text: # -*- coding: utf-8 -*-
  """
  Created on Wed Oct  6 23:59:38 2021
  
  @author: Sat Patel
  """
  
  # Adding Salt and Pepper Noise to image
  import cv2 as cv
  import numpy as np
  import random 
  
  
  # Adding salt and pepper noise
  
  def gaussian_noise(image):
        row = 512
        col = 512
        mean = 0
        var = 0.1
        sigma = var**0.5
        gauss = np.random.normal(mean,sigma,(row,col))
        gauss = gauss.reshape(row,col)
        gauss_noisy = image + gauss
        return gauss_noisy
  
  def salt_and_pepper_noise(image):
    
      # Getting the dimensions of the image
      row , col = img.shape
        
      # Randomly pick some pixels in the
      # image for coloring them white
      # Pick a random number between 300 and 10000
      number_of_pixels = random.randint(300, 10000)
      for i in range(number_of_pixels):
          
          # Pick a random y coordinate
          y_coord=random.randint(0, row - 1)
            
          # Pick a random x coordinate
          x_coord=random.randint(0, col - 1)
            
          # Color that pixel to white
          img[y_coord][x_coord] = 255
            
      # Randomly pick some pixels in
      # the image for coloring them black
      # Pick a random number between 300 and 10000
      number_of_pixels = random.randint(300 , 10000)
      for i in range(number_of_pixels):
          
          # Pick a random y coordinate
          y_coord=random.randint(0, row - 1)
            
          # Pick a random x coordinate
          x_coord=random.randint(0, col - 1)
            
          # Color that pixel to black
          img[y_coord][x_coord] = 0
            
      return img
    
      
  img = cv.imread('Lenna.jpg', 0)
  gn =  gaussian_noise(img) 
  snp = salt_and_pepper_noise(img)
  
  
  