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import os | ||
import numpy as np | ||
import math | ||
import cv2 | ||
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def psnr(img1, img2): | ||
mse = np.mean((img1/1. - img2/1.) ** 2 ) | ||
if mse < 1.0e-10: | ||
return 100*1.0 | ||
return 10 * math.log10(255.0*255.0/mse) | ||
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def mse(img1,img2): | ||
mse = np.mean((img1/1. - img2/1.) ** 2 ) | ||
return mse | ||
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def ssim(y_true , y_pred): | ||
u_true = np.mean(y_true) | ||
u_pred = np.mean(y_pred) | ||
var_true = np.var(y_true) | ||
var_pred = np.var(y_pred) | ||
std_true = np.sqrt(var_true) | ||
std_pred = np.sqrt(var_pred) | ||
c1 = np.square(0.01*7) | ||
c2 = np.square(0.03*7) | ||
ssim = (2 * u_true * u_pred + c1) * (2 * std_pred * std_true + c2) | ||
denom = (u_true ** 2 + u_pred ** 2 + c1) * (var_pred + var_true + c2) | ||
return ssim / denom | ||
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list_psnr = [] | ||
list_ssim = [] | ||
list_mse = [] | ||
for j in range(1,11): | ||
path1 = f"/public/home/chenzheng/CV_final_proj/CV2-Final/diffusion/sampling/{j}/" #指定输出结果文件夹 | ||
path2 = f"/public/home/chenzheng/CV_final_proj/CV2-Final/diffusion/sampling/{j}/"#指定原图文件夹 | ||
f_nums = len(os.listdir(path1)) | ||
#change if you sample more. | ||
for i in range(0,4): | ||
img_a = cv2.imread(path1+str(i)+'.png') | ||
img_b = cv2.imread(path2+'gt.png') | ||
psnr_num = psnr(img_a, img_b) | ||
ssim_num = ssim(img_a, img_b) | ||
mse_num = mse(img_a,img_b) | ||
list_ssim.append(ssim_num) | ||
list_psnr.append(psnr_num) | ||
list_mse.append(mse_num) | ||
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) |