#!/usr/bin/env python ''' Texture flow direction estimation. Sample shows how cv2.cornerEigenValsAndVecs function can be used to estimate image texture flow direction. Usage: texture_flow.py [<image>] ''' import numpy as np import cv2 if __name__ == '__main__': import sys try: fn = sys.argv[1] except: fn = '../data/starry_night.jpg' img = cv2.imread(fn) if img is None: print 'Failed to load image file:', fn sys.exit(1) gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) h, w = img.shape[:2] eigen = cv2.cornerEigenValsAndVecs(gray, 15, 3) eigen = eigen.reshape(h, w, 3, 2) # [[e1, e2], v1, v2] flow = eigen[:,:,2] vis = img.copy() vis[:] = (192 + np.uint32(vis)) / 2 d = 12 points = np.dstack( np.mgrid[d/2:w:d, d/2:h:d] ).reshape(-1, 2) for x, y in points: vx, vy = np.int32(flow[y, x]*d) cv2.line(vis, (x-vx, y-vy), (x+vx, y+vy), (0, 0, 0), 1, cv2.LINE_AA) cv2.imshow('input', img) cv2.imshow('flow', vis) cv2.waitKey()