gabor.py

import numpy as np
import cv2

# cv2.getGaborKernel(ksize, sigma, theta, lambda, gamma, psi, ktype)
# ksize - size of gabor filter (n, n)
# sigma - standard deviation of the gaussian function
# theta - orientation of the normal to the parallel stripes
# lambda - wavelength of the sunusoidal factor
# gamma - spatial aspect ratio
# psi - phase offset
# ktype - type and range of values that each pixel in the gabor kernel can hold

g_kernel = cv2.getGaborKernel((21, 21), 8.0, np.pi/4, 10.0, 0.5, 0, ktype=cv2.CV_32F)

img = cv2.imread('108004.jpg')
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
filtered_img = cv2.filter2D(img, cv2.CV_8UC3, g_kernel)

cv2.imshow('image', img)
cv2.imshow('filtered image', filtered_img)
cv2.waitKey(0)
cv2.destroyAllWindows()