Daniel Garcia
f6921517ab
- Update to 0.5 * No release notes found OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-pyssim?expand=0&rev=9
70 lines
2.4 KiB
Diff
70 lines
2.4 KiB
Diff
From fa854ac6b4c2a691a418cfac0eb5a2305731576c Mon Sep 17 00:00:00 2001
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From: "adria.labay" <adria.labay@gmail.com>
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Date: Wed, 8 Feb 2023 15:40:36 +0100
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Subject: [PATCH] support numpy 1.20
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---
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ssim/utils.py | 26 ++++++++++++--------------
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1 file changed, 12 insertions(+), 14 deletions(-)
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Index: pyssim-0.5/ssim/utils.py
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===================================================================
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--- pyssim-0.5.orig/ssim/utils.py
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+++ pyssim-0.5/ssim/utils.py
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@@ -2,31 +2,29 @@
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from __future__ import absolute_import
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-import numpy
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-from numpy.ma.core import exp
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+import numpy as np
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import scipy.ndimage
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from ssim.compat import ImageOps
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+
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def convolve_gaussian_2d(image, gaussian_kernel_1d):
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"""Convolve 2d gaussian."""
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- result = scipy.ndimage.filters.correlate1d(
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+ result = scipy.ndimage.correlate1d(
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image, gaussian_kernel_1d, axis=0)
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- result = scipy.ndimage.filters.correlate1d(
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+ return scipy.ndimage.correlate1d(
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result, gaussian_kernel_1d, axis=1)
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- return result
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+
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def get_gaussian_kernel(gaussian_kernel_width=11, gaussian_kernel_sigma=1.5):
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"""Generate a gaussian kernel."""
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# 1D Gaussian kernel definition
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- gaussian_kernel_1d = numpy.ndarray((gaussian_kernel_width))
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- norm_mu = int(gaussian_kernel_width / 2)
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+ gaussian_kernel_1d = np.arange(0, gaussian_kernel_width, 1.)
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+ gaussian_kernel_1d -= gaussian_kernel_width / 2
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+ gaussian_kernel_1d = np.exp(-0.5 * gaussian_kernel_1d**2 /
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+ gaussian_kernel_sigma**2)
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+ return gaussian_kernel_1d / np.sum(gaussian_kernel_1d)
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- # Fill Gaussian kernel
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- for i in range(gaussian_kernel_width):
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- gaussian_kernel_1d[i] = (exp(-(((i - norm_mu) ** 2)) /
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- (2 * (gaussian_kernel_sigma ** 2))))
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- return gaussian_kernel_1d / numpy.sum(gaussian_kernel_1d)
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def to_grayscale(img):
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"""Convert PIL image to numpy grayscale array and numpy alpha array.
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@@ -37,11 +35,11 @@ def to_grayscale(img):
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Returns:
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(gray, alpha): both numpy arrays.
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"""
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- gray = numpy.asarray(ImageOps.grayscale(img)).astype(numpy.float)
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+ gray = np.asarray(ImageOps.grayscale(img)).astype(float)
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imbands = img.getbands()
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alpha = None
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if 'A' in imbands:
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- alpha = numpy.asarray(img.split()[-1]).astype(numpy.float)
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+ alpha = np.asarray(img.split()[-1]).astype(float)
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return gray, alpha
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