arrays (Mat)
+ Dynamically loaded videoio backends (FFmpeg, GStreamer)
+ opencv_contrib: Robust local optical flow (RLOF) implementations
+ opencv_contrib: Implementation of Quasi Dense Stereo algorithm
+ opencv_contrib: New module: Image Quality Analysis (IQA) API
+ opencv_contrib: BRISQUE No Reference Image Quality Assessment (IQA) API
Check https://github.com/opencv/opencv/wiki/ChangeLog#version410
- Update to version 4.0.0
* A lot of C API from OpenCV 1.x has been removed. The affected modules are
objdetect, photo, video, videoio, imgcodecs, calib3d.
* Persistence (storing and loading structured data to/from XML, YAML or JSON)
in the core module has been completely reimplemented.
* OpenCV is now C++11 library and requires C++11-compliant compiler.
Thanks to the extended C++11 standard library, we could get rid of hand-crafted
cv::String and cv::Ptr. Now cv::String == std::string and cv::Ptr is a thin
wrapper on top of std::shared_ptr. Also, on Linux/BSD for cv::parallel_for_
we now use std::thread's instead of pthreads.
* DNN improvements
* Completely new module opencv_gapi has been added. It is the engine for very
efficient image processing, based on lazy evaluation and on-fly construction.
* Performance improvements
A few hundreds of basic kernels in OpenCV have been rewritten using so-called
"wide universal intrinsics". Those intrinsics map to SSE2, SSE4, AVX2, NEON or
VSX intrinsics, depending on the target platform and the compile flags.
* QR code detector and decoder have been added to opencv/objdetect module.
* The popular Kinect Fusion algorithm has been implemented, optimized for CPU and
GPU (OpenCL), and integrated into opencv_contrib/rgbd module.
* Very efficient and yet high-quality DIS dense optical flow algorithm has been
moved from opencv_contrib to opencv, video module. See the example.
* The slower TV L1 optical flow algorithm has been moved to opencv_contrib.
Check https://github.com/opencv/opencv/wiki/ChangeLog#version400
- Drop obsolete opencv-lib_suffix.patch
- Add 0001-Handle-absolute-OPENCV_INCLUDE_INSTALL_PATH-correctl.patch
- As this is a major version upgrade, the old 3.4.x package is still
available as opencv3
- Update to 3.4.3
* Compatibility fixes with python 3.7
* Added a new computational target DNN_TARGET_OPENCL_FP16
* Extended support of Intel's Inference Engine backend
* Enabled import of Intel's OpenVINO pre-trained networks from
intermediate representation (IR).
* tutorials improvements
Check https://github.com/opencv/opencv/wiki/ChangeLog#version343
for the complete changelog.
- Drop fix-build-i386-nosse.patch, build-workaround-issues-with-c.patch
(fixed upstream)
- Refresh patches
- Add patch to fix use of headers from C:
* build-workaround-issues-with-c.patch
- Update to 3.4.1:
* Added support for quantized TensorFlow networks
* OpenCV is now able to use Intel DL inference engine as DNN
acceleration backend
* Added AVX-512 acceleration to the performance-critical kernels
* For more information, read
https://github.com/opencv/opencv/wiki/ChangeLog#version341
- Update contrib modules to 3.4.1:
* No changelog available
- Change mechanism the contrib modules are built
- Include LICENSE of contrib tarball as well
- Build with python3 on >= 15
- Add patch to fix build on i386 without SSE:
* fix-build-i386-nosse.patch
- Refresh patches:
* fix_processor_detection_for_32bit_on_64bit.patch
* opencv-build-compare.patch
- Mention all libs explicitly
- Rebase 3.4.0 update from i@marguerite.su
- update to 3.4.0
* Added faster R-CNN support
* Javascript bindings have been extended to
cover DNN module
* DNN has been further accelerated for iGPU
using OpenCL
* On-disk caching of precompiled OpenCL
kernels has been finally implemented
* possible to load and run pre-compiled
OpenCL kernels via T-API
* Bit-exact 8-bit and 16-bit resize has been
implemented (currently supported only
bilinear interpolation)
- update face module to 3.4.0
- add opencv-lib_suffix.patch, remove LIB_SUFFIX
from OPENCV_LIB_INSTALL_PATH, as CMAKE_INSTALL
_LIBDIR is arch dependent.
