I tried using the image filter of OpenCV

#-*- coding:utf-8 -*-
import cv2
import numpy as np

def main():
    #Read the input image
    img = cv2.imread("input.jpg ")

    #Grayscale conversion
    gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
    cv2.imwrite("gray.jpg ", gray )
    
    #median filter
    median = cv2.medianBlur(gray,9)
    cv2.imwrite("median.jpg ", median )
    
    #sobel filter
    gray_x = cv2.Sobel(gray, cv2.CV_32F, 1, 0, ksize=3)
    gray_y = cv2.Sobel(gray, cv2.CV_32F, 0, 1, ksize=3)
    sobel = np.sqrt(gray_x ** 2 + gray_y ** 2)
    cv2.imwrite("sobel.jpg ", sobel)

    #Gaussian filtering
    gauss = cv2.GaussianBlur(gray, (11,11), 5.0)
    cv2.imwrite("gauss.jpg ", gauss )
    

if __name__ == "__main__":
    main()

$ python image_filter.py

Recommended Posts