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Open Source Computer Vision Library
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38 lines
1.0 KiB
38 lines
1.0 KiB
#!/usr/bin/env python |
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''' |
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CUDA-accelerated Computer Vision functions |
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''' |
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# Python 2/3 compatibility |
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from __future__ import print_function |
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import numpy as np |
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import cv2 as cv |
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import os |
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from tests_common import NewOpenCVTests, unittest |
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class cuda_test(NewOpenCVTests): |
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def setUp(self): |
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super(cuda_test, self).setUp() |
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if not cv.cuda.getCudaEnabledDeviceCount(): |
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self.skipTest("No CUDA-capable device is detected") |
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def test_cuda_upload_download(self): |
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npMat = (np.random.random((128, 128, 3)) * 255).astype(np.uint8) |
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cuMat = cv.cuda_GpuMat() |
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cuMat.upload(npMat) |
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self.assertTrue(np.allclose(cuMat.download(), npMat)) |
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def test_cuda_interop(self): |
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npMat = (np.random.random((128, 128, 3)) * 255).astype(np.uint8) |
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cuMat = cv.cuda_GpuMat() |
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cuMat.upload(npMat) |
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self.assertTrue(cuMat.cudaPtr() != 0) |
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stream = cv.cuda_Stream() |
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self.assertTrue(stream.cudaPtr() != 0) |
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if __name__ == '__main__': |
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NewOpenCVTests.bootstrap()
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