- Add option to build without openblas
- Add conditionals for python2 and python3 to allow us enabling
only desired python variants when needed
- Do not depend on sphinx as py2 and py3 seem to collide there
- Readd opencv-gles.patch, it is *not* included upstream; otherwise
build breaks on all GLES Qt5 platforms (armv6l, armv7l, aarch64)
- add fix_processor_detection_for_32bit_on_64bit.patch
- Correctly set optimizations and dynamic dispatch on ARM, use
OpenCV 3.3 syntax on x86.
- Update licensing information
- change requires of python-numpy-devel to build in Leap and
to not break factory in future
- fix build error/unresolvable for Leap 42.2 and 42.3
- Update to version 3.3.1:
* Lots of various bugfixes
- Update source url
- Rename python subpackage to python2
- Do not explicitly require python-base for python subpackages
- Update to 3.3
- Dropped obsolete patches
* opencv-gcc6-fix-pch-support-PR8345.patch
* opencv-gles.patch
- Updated opencv-build-compare.patch
- Add 0001-Do-not-include-glx.h-when-using-GLES.patch
Fix build for 32bit ARM, including both GLES and desktop GL headers
causes incompatible pointer type errors
- Add conditional for the qt5/qt4 integration
* This is used only for gui tools, library is not affected
- Add provides/obsoletes for the qt5 packages to allow migration
- Drop patch opencv-qt5-sobump.diff
* Used only by the obsoleted qt5 variant
- Cleanup a bit with spec-cleaner
- Use %cmake macros
- Remove the conditions that are not really needed
- Add tests conditional disabled by default
* Many tests fail and there are missing testdata
- Switch to pkgconfig style dependencies
- Update to OpenCV 3.2.0
- Results from 11 GSoC 2016 projects have been submitted to the library:
+ sinusoidal patterns for structured light and phase unwrapping module
[Ambroise Moreau (Delia Passalacqua)]
+ DIS optical flow (excellent dense optical flow algorithm that is both
significantly better and significantly faster than Farneback’s algorithm –
our baseline), and learning-based color constancy algorithms implementation
[Alexander Bokov (Maksim Shabunin)]
+ CNN based tracking algorithm (GOTURN) [Tyan Vladimir (Antonella Cascitelli)]
+ PCAFlow and Global Patch Collider algorithms implementation
[Vladislav Samsonov (Ethan Rublee)]
+ Multi-language OpenCV Tutorials in Python, C++ and Java
[João Cartucho (Vincent Rabaud)]
+ New camera model and parallel processing for stitching pipeline
[Jiri Horner (Bo Li)]
+ Optimizations and improvements of dnn module
[Vitaliy Lyudvichenko (Anatoly Baksheev)]
+ Base64 and JSON support for file storage. Use names like
“myfilestorage.xml?base64” when writing file storage to store big chunks of
numerical data in base64-encoded form. [Iric Wu (Vadim Pisarevsky)]
+ tiny_dnn improvements and integration
[Edgar Riba (Manuele Tamburrano, Stefano Fabri)]
+ Quantization and semantic saliency detection with tiny_dnn
[Yida Wang (Manuele Tamburrano, Stefano Fabri)]
+ Word-spotting CNN based algorithm
[Anguelos Nicolaou (Lluis Gomez)]
- Contributions besides GSoC:
+ Greatly improved and accelerated dnn module in opencv_contrib:
- Many new layers, including deconvolution, LSTM etc.
- Support for semantic segmentation and SSD networks with samples.
- TensorFlow importer + sample that runs Inception net by Google.
