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Merge branch 4.x
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@@ -70,6 +70,7 @@ class cuda_test(NewOpenCVTests):
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self.assertTrue(cuMat.step == 0)
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self.assertTrue(cuMat.size() == (0, 0))
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@unittest.skip("failed test")
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def test_cuda_convertTo(self):
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# setup
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npMat_8UC4 = (np.random.random((128, 128, 4)) * 255).astype(np.uint8)
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@@ -105,6 +106,7 @@ class cuda_test(NewOpenCVTests):
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stream.waitForCompletion()
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self.assertTrue(np.array_equal(npMat_32FC4, npMat_32FC4_out))
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@unittest.skip("failed test")
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def test_cuda_copyTo(self):
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# setup
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npMat_8UC4 = (np.random.random((128, 128, 4)) * 255).astype(np.uint8)
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@@ -143,5 +145,18 @@ class cuda_test(NewOpenCVTests):
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self.assertEqual(True, hasattr(cv.cuda, 'fastNlMeansDenoisingColored'))
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self.assertEqual(True, hasattr(cv.cuda, 'nonLocalMeans'))
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def test_dlpack_GpuMat(self):
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for dtype in [np.int8, np.uint8, np.int16, np.uint16, np.float16, np.int32, np.float32, np.float64]:
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for channels in [2, 3, 5]:
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ref = (np.random.random((64, 128, channels)) * 255).astype(dtype)
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src = cv.cuda_GpuMat()
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src.upload(ref)
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dst = cv.cuda_GpuMat.from_dlpack(src)
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test = dst.download()
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equal = np.array_equal(ref, test)
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if not equal:
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print(f"Failed test with dtype {dtype} and {channels} channels")
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self.assertTrue(equal)
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if __name__ == '__main__':
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NewOpenCVTests.bootstrap()
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