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May 16, 2016 01:07
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Gabor kernel filter example in python
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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('test.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) | |
h, w = g_kernel.shape[:2] | |
g_kernel = cv2.resize(g_kernel, (3*w, 3*h), interpolation=cv2.INTER_CUBIC) | |
cv2.imshow('gabor kernel (resized)', g_kernel) | |
cv2.waitKey(0) | |
cv2.destroyAllWindows() |
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You example is very simple, but very understandable. I'm improve this example to interactive dashboard, mayby it will be helped for someone: https://github.com/Kostya-228/gabor_dashboard/tree/main