+ More image formats and camera backends supported
+ Interactive camera calibration app
+ Multiple algorithms implemented in opencv_contrib
+ Supported latest OSes, including Ubuntu 16.04 LTS and OSX 10.12
+ Lot’s of optimizations for IA and ARM archs using parallelism, vector
instructions and new OpenCL kernels.
+ OpenCV now can use vendor-provided OpenVX and LAPACK/BLAS (including Intel MKL,
Apple’s Accelerate, OpenBLAS and Atlas) for acceleration
- Refreshed opencv-build-compare.patch
- Dropped upstream opencv-gcc5.patch
- Replace opencv-gcc6-disable-pch.patch with upstream patch
opencv-gcc6-fix-pch-support-PR8345.patch
- Enable TBB support (C++ threading library)
- Add dependency on openBLAS
- Enable ffmpeg support unconditional
- In case we build using GCC6 (or newer), add -mlra to CFLAGS to
workaround gcc bug
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=71294.
- Apply upstream patch opencv-gcc6-disable-pch.patch to disable
PCH for GCC6.
- Test for python versions greater than or equal to the current
version.
- Add python 3 support
- Added opencv_contrib_face-3.1.0.tar.bz2
* This tarball is created to take only the face module from the
contrib package. The Face module is required by libkface, which
in its turn is required by digikam.
- Added _constraints file to avoid random failures on small workers
(at least for builds on PMBS)
- Update to OpenCV 3.1.0
- A lot of new functionality has been introduced during Google
Summer of Code 2015:
+ “Omnidirectional Cameras Calibration and Stereo 3D
Reconstruction” – opencv_contrib/ccalib module
(Baisheng Lai, Bo Li)
+ “Structure From Motion” – opencv_contrib/sfm module
(Edgar Riba, Vincent Rabaud)
+ “Improved Deformable Part-based Models” – opencv_contrib/dpm
module (Jiaolong Xu, Bence Magyar)
+ “Real-time Multi-object Tracking using Kernelized Correlation
Filter” – opencv_contrib/tracking module
(Laksono Kurnianggoro, Fernando J. Iglesias Garcia)
+ “Improved and expanded Scene Text Detection” –
opencv_contrib/text module (Lluis Gomez, Vadim Pisarevsky)
+ “Stereo correspondence improvements” – opencv_contrib/stereo
module (Mircea Paul Muresan, Sergei Nosov)
+ “Structured-Light System Calibration” –
opencv_contrib/structured_light (Roberta Ravanelli,
Delia Passalacqua, Stefano Fabri, Claudia Rapuano)
+ “Chessboard+ArUco for camera calibration” –
opencv_contrib/aruco (Sergio Garrido, Prasanna, Gary Bradski)
+ “Implementation of universal interface for deep neural
network frameworks” – opencv_contrib/dnn module
(Vitaliy Lyudvichenko, Anatoly Baksheev)
+ “Recent advances in edge-aware filtering, improved SGBM
stereo algorithm” – opencv/calib3d and opencv_contrib/ximgproc
(Alexander Bokov, Maksim Shabunin)
+ “Improved ICF detector, waldboost implementation” –
opencv_contrib/xobjdetect (Vlad Shakhuro, Alexander Bovyrin)
+ “Multi-target TLD tracking” – opencv_contrib/tracking module
(Vladimir Tyan, Antonella Cascitelli)
+ “3D pose estimation using CNNs” – opencv_contrib/cnn_3dobj
(Yida Wang, Manuele Tamburrano, Stefano Fabri)
- Many great contributions made by the community, such as:
+ Support for HDF5 format
+ New/Improved optical flow algorithms
+ Multiple new image processing algorithms for filtering,
segmentation and feature detection
+ Superpixel segmentation and much more
- IPPICV is now based on IPP 9.0.1, which should make OpenCV
even faster on modern Intel chips
- opencv_contrib modules can now be included into the
opencv2.framework for iOS
- Newest operating systems are supported: Windows 10 and
OSX 10.11 (Visual Studio 2015 and XCode 7.1.1)
- Interoperability between T-API and OpenCL, OpenGL, DirectX and
Video Acceleration API on Linux, as well as Android 5 camera.
