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Open Source Computer Vision Library
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35 lines
1.3 KiB
35 lines
1.3 KiB
15 years ago
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import cv
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import unittest
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class TestGoodFeaturesToTrack(unittest.TestCase):
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def test(self):
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arr = cv.LoadImage("../samples/c/lena.jpg", 0)
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original = cv.CloneImage(arr)
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size = cv.GetSize(arr)
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eig_image = cv.CreateImage(size, cv.IPL_DEPTH_32F, 1)
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temp_image = cv.CreateImage(size, cv.IPL_DEPTH_32F, 1)
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threshes = [ x / 100. for x in range(1,10) ]
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results = dict([(t, cv.GoodFeaturesToTrack(arr, eig_image, temp_image, 20000, t, 2, use_harris = 1)) for t in threshes])
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# Check that GoodFeaturesToTrack has not modified input image
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self.assert_(arr.tostring() == original.tostring())
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# Check for repeatability
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for i in range(10):
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results2 = dict([(t, cv.GoodFeaturesToTrack(arr, eig_image, temp_image, 20000, t, 2, use_harris = 1)) for t in threshes])
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self.assert_(results == results2)
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for t0,t1 in zip(threshes, threshes[1:]):
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r0 = results[t0]
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r1 = results[t1]
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# Increasing thresh should make result list shorter
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self.assert_(len(r0) > len(r1))
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# Increasing thresh should monly truncate result list
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self.assert_(r0[:len(r1)] == r1)
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if __name__ == '__main__':
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unittest.main()
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