opencv/samples/python2/kmeans.py
flp 4ed2d6328b Python samples adapted for Python3 compatibility
Common fixes:
- print function
- int / float division
- map, zip iterators in py3 but lists in py2

Known bugs with opencv 3.0.0
- digits.py, called via digits_video.py: https://github.com/Itseez/opencv/issues/4969
- gaussian_mix.py: https://github.com/Itseez/opencv/pull/4232
- video_v4l2.py: https://github.com/Itseez/opencv/pull/5474

Not working:
- letter_recog.py due to changed ml_StatModel.train() signature
2015-12-13 02:49:54 +01:00

51 lines
1.2 KiB
Python
Executable File

#!/usr/bin/env python
'''
K-means clusterization sample.
Usage:
kmeans.py
Keyboard shortcuts:
ESC - exit
space - generate new distribution
'''
# Python 2/3 compatibility
from __future__ import print_function
import numpy as np
import cv2
from gaussian_mix import make_gaussians
if __name__ == '__main__':
cluster_n = 5
img_size = 512
print(__doc__)
# generating bright palette
colors = np.zeros((1, cluster_n, 3), np.uint8)
colors[0,:] = 255
colors[0,:,0] = np.arange(0, 180, 180.0/cluster_n)
colors = cv2.cvtColor(colors, cv2.COLOR_HSV2BGR)[0]
while True:
print('sampling distributions...')
points, _ = make_gaussians(cluster_n, img_size)
term_crit = (cv2.TERM_CRITERIA_EPS, 30, 0.1)
ret, labels, centers = cv2.kmeans(points, cluster_n, None, term_crit, 10, 0)
img = np.zeros((img_size, img_size, 3), np.uint8)
for (x, y), label in zip(np.int32(points), labels.ravel()):
c = list(map(int, colors[label]))
cv2.circle(img, (x, y), 1, c, -1)
cv2.imshow('gaussian mixture', img)
ch = 0xFF & cv2.waitKey(0)
if ch == 27:
break
cv2.destroyAllWindows()