- HAL (Hardware Acceleration Layer) module functionality has been
moved into corresponding basic modules; the HAL replacement
mechanism has been implemented along with the examples
- Removed improve-sphinx-search.diff, opencv-altivec-vector.patch,
opencv-pkgconfig.patch and opencv-samples.patch, fixed upstream.
- Fixed opencv-qt5-sobump.diff, opencv-build-compare.patch,
opencv-gcc5.patch and opencv-gles.patch.
- Version OpenCV 3.0.0
+ ~1500 patches, submitted as PR @ github. All our patches go
the same route.
+ opencv_contrib (http://github.com/itseez/opencv_contrib)
repository has been added. A lot of new functionality is there
already! opencv_contrib is only compatible with 3.0/master,
not 2.4. Clone the repository and use “cmake …
-D OPENCV_EXTRA_MODULES_PATH=<path_to opencv_contrib/modules> …”
to build opencv and opencv_contrib together.
+ a subset of Intel IPP (IPPCV) is given to us and our users free
of charge, free of licensing fees, for commercial and
non-commerical use. It’s used by default in x86 and x64 builds
on Windows, Linux and Mac.
+ T-API (transparent API) has been introduced, this is transparent
GPU acceleration layer using OpenCL. It does not add any
compile-time or runtime dependency of OpenCL. When OpenCL is
available, it’s detected and used, but it can be disabled at
compile time or at runtime. It covers ~100 OpenCV functions.
This work has been done by contract and with generous support
from AMD and Intel companies.
+ ~40 OpenCV functions have been accelerated using NEON intrinsics
and because these are mostly basic functions, some higher-level
functions got accelerated as well.
+ There is also new OpenCV HAL layer that will simplifies creation
of NEON-optimized code and that should form a base for the
open-source and proprietary OpenCV accelerators.
+ The documentation is now in Doxygen: http://docs.opencv.org/master/
+ We cleaned up API of many high-level algorithms from features2d,
calib3d, objdetect etc. They now follow the uniform
“abstract interface – hidden implementation” pattern and make
extensive use of smart pointers (Ptr<>).
+ Greatly improved and extended Python & Java bindings (also,
see below on the Python bindings), newly introduced Matlab
bindings (still in alpha stage).
+ Improved Android support – now OpenCV Manager is in Java and
supports both 2.4 and 3.0.
+ Greatly improved WinRT support, including video capturing and
multi-threading capabilities. Thanks for Microsoft team for this!
+ Big thanks to Google who funded several successive GSoC programs
and let OpenCV in. The results of many successful GSoC 2013 and
2014 projects have been integrated in opencv 3.0 and
opencv_contrib (earlier results are also available in
OpenCV 2.4.x). We can name:
- text detection
- many computational photography algorithms (HDR, inpainting,
edge-aware filters, superpixels, …)
- tracking and optical flow algorithms
- new features, including line descriptors, KAZE/AKAZE
- general use optimization (hill climbing, linear programming)
- greatly improved Python support, including Python 3.0 support,
many new tutorials & samples on how to use OpenCV with Python.
- 2d shape matching module and 3d surface matching module
- RGB-D module
- VTK-based 3D visualization module
- etc.
+ Besides Google, we enjoyed (and hope that you will enjoy too)
many useful contributions from community, like:
- biologically inspired vision module
- DAISY features, LATCH descriptor, improved BRIEF
- image registration module
- etc.
- Reduce build-compare noise
opencv-build-compare.patch
- Remove BuildRequirement for python-sphinx in SLE12, since it's
not available there and it's not a mandatory requirement.
