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#!/usr/bin/env python
'''
Watershed segmentation test
'''
# Python 2/3 compatibility
from __future__ import print_function
import numpy as np
import cv2
from tests_common import NewOpenCVTests
class watershed_test(NewOpenCVTests):
def test_watershed(self):
img = self.get_sample('cv/inpaint/orig.png')
markers = self.get_sample('cv/watershed/wshed_exp.png', 0)
refSegments = self.get_sample('cv/watershed/wshed_segments.png')
if img is None or markers is None:
self.assertEqual(0, 1, 'Missing test data')
colors = np.int32( list(np.ndindex(3, 3, 3)) ) * 122
cv2.watershed(img, np.int32(markers))
segments = colors[np.maximum(markers, 0)]
if refSegments is None:
refSegments = segments.copy()
cv2.imwrite(self.extraTestDataPath + '/cv/watershed/wshed_segments.png', refSegments)
self.assertLess(cv2.norm(segments - refSegments, cv2.NORM_L1) / 255.0, 50)
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