Open Source Computer Vision Library
https://opencv.org/
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45 lines
1.4 KiB
45 lines
1.4 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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from tests_common import NewOpenCVTests |
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class cuda_test(NewOpenCVTests): |
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def setUp(self): |
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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((200, 200, 3)) * 255).astype(np.uint8) |
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gpuMat = cv.cuda_GpuMat() |
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gpuMat.upload(npMat) |
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self.assertTrue(np.allclose(gpuMat.download(), npMat)) |
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def test_cuda_imgproc_cvtColor(self): |
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npMat = (np.random.random((200, 200, 3)) * 255).astype(np.uint8) |
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gpuMat = cv.cuda_GpuMat() |
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gpuMat.upload(npMat) |
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gpuMat2 = cv.cuda.cvtColor(gpuMat, cv.COLOR_BGR2HSV) |
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self.assertTrue(np.allclose(gpuMat2.download(), cv.cvtColor(npMat, cv.COLOR_BGR2HSV))) |
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def test_cuda_filter_laplacian(self): |
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npMat = (np.random.random((200, 200)) * 255).astype(np.uint16) |
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gpuMat = cv.cuda_GpuMat() |
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gpuMat.upload(npMat) |
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gpuMat = cv.cuda.createLaplacianFilter(cv.CV_16UC1, -1, ksize=3).apply(gpuMat) |
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self.assertTrue(np.allclose(gpuMat.download(), cv.Laplacian(npMat, cv.CV_16UC1, ksize=3))) |
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if __name__ == '__main__': |
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NewOpenCVTests.bootstrap()
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