- Reduce differences between two spec files
- Use pkgconfig for ffmpeg BuildRequires
- Update improve-sphinx-search.diff for new python-Sphinx(1.3.1)
* now that sphinx-build disallow executing without arguments and
give you "Insufficient arguments" error, use "sphinx-build -h"
instead
* the default usages output ie. sphinx-build(or --help) no longer
are standard error but standard output, drop OUTPUT_QUIET and
add OUTPUT_VARIABLE throws the output to SPHINX_OUTPUT as well
- support gcc 5 (i.e. gcc versions without minor version):
opencv-gcc5.patch
- Update to OpenCV 2.4.11 - can't find NEWS or Changelog
merely collecting bug fixes while 3.0 is in the making, 2.4.11
didn't even make it on their web page, it's only on download
server
- remove opencv-underlinking.patch as obsolete
- remove upstream patch bomb_commit_gstreamer-1x-support.patch
- commenting out opencv-pkgconfig.patch - possibly it requires a rebase,
but the problem it tries to solve is unclear
- Add specific buildrequires for libpng15, so that we are
building against the system provided libpng.
- Update to OpenCV 2.4.9
More info at:
http://opencv.org/opencv-2-4-9-is-out.html
The brief list of changes:
* new 3D visualization module ‘viz’;
* performance fixes in ‘ocl’ module;
* fixes in Android Camera;
* improved CUDA support for mobile platforms;
* bugfixes from community;
* 55 reported bugs have been closed;
* 156 pull requests have been merged.
- Drop the BuildRequires on libucil and libunicap for Factory. This
stops us from getting ride of Gstreamer 0.10 and besides these two
libraries seem to be unmaintained upstream as that the latest
actions are from 2010
- Add upstream patch (3.0 version) to support Gstreamer 1.x
* bomb_commit_gstreamer-1x-support.patch
- Upstream now provides tarballs with source only as git tags
from github so update Source0 path.
- Add requires on various X extensions linked to opencv_ts module.
As those are present in the .pc file we need it anyway.
- Update to OpenCV 2.4.8
More info at:
http://opencv.org/opencv-2-4-8.html
The brief list of changes:
* NVidia CUDA support on Android devices with CUDA capable SoC and
CUDA sample;
* Concurrent kernel execution and user defined context support for
OpenCL;
* Integration with Intel Perceptual SDK and new depth sensors support
for Windows;
* 32 reported bugs have been closed;
* 139 pull requests have been merged;
- Fix build with altivec:
opencv-altivec-vector.patch
- Added opencv-pkgconfig.patch: make sure to provide link flags in
OpenCV pc file (bnc#853036)
- Update to OpenCV 2.4.7
More info at:
http://opencv.org/opencv-2-4-7-is-out.html
The brief list of changes:
* dynamic OpenCL runtime loading, setting default OpenCL device
via env var, many bug-fixes and some new optimization with OpenCL
* bug-fixes and new optimizations in CUDA stuff
* latest NDK and Android OS support, Native Android Camera tuning
* minor fixes, XAML sample and MS Certification compatibility
in WinRT stuff
* 382 pull requests have been merged
* 54 reported bugs have been fixed
- Added pkgconfig(glu) Requires to devel package, as per .pc file
- Make devel package provides also devel-static one
- Drop assume-Sphinx-is-there.diff, and add improve-sphinx-search.diff,
for properly finding sphinx with alphabetic chars in version
- Add patch assume-Sphinx-is-there.diff to fix building with
Sphinx versions that have alphanumeric characters in the version
(Only for factory builds at the moment)
- Use eigen3 instead of eigen2 as build requirement for openSUSE > 12.3.
- Enable compilation with libucil and libunicap.
- Removed dos2unix build requirement (not needed anymore).
