[Computer Vision] Data set(image) Normalize value 계산(mean, std)

import torch
from tqdm.notebook import tqdm
import glob
from PIL import Image
from torchvision.transforms import ToTensor

target_path = "./images/*"
img_lst = glob.glob(target_path)

totensor = ToTensor()
img_val_lst = []
for img in tqdm(img_lst):
    img_RGB = Image.open(img).convert("RGB")
    img_val = totensor(img_RGB)
    img_val_lst.append(img_val)
mean = torch.zeros(3)
std = torch.zeros(3)
print('==> Computing mean and std..')
for inputs in tqdm(img_val_lst):
    for i in range(3):#RGB
        mean[i] += inputs[i,:,:].mean()
        std[i] += inputs[i,:,:].std()
        
mean.div_(len(img_val_lst))
std.div_(len(img_val_lst))
print(mean, std)