add_noise.py

import numpy as np




def salt_and_pepper(image,var):
    row,col,ch = image.shape
    s_vs_p = 0.5
    amount = var
    out = np.copy(image)
    # Salt mode
    num_salt = np.ceil(amount * image.size * s_vs_p)
    coords = [np.random.randint(0, i - 1, int(num_salt))
            for i in image.shape]
    out[coords] = 255

    # Pepper mode
    num_pepper = np.ceil(amount* image.size * (1. - s_vs_p))
    coords = [np.random.randint(0, i - 1, int(num_pepper))
            for i in image.shape]
    out[coords] = 0
    return out


def gaussian_noise(image,var):
    row,col,ch = image.shape
    #print("here",row,col)
    mean = 0
    sigma = var**0.5
    gauss = np.random.normal(mean,sigma,(row,col,ch))
    gauss = gauss.reshape(row,col,ch)
    noisy = image + gauss
    return noisy

def img_noise(img,var):
    out1 = gaussian_noise(img, var)
    out2 = salt_and_pepper(img, var)
    cv2.imwrite("img/gauss_"+str(var)+".jpg", out1)
    cv2.imwrite("img/snp_"+str(var)+".jpg", out2)



import cv2
img = cv2.imread('example.jpg')
arr = [0.001,0.01,0.1,0.2]
for i in arr:
    img_noise(img,i)