f4334277
 Hu Chunming
提交3rdparty
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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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