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#!/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>]
'''
# Python 2/3 compatibility
from __future__ import print_function
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 np.int32(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()
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