（6）Python批量计算PSNR、SSIM、MSE

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目录

import os
import numpy as np
from glob import glob
import cv2
from skimage.measure import compare_mse,compare_ssim,compare_psnr

def read_img(path):
    return cv2.imread(path,cv2.IMREAD_GRAYSCALE)

def mse(tf_img1, tf_img2):
    return compare_mse(tf_img1,tf_img2)

def psnr(tf_img1, tf_img2):
    return compare_psnr(tf_img1,tf_img2)

def ssim(tf_img1, tf_img2):
    return compare_ssim(tf_img1,tf_img2)

def main():
    WSI_MASK_PATH1 = 'E:/test/A/'
    WSI_MASK_PATH2 = 'E:/test/B/'
    path_real = glob(os.path.join(WSI_MASK_PATH1, '*.jpg'))
    path_fake = glob(os.path.join(WSI_MASK_PATH2, '*.jpg'))
    list_psnr = []
    list_ssim = []
    list_mse = []

    for i in range(len(path_real)):
        t1 = read_img(path_real[i])
        t2 = read_img(path_fake[i])
        result1 = np.zeros(t1.shape,dtype=np.float32)
        result2 = np.zeros(t2.shape,dtype=np.float32)
        cv2.normalize(t1,result1,alpha=0,beta=1,norm_type=cv2.NORM_MINMAX,dtype=cv2.CV_32F)
        cv2.normalize(t2,result2,alpha=0,beta=1,norm_type=cv2.NORM_MINMAX,dtype=cv2.CV_32F)
        mse_num = mse(result1, result2)
        psnr_num = psnr(result1, result2)
        ssim_num = ssim(result1, result2)
        list_psnr.append(psnr_num)
        list_ssim.append(ssim_num)
        list_mse.append(mse_num)
       
        #输出每张图像的指标：
        print("{}/".format(i+1)+"{}:".format(len(path_real)))
        str = "\\"
        print("image:"+path_real[i][(path_real[i].index(str)+1):])
        print("PSNR:", psnr_num)
        print("SSIM:", ssim_num)
        print("MSE:",mse_num)

	#输出平均指标：
    print("平均PSNR:", np.mean(list_psnr))  # ,list_psnr)
    print("平均SSIM:", np.mean(list_ssim))  # ,list_ssim)
    print("平均MSE:", np.mean(list_mse))  # ,list_mse)

if __name__ == '__main__':
    main()