36 lines
1.5 KiB
Python
36 lines
1.5 KiB
Python
#!/usr/bin/env python
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# Python 2/3 compatibility
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from __future__ import print_function
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import cv2
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import numpy as np
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from tests_common import NewOpenCVTests
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class TestGoodFeaturesToTrack_test(NewOpenCVTests):
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def test_goodFeaturesToTrack(self):
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arr = self.get_sample('samples/data/lena.jpg', 0)
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original = arr.copy(True)
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threshes = [ x / 100. for x in range(1,10) ]
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numPoints = 20000
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results = dict([(t, cv2.goodFeaturesToTrack(arr, numPoints, t, 2, useHarrisDetector=True)) for t in threshes])
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# Check that GoodFeaturesToTrack has not modified input image
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self.assertTrue(arr.tostring() == original.tostring())
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# Check for repeatability
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for i in range(1):
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results2 = dict([(t, cv2.goodFeaturesToTrack(arr, numPoints, t, 2, useHarrisDetector=True)) for t in threshes])
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for t in threshes:
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self.assertTrue(len(results2[t]) == len(results[t]))
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for i in range(len(results[t])):
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self.assertTrue(cv2.norm(results[t][i][0] - results2[t][i][0]) == 0)
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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.assertTrue(len(r0) > len(r1))
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# Increasing thresh should monly truncate result list
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for i in range(len(r1)):
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self.assertTrue(cv2.norm(r1[i][0] - r0[i][0])==0) |