forked from pool/python-pydicom
50d3c94106
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python/python-pydicom?expand=0&rev=32
102 lines
4.4 KiB
Diff
102 lines
4.4 KiB
Diff
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Index: pydicom-2.4.4/pydicom/pixel_data_handlers/pillow_handler.py
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===================================================================
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--- pydicom-2.4.4.orig/pydicom/pixel_data_handlers/pillow_handler.py
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+++ pydicom-2.4.4/pydicom/pixel_data_handlers/pillow_handler.py
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@@ -255,14 +255,14 @@ def get_pixeldata(ds: "Dataset") -> "num
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if ds.PixelRepresentation == 1:
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# Pillow converts signed data to unsigned
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# so we need to undo this conversion
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- arr -= 2**(bits_allocated - 1)
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+ arr -= numpy.uint32(2**(bits_allocated - 1))
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if shift:
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arr = numpy.right_shift(arr, shift)
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else:
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# Corrections based on dataset elements
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if ds.PixelRepresentation == 1:
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- arr -= 2**(bits_allocated - 1)
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+ arr -= numpy.uint32(2**(bits_allocated - 1))
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if shift:
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arr = numpy.right_shift(arr, shift)
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Index: pydicom-2.4.4/pydicom/pixel_data_handlers/pylibjpeg_handler.py
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===================================================================
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--- pydicom-2.4.4.orig/pydicom/pixel_data_handlers/pylibjpeg_handler.py
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+++ pydicom-2.4.4/pydicom/pixel_data_handlers/pylibjpeg_handler.py
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@@ -66,11 +66,7 @@ except ImportError:
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HAVE_PYLIBJPEG = False
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if HAVE_PYLIBJPEG:
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- try:
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- from pylibjpeg.utils import get_pixel_data_decoders
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- except ImportError:
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- # Old import, deprecated in 1.2, removal in 2.0
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- from pylibjpeg.pydicom.utils import get_pixel_data_decoders
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+ from pylibjpeg.utils import get_pixel_data_decoders, Decoder
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try:
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import openjpeg
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@@ -249,7 +245,7 @@ def generate_frames(
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"elements are missing from the dataset: " + ", ".join(missing)
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)
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- decoder = _DECODERS[tsyntax]
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+ decoder = cast(Decoder, _DECODERS[tsyntax])
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LOGGER.debug(f"Decoding {tsyntax.name} encoded Pixel Data using {decoder}")
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nr_frames = getattr(ds, "NumberOfFrames", 1)
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@@ -260,7 +256,7 @@ def generate_frames(
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bits_allocated = cast(int, ds.BitsAllocated)
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for frame in generate_pixel_data_frame(ds.PixelData, nr_frames):
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- arr = decoder(frame, pixel_module)
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+ arr = decoder(frame, ds=pixel_module)
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if (
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tsyntax in [JPEG2000, JPEG2000Lossless]
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Index: pydicom-2.4.4/pydicom/tests/test_encoders_pydicom.py
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===================================================================
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--- pydicom-2.4.4.orig/pydicom/tests/test_encoders_pydicom.py
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+++ pydicom-2.4.4/pydicom/tests/test_encoders_pydicom.py
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@@ -444,7 +444,7 @@ class TestRLEEncodeFrame:
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assert ds.SamplesPerPixel == 3
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assert ds.PixelRepresentation == 0
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- arr = ref.newbyteorder('>')
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+ arr = ref.view(ref.dtype.newbyteorder('>'))
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assert id(arr) != id(ref)
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assert arr.dtype == '>u2'
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encoded = rle_encode_frame(arr)
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Index: pydicom-2.4.4/pydicom/pixel_data_handlers/util.py
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===================================================================
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--- pydicom-2.4.4.orig/pydicom/pixel_data_handlers/util.py
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+++ pydicom-2.4.4/pydicom/pixel_data_handlers/util.py
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@@ -200,7 +200,7 @@ def apply_color_lut(
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# IVs >= `first_map` are mapped by the Palette Color LUTs
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# `first_map` may be negative, positive or 0
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mapped_pixels = arr >= first_map
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- clipped_iv[mapped_pixels] = arr[mapped_pixels] - first_map
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+ clipped_iv[mapped_pixels] = arr[mapped_pixels] - np.int32(first_map)
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# IVs > number of entries get set to last entry
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np.clip(clipped_iv, 0, nr_entries - 1, out=clipped_iv)
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@@ -276,7 +276,7 @@ def apply_modality_lut(arr: "np.ndarray"
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# IVs >= `first_map` are mapped by the Modality LUT
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# `first_map` may be negative, positive or 0
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mapped_pixels = arr >= first_map
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- clipped_iv[mapped_pixels] = arr[mapped_pixels] - first_map
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+ clipped_iv[mapped_pixels] = arr[mapped_pixels] - np.int32(first_map)
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# IVs > number of entries get set to last entry
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np.clip(clipped_iv, 0, nr_entries - 1, out=clipped_iv)
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@@ -458,7 +458,7 @@ def apply_voi(
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# IVs >= `first_map` are mapped by the VOI LUT
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# `first_map` may be negative, positive or 0
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mapped_pixels = arr >= first_map
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- clipped_iv[mapped_pixels] = arr[mapped_pixels] - first_map
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+ clipped_iv[mapped_pixels] = arr[mapped_pixels] - np.int32(first_map)
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# IVs > number of entries get set to last entry
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np.clip(clipped_iv, 0, nr_entries - 1, out=clipped_iv)
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