92 lines
2.3 KiB
Python
Executable File
92 lines
2.3 KiB
Python
Executable File
#!/usr/bin/env python
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'''
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This sample demonstrates SEEDS Superpixels segmentation
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Use [space] to toggle output mode
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Usage:
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seeds.py [<video source>]
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'''
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import numpy as np
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import cv2 as cv
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# relative module
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import video
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# built-in module
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import sys
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if __name__ == '__main__':
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print __doc__
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try:
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fn = sys.argv[1]
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except:
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fn = 0
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def nothing(*arg):
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pass
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cv.namedWindow('SEEDS')
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cv.createTrackbar('Number of Superpixels', 'SEEDS', 400, 1000, nothing)
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cv.createTrackbar('Iterations', 'SEEDS', 4, 12, nothing)
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seeds = None
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display_mode = 0
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num_superpixels = 400
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prior = 2
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num_levels = 4
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num_histogram_bins = 5
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cap = video.create_capture(fn)
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while True:
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flag, img = cap.read()
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converted_img = cv.cvtColor(img, cv.COLOR_BGR2HSV)
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height,width,channels = converted_img.shape
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num_superpixels_new = cv.getTrackbarPos('Number of Superpixels', 'SEEDS')
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num_iterations = cv.getTrackbarPos('Iterations', 'SEEDS')
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if not seeds or num_superpixels_new != num_superpixels:
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num_superpixels = num_superpixels_new
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seeds = cv.ximgproc.createSuperpixelSEEDS(width, height, channels,
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num_superpixels, num_levels, prior, num_histogram_bins)
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color_img = np.zeros((height,width,3), np.uint8)
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color_img[:] = (0, 0, 255)
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seeds.iterate(converted_img, num_iterations)
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# retrieve the segmentation result
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labels = seeds.getLabels()
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# labels output: use the last x bits to determine the color
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num_label_bits = 2
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labels &= (1<<num_label_bits)-1
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labels *= 1<<(16-num_label_bits)
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mask = seeds.getLabelContourMask(False)
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# stitch foreground & background together
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mask_inv = cv.bitwise_not(mask)
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result_bg = cv.bitwise_and(img, img, mask=mask_inv)
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result_fg = cv.bitwise_and(color_img, color_img, mask=mask)
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result = cv.add(result_bg, result_fg)
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if display_mode == 0:
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cv.imshow('SEEDS', result)
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elif display_mode == 1:
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cv.imshow('SEEDS', mask)
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else:
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cv.imshow('SEEDS', labels)
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ch = cv.waitKey(1)
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if ch == 27:
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break
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elif ch & 0xff == ord(' '):
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display_mode = (display_mode + 1) % 3
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cv.destroyAllWindows()
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