I have many images and want to compute the GLCM properties for every image. Below my code that runs many hours to complete the task:
import numpy as np from skimage.feature import greycomatrix, greycoprops ANGLES = [0., np.pi/4., np.pi/2., 3.*np.pi/4.] DISTANCES = [1,2] properties = ["correlation", "contrast", "homogeneity", "energy"] n_img = 1000 I = np.random.randint(0,255,size=(n_img, 100, 100)) stats =  for k in range(n_img): glcm = greycomatrix(I[k], distances=DISTANCES, angles=ANGLES, levels=256, symmetric=True, normed=True) prop = [np.mean(greycoprops(glcm, properties[i])) for i in range(len(properties))] stats.append(prop) stats = np.array(stats)
This code is a real bottleneck. How can parallelize the task? Are there other ways to speed up the code?