#!/usr/bin/env python ''' Texture flow direction estimation. Sample shows how cv.cornerEigenValsAndVecs function can be used to estimate image texture flow direction. Usage: texture_flow.py [<image>] ''' # Python 2/3 compatibility from __future__ import print_function import numpy as np import cv2 as cv def main(): import sys try: fn = sys.argv[1] except: fn = 'starry_night.jpg' img = cv.imread(cv.samples.findFile(fn)) if img is None: print('Failed to load image file:', fn) sys.exit(1) gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY) h, w = img.shape[:2] eigen = cv.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 np.int32(points): vx, vy = np.int32(flow[y, x]*d) cv.line(vis, (x-vx, y-vy), (x+vx, y+vy), (0, 0, 0), 1, cv.LINE_AA) cv.imshow('input', img) cv.imshow('flow', vis) cv.waitKey() print('Done') if __name__ == '__main__': print(__doc__) main() cv.destroyAllWindows()