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