mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
69 lines
2.0 KiB
69 lines
2.0 KiB
#!/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 |
|
from numpy import random |
|
import cv2 |
|
|
|
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 = np.int32(mean) |
|
w, u, vt = cv2.SVDecomp(cov) |
|
ang = np.arctan2(u[1, 0], u[0, 0])*(180/np.pi) |
|
s1, s2 = np.sqrt(w)*3.0 |
|
cv2.ellipse(img, (x, y), (s1, s2), ang, 0, 360, color, 1, cv2.LINE_AA) |
|
|
|
|
|
if __name__ == '__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 = cv2.ml.EM_create() |
|
em.setClustersNumber(cluster_n) |
|
em.setCovarianceMatrixType(cv2.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): |
|
cv2.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)) |
|
|
|
cv2.imshow('gaussian mixture', img) |
|
ch = 0xFF & cv2.waitKey(0) |
|
if ch == 27: |
|
break |
|
cv2.destroyAllWindows()
|
|
|