mirror of
https://github.com/opencv/opencv.git
synced 2024-12-02 16:00:17 +08:00
51 lines
1.4 KiB
Python
51 lines
1.4 KiB
Python
|
#!/usr/bin/env python
|
||
|
|
|
||
|
|
'''
|
||
|
|
Texture flow direction estimation.
|
||
|
|
|
||
|
|
Sample shows how cv2.cornerEigenValsAndVecs function can be used
|
||
|
|
to estimate image texture flow direction.
|
||
|
|
'''
|
||
|
|
|
||
|
|
# Python 2/3 compatibility
|
||
|
|
from __future__ import print_function
|
||
|
|
|
||
|
|
import numpy as np
|
||
|
|
import cv2
|
||
|
|
import sys
|
||
|
|
|
||
|
|
from tests_common import NewOpenCVTests
|
||
|
|
|
||
|
|
|
||
|
|
class texture_flow_test(NewOpenCVTests):
|
||
|
|
|
||
|
|
def test_texture_flow(self):
|
||
|
|
|
||
|
|
img = self.get_sample('samples/data/pic6.png')
|
||
|
|
|
||
|
|
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 = 80
|
||
|
|
points = np.dstack( np.mgrid[d/2:w:d, d/2:h:d] ).reshape(-1, 2)
|
||
|
|
|
||
|
|
textureVectors = []
|
||
|
|
|
||
|
|
for x, y in np.int32(points):
|
||
|
|
textureVectors.append(np.int32(flow[y, x]*d))
|
||
|
|
|
||
|
|
eps = 0.05
|
||
|
|
|
||
|
|
testTextureVectors = [[0, 0], [0, 0], [0, 0], [0, 0], [0, 0],
|
||
|
|
[-38, 70], [-79, 3], [0, 0], [0, 0], [-39, 69], [-79, -1],
|
||
|
|
[0, 0], [0, 0], [0, -79], [17, -78], [-48, -63], [65, -46],
|
||
|
|
[-69, -39], [-48, -63], [-45, 66]]
|
||
|
|
|
||
|
|
for i in range(len(textureVectors)):
|
||
|
|
self.assertLessEqual(cv2.norm(textureVectors[i] - testTextureVectors[i], cv2.NORM_L2), eps)
|