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- #!/usr/bin/env python
- # Python 2/3 compatibility
- from __future__ import print_function
- import sys
- PY3 = sys.version_info[0] == 3
- if PY3:
- xrange = range
- import numpy as np
- import cv2 as cv
- from numpy import random
- def make_gaussians(cluster_n, img_size):
- points = []
- ref_distrs = []
- for _i in xrange(cluster_n):
- mean = (0.1 + 0.8*random.rand(2)) * img_size
- a = (random.rand(2, 2)-0.5)*img_size*0.1
- cov = np.dot(a.T, a) + img_size*0.05*np.eye(2)
- n = 100 + random.randint(900)
- pts = random.multivariate_normal(mean, cov, n)
- points.append( pts )
- ref_distrs.append( (mean, cov) )
- points = np.float32( np.vstack(points) )
- return points, ref_distrs
- def draw_gaussain(img, mean, cov, color):
- x, y = mean
- w, u, _vt = cv.SVDecomp(cov)
- ang = np.arctan2(u[1, 0], u[0, 0])*(180/np.pi)
- s1, s2 = np.sqrt(w)*3.0
- cv.ellipse(img, (int(x), int(y)), (int(s1), int(s2)), ang, 0, 360, color, 1, cv.LINE_AA)
- def main():
- cluster_n = 5
- img_size = 512
- print('press any key to update distributions, ESC - exit\n')
- while True:
- print('sampling distributions...')
- points, ref_distrs = make_gaussians(cluster_n, img_size)
- print('EM (opencv) ...')
- em = cv.ml.EM_create()
- em.setClustersNumber(cluster_n)
- em.setCovarianceMatrixType(cv.ml.EM_COV_MAT_GENERIC)
- em.trainEM(points)
- means = em.getMeans()
- covs = em.getCovs() # Known bug: https://github.com/opencv/opencv/pull/4232
- found_distrs = zip(means, covs)
- print('ready!\n')
- img = np.zeros((img_size, img_size, 3), np.uint8)
- for x, y in np.int32(points):
- cv.circle(img, (x, y), 1, (255, 255, 255), -1)
- for m, cov in ref_distrs:
- draw_gaussain(img, m, cov, (0, 255, 0))
- for m, cov in found_distrs:
- draw_gaussain(img, m, cov, (0, 0, 255))
- cv.imshow('gaussian mixture', img)
- ch = cv.waitKey(0)
- if ch == 27:
- break
- print('Done')
- if __name__ == '__main__':
- print(__doc__)
- main()
- cv.destroyAllWindows()
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