- Update to OpenCV 2.4.6.1
More info at:
http://opencv.org/opencv-2-4-6-is-out.html
The brief list of changes:
* added video file i/o Windows RT and sample application using
camera, enabled parallelization with TBB or MS Concurrency
* added CUDA 5.5 support for desktop and ARM systems
* added Qt 5 support
* added many new OpenCL algorithms ports, included OpenCL binaries
into the Windows superpack
* iOS build scripts (together with Android ones) moved to
‘opencv/platforms’ directory
* added functions for UIImage <-> cv::Mat conversion
* correct front/back camera selection in Android app framework
* added Linaro NDK support and fixes for MIPS to Android CMake
toolchain
* stability has been improved by a lot, numerous bug-fixes across
all the library
- build with LFS_CFLAGS in 32 bit archs.
- Disable SSE3 for all architectures (bnc#814333)
- Disable SSE(2) on non x86_64 architectures, causes crashing
kde#276923, bnc#789173
- Update to OpenCV 2.4.5
More info at:
http://opencv.org/opencv-2-4-5-is-out.html
The brief list of changes:
* experimental WinRT support
* new video super-resolution module
* CLAHE (adaptive histogram equalization) algorithm on both CPU
and GPU
* further improvements and extensions in ocl module
(stereo block matching and belief propagation have been added,
fixed crashes on Intel HD4000)
* Visual Studio 2012 cv::Mat visualizer plugin debugger tutorial
from Microsoft Research
* OpenCV4Android SDK improvements
(NDK r8e support, native activity sample using OpenCV Manager,
bug-fixes)
* ~25 reported problems have been resolved since 2.4.4, ~78 pull
requests have been merged, thanks everybody who participated!
- Update to OpenCV 2.4.4
More info at:
http://opencv.org/opencv-2-4-4-is-out.html
The brief list of changes:
* OpenCV Java bindings are ported from Android to desktop Java!
Actually any JVM language will work, see Tutorial for details,
and Java or Scala code samples.
* Android application framework, samples, tutorials, and OpenCV
Manager are improved.
* Optimizations for the new NVIDIA Kepler architecture, CARMA
platform support and other new optimizations in CUDA.
* OpenCL module now builds successfully with various SDKs (from
AMD, NVIDIA, Intel and Apple) and runs well on different GPUs
(AMD, NVidia, Intel HD4000). A lot of new functionality has been
added, tons of bugs fixed, performance of many functions has
been significantly improved.
* 100+ reported problems have been resolved since 2.4.3, thanks
everybody who participated!
- Drop the buildrequire for libxine
- Update to OpenCV 2.4.3
More info at:
http://opencv.org/opencv-2-4-3-released.html
The nicely formatted changelog can be seen here:
http://code.opencv.org/projects/opencv/wiki/ChangeLog;
here are the highlights:
* A lot of good stuff from the Google Summer of Code 2012 has been
integrated; this was a very productive summer!
* Significantly improved and optimized Android and iOS ports.
* Greatly extended GPU (i.e. CUDA-based) module.
* The brand new ocl (OpenCL-based) module that unleashes GPU power
also for AMD and Intel GPU users. It’s not included into the
binary package, since there are different SDKs, and it’s not
turned on by default. You need to run CMake and turn on
“WITH_OPENCL”. Also, please note that this is very first version
of the module, so it may be not very stable and not very
functional.
* Much better performance on many-core systems out of the box. You
do not need TBB anymore on MacOSX, iOS and Windows. BTW, the
binary package for Windows is now built without TBB support.
Libraries and DLLs for Visual Studio 2010 use the Concurrency
framework.
* About 130 bugs have been fixed since 2.4.2.
* Since 2.4.3rc we fixed several more problems, in particular some
compile problems with iOS 6 SDK.
- buildrequire glu
- Update to OpenCV 2.4.2
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Drop opencv-datadir.patch to comply with upstream directory layout
- Update to OpenCV 2.4.1
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Update to OpenCV 2.4.0
More info at:
http://code.opencv.org/projects/opencv/wiki/ChangeLog
- Add opencv-gcc47.patch: Fix build with gcc 4.7.
- Use Explicit Buildrequires on several needed libraries
future dependency cleanups may/will cause build to fail otherwise.
