example5_3_training_set.py

import matplotlib.pyplot as plt
import numpy as np
import cv2
from skimage.feature import greycomatrix, greycoprops


im = cv2.imread("Texture//Beef//1.jpg")
im_gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
cv2.imshow("image",im)

L = 10
im_gray = (im_gray/16).astype(np.uint8)
glcm = greycomatrix(im_gray, range(1,L+1), [0,np.pi/4,np.pi/2], 16, symmetric=True, normed=True)
glcm_props = np.zeros(4*L*3)
glcm_props[0:(L*3)] = greycoprops(glcm, 'ASM').reshape(1,-1)[0]
glcm_props[(L*3):(L*3*2)] = greycoprops(glcm, 'contrast').reshape(1,-1)[0]
glcm_props[(L*3*2):(L*3*3)] = greycoprops(glcm, 'homogeneity').reshape(1,-1)[0]
glcm_props[(L*3*3):(L*3*4)] = greycoprops(glcm, 'correlation').reshape(1,-1)[0]

print(glcm.shape)
print(glcm_props)

cv2.waitKey(0)
cv2.destroyAllWindows()