86 lines
2.3 KiB
Python
86 lines
2.3 KiB
Python
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#!/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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