- Add upstream r6881 to fix clang compatibility
- uncomment libraries not in 12.1 for now
- Changed groups (fix for RPMLINT warning)
- Added check for duplicate files (fix for RPMLINT warning)
- Added py_requires macros and python-base dependencies (fix for RPMLINT warning)
- Escaped macros (fix for RPMLINT warning)
- Fixed end-of-line encoding problems (fix for RPMLINT warning)
- Added libeigen2-devel buildrequires
- Added libunicap and libucil buildrequires (libunicap supports requires libucil)
- Cleaned up spec file formatting
- Dropped opencv-2.3-ffmpeg.patch, applied upstream
- Revive opencv-2.3-ffmpeg.patch, needs rebase
- Tag all patches according to openSUSE packaging guidelines
- Removed opencv-2.3-cmake.patch, old cmake cannot be used any more.
- Python bindings cannot be built without NumPy any more.
- Update to OpenCV 2.3.1
- Update and readd opencv-2.3-underlinking.patch since it is still
necessary.
- Fix support for new ffmpeg versions
- Removed unnecessary patches
- Enable Python NumPy support on openSUSE 11.2
- Build Qt instead of Gtk GUI
- Fix cmake files for openSUSE 11.1
- No GStreamer support on openSUSE 11.1
- Update to OpenCV 2.3.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Fix build on openSUSE 11.2
- Add opencv-v4l-2.6.38.patch: use the new libv4l2 interface
- Enable Python NumPy support
- SWIG is not required any more
- Enable OpenEXR support
- Update to OpenCV 2.2.0.
More info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- Use system zlib, oh, and do not export ZLIB symbols to
other applications, clashes ensued.
- fix build with gcc 4.6
- add -underlinking patch
- devel package renamed to opencv-devel, so that switching between
OBS and packman opencv packages is easier
- fix gstreamer support
- fix xine support
- fix some rpmlint warnings
- fix shared libraries permissions
- Do not waste resources building the tests as we do not run them
- Do not disable SSE,SSE2,etc. According to OpenCV changelog,
it should be safe to leave these enabled.
- fix build on openSUSE 11.0
- Update to OpenCV 2.1.0:
* The whole OpenCV is now using exceptions instead of the old
libc-style mechanism
* Experimental "static" OpenCV configuration in CMake was
contributed by Jose Luis Blanco.
Pass "BUILD_SHARED_LIBS=OFF" to CMake to build OpenCV statically.
* new improved version of one-way descriptor is added
* User can now control the image areas visible after the stereo
rectification
* Fullscreen has been added (thanks to Yannick Verdie).
* Further info at:
http://opencv.willowgarage.com/wiki/OpenCV%20Change%20Logs
- fix build with libpng14
- small spec file cleanup
- Moved to the KDE repositories to enable inclusion in kipi-plugins
- Initial package
OBS-URL: https://build.opensuse.org/request/show/714221
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/opencv?expand=0&rev=73
2019-07-17 13:13:58 +02:00
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%dir %{_libdir}/cmake/opencv4
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%{_libdir}/cmake/opencv4/OpenCVConfig*.cmake
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%{_libdir}/cmake/opencv4/OpenCVModules*.cmake
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%{_datadir}/opencv4/valgrind*
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2010-03-08 18:16:50 +01:00
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2018-01-16 09:32:34 +01:00
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%if %{with python3}
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2024-02-05 08:31:49 +01:00
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%files %{python_files %{name}}
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2018-06-02 11:53:10 +02:00
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%license LICENSE LICENSE.contrib
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2024-02-05 08:31:49 +01:00
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%{python_sitearch}/cv2.*.so
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2018-01-16 09:32:34 +01:00
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%endif
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2016-03-26 15:20:54 +01:00
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2013-08-01 15:56:40 +02:00
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%files doc
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%{_docdir}/%{name}-doc/
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2010-03-08 18:16:50 +01:00
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%changelog
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