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Removed obsolete python samples #25268 Clean Samples #25006 This PR removes 36 obsolete python samples from the project, as part of an effort to keep the codebase clean and focused on current best practices. Some of these samples will be updated with latest algorithms or will be combined with other existing samples. Removed Samples: > browse.py camshift.py coherence.py color_histogram.py contours.py deconvolution.py dft.py dis_opt_flow.py distrans.py edge.py feature_homography.py find_obj.py fitline.py gabor_threads.py hist.py houghcircles.py houghlines.py inpaint.py kalman.py kmeans.py laplace.py lk_homography.py lk_track.py logpolar.py mosse.py mser.py opt_flow.py plane_ar.py squares.py stitching.py text_skewness_correction.py texture_flow.py turing.py video_threaded.py video_v4l2.py watershed.py These changes aim to improve the repository's clarity and usability by removing examples that are no longer relevant or have been superseded by more up-to-date techniques.
86 lines
2.3 KiB
Python
Executable File
86 lines
2.3 KiB
Python
Executable File
#!/usr/bin/env python
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'''
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Watershed segmentation
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=========
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This program demonstrates the watershed segmentation algorithm
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in OpenCV: watershed().
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Usage
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-----
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watershed.py [image filename]
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Keys
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----
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1-7 - switch marker color
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SPACE - update segmentation
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r - reset
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a - toggle autoupdate
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ESC - exit
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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 as cv
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from common import Sketcher
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class App:
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def __init__(self, fn):
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self.img = cv.imread(fn)
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if self.img is None:
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raise Exception('Failed to load image file: %s' % fn)
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h, w = self.img.shape[:2]
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self.markers = np.zeros((h, w), np.int32)
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self.markers_vis = self.img.copy()
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self.cur_marker = 1
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self.colors = np.int32( list(np.ndindex(2, 2, 2)) ) * 255
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self.auto_update = True
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self.sketch = Sketcher('img', [self.markers_vis, self.markers], self.get_colors)
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def get_colors(self):
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return list(map(int, self.colors[self.cur_marker])), self.cur_marker
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def watershed(self):
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m = self.markers.copy()
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cv.watershed(self.img, m)
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overlay = self.colors[np.maximum(m, 0)]
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vis = cv.addWeighted(self.img, 0.5, overlay, 0.5, 0.0, dtype=cv.CV_8UC3)
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cv.imshow('watershed', vis)
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def run(self):
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while cv.getWindowProperty('img', 0) != -1 or cv.getWindowProperty('watershed', 0) != -1:
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ch = cv.waitKey(50)
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if ch == 27:
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break
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if ch >= ord('1') and ch <= ord('7'):
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self.cur_marker = ch - ord('0')
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print('marker: ', self.cur_marker)
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if ch == ord(' ') or (self.sketch.dirty and self.auto_update):
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self.watershed()
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self.sketch.dirty = False
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if ch in [ord('a'), ord('A')]:
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self.auto_update = not self.auto_update
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print('auto_update if', ['off', 'on'][self.auto_update])
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if ch in [ord('r'), ord('R')]:
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self.markers[:] = 0
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self.markers_vis[:] = self.img
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self.sketch.show()
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cv.destroyAllWindows()
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if __name__ == '__main__':
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print(__doc__)
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import sys
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try:
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fn = sys.argv[1]
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except:
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fn = 'fruits.jpg'
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App(cv.samples.findFile(fn)).run()
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