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47 lines
1.6 KiB
47 lines
1.6 KiB
#!/usr/bin/env python |
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import os |
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import cv2 as cv |
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import numpy as np |
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from tests_common import NewOpenCVTests, unittest |
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class cudafeatures2d_test(NewOpenCVTests): |
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def setUp(self): |
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super(cudafeatures2d_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_cudafeatures2d(self): |
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npMat1 = self.get_sample("samples/data/right01.jpg") |
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npMat2 = self.get_sample("samples/data/right02.jpg") |
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cuMat1 = cv.cuda_GpuMat() |
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cuMat2 = cv.cuda_GpuMat() |
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cuMat1.upload(npMat1) |
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cuMat2.upload(npMat2) |
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cuMat1 = cv.cuda.cvtColor(cuMat1, cv.COLOR_RGB2GRAY) |
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cuMat2 = cv.cuda.cvtColor(cuMat2, cv.COLOR_RGB2GRAY) |
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fast = cv.cuda_FastFeatureDetector.create() |
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_kps = fast.detectAsync(cuMat1) |
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orb = cv.cuda_ORB.create() |
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_kps1, descs1 = orb.detectAndComputeAsync(cuMat1, None) |
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_kps2, descs2 = orb.detectAndComputeAsync(cuMat2, None) |
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self.assertTrue(len(orb.convert(_kps1)) == _kps1.size()[0]) |
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self.assertTrue(len(orb.convert(_kps2)) == _kps2.size()[0]) |
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bf = cv.cuda_DescriptorMatcher.createBFMatcher(cv.NORM_HAMMING) |
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matches = bf.match(descs1, descs2) |
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self.assertGreater(len(matches), 0) |
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matches = bf.knnMatch(descs1, descs2, 2) |
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self.assertGreater(len(matches), 0) |
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matches = bf.radiusMatch(descs1, descs2, 0.1) |
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self.assertGreater(len(matches), 0) |
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self.assertTrue(True) #It is sufficient that no exceptions have been there |
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if __name__ == '__main__': |
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NewOpenCVTests.bootstrap() |