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Open Source Computer Vision Library
https://opencv.org/
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62 lines
1.9 KiB
62 lines
1.9 KiB
import numpy as np |
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import cv2, cv |
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from common import Sketcher |
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help_message = ''' |
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USAGE: watershed.py [<image>] |
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Use keys 1 - 7 to switch marker color |
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SPACE - update segmentation |
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r - reset |
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a - switch autoupdate |
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ESC - exit |
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''' |
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class App: |
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def __init__(self, fn): |
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self.img = cv2.imread(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 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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cv2.watershed(self.img, m) |
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vis = np.uint8( (self.img + self.colors[np.maximum(m, 0)]) / 2 ) |
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cv2.imshow('watershed', vis) |
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def run(self): |
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while True: |
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ch = cv2.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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if __name__ == '__main__': |
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import sys |
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try: fn = sys.argv[1] |
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except: fn = '../cpp/fruits.jpg' |
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print help_message |
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App(fn).run()
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