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Open Source Computer Vision Library
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33 lines
974 B
33 lines
974 B
#!/usr/bin/env python |
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''' |
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Watershed segmentation test |
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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 |
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from tests_common import NewOpenCVTests |
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class watershed_test(NewOpenCVTests): |
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def test_watershed(self): |
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img = self.get_sample('cv/inpaint/orig.png') |
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markers = self.get_sample('cv/watershed/wshed_exp.png', 0) |
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refSegments = self.get_sample('cv/watershed/wshed_segments.png') |
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if img is None or markers is None: |
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self.assertEqual(0, 1, 'Missing test data') |
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colors = np.int32( list(np.ndindex(3, 3, 3)) ) * 122 |
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cv2.watershed(img, np.int32(markers)) |
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segments = colors[np.maximum(markers, 0)] |
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if refSegments is None: |
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refSegments = segments.copy() |
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cv2.imwrite(self.extraTestDataPath + '/cv/watershed/wshed_segments.png', refSegments) |
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self.assertLess(cv2.norm(segments - refSegments, cv2.NORM_L1) / 255.0, 50) |