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'''
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Texture flow direction estimation.
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Sample shows how cv2.cornerEigenValsAndVecs function can be used
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to estimate image texture flow direction.
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Usage:
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texture_flow.py [<image>]
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'''
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import numpy as np
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import cv2
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if __name__ == '__main__':
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import sys
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try: fn = sys.argv[1]
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except: fn = 'data/starry_night.jpg'
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img = cv2.imread(fn)
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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h, w = img.shape[:2]
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eigen = cv2.cornerEigenValsAndVecs(gray, 15, 3)
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eigen = eigen.reshape(h, w, 3, 2) # [[e1, e2], v1, v2]
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flow = eigen[:,:,2]
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vis = img.copy()
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vis[:] = (192 + np.uint32(vis)) / 2
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d = 12
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points = np.dstack( np.mgrid[d/2:w:d, d/2:h:d] ).reshape(-1, 2)
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for x, y in points:
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vx, vy = np.int32(flow[y, x]*d)
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cv2.line(vis, (x-vx, y-vy), (x+vx, y+vy), (0, 0, 0), 1, cv2.CV_AA)
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cv2.imshow('input', img)
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cv2.imshow('flow', vis)
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cv2.waitKey()
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