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python: 'cv2.' -> 'cv.' via 'import cv2 as cv'
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@@ -10,7 +10,7 @@ if PY3:
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import numpy as np
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from numpy import random
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import cv2
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import cv2 as cv
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def make_gaussians(cluster_n, img_size):
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points = []
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@@ -28,10 +28,10 @@ def make_gaussians(cluster_n, img_size):
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def draw_gaussain(img, mean, cov, color):
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x, y = np.int32(mean)
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w, u, _vt = cv2.SVDecomp(cov)
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w, u, _vt = cv.SVDecomp(cov)
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ang = np.arctan2(u[1, 0], u[0, 0])*(180/np.pi)
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s1, s2 = np.sqrt(w)*3.0
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cv2.ellipse(img, (x, y), (s1, s2), ang, 0, 360, color, 1, cv2.LINE_AA)
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cv.ellipse(img, (x, y), (s1, s2), ang, 0, 360, color, 1, cv.LINE_AA)
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if __name__ == '__main__':
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@@ -45,9 +45,9 @@ if __name__ == '__main__':
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points, ref_distrs = make_gaussians(cluster_n, img_size)
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print('EM (opencv) ...')
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em = cv2.ml.EM_create()
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em = cv.ml.EM_create()
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em.setClustersNumber(cluster_n)
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em.setCovarianceMatrixType(cv2.ml.EM_COV_MAT_GENERIC)
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em.setCovarianceMatrixType(cv.ml.EM_COV_MAT_GENERIC)
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em.trainEM(points)
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means = em.getMeans()
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covs = em.getCovs() # Known bug: https://github.com/opencv/opencv/pull/4232
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@@ -56,14 +56,14 @@ if __name__ == '__main__':
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img = np.zeros((img_size, img_size, 3), np.uint8)
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for x, y in np.int32(points):
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cv2.circle(img, (x, y), 1, (255, 255, 255), -1)
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cv.circle(img, (x, y), 1, (255, 255, 255), -1)
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for m, cov in ref_distrs:
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draw_gaussain(img, m, cov, (0, 255, 0))
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for m, cov in found_distrs:
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draw_gaussain(img, m, cov, (0, 0, 255))
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cv2.imshow('gaussian mixture', img)
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ch = cv2.waitKey(0)
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cv.imshow('gaussian mixture', img)
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ch = cv.waitKey(0)
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if ch == 27:
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break
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cv2.destroyAllWindows()
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cv.destroyAllWindows()
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