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calc_mean.py
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calc_mean.py
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# 用于计算图片色素均值,用于归一化
from torchvision.datasets import ImageFolder
import torch
from torchvision import transforms as T
from tqdm import tqdm
transform = T.Compose([
T.RandomResizedCrop(224),
T.ToTensor(),
])
def getStat(train_data):
train_loader = torch.utils.data.DataLoader(
train_data, batch_size=1, shuffle=False, num_workers=0, pin_memory=True)
mean = torch.zeros(3)
std = torch.zeros(3)
for X, _ in tqdm(train_loader):
for d in range(3):
mean[d] += X[:, d, :, :].mean() # N, C, H ,W
std[d] += X[:, d, :, :].std()
mean.div_(len(train_data))
std.div_(len(train_data))
return list(mean.numpy()), list(std.numpy())
if __name__ == '__main__':
train_dataset = ImageFolder(root=r'enhance_dataset', transform=transform)
print(getStat(train_dataset))