What about this one:
dataset = datasets.ImageFolder('train', transform=transforms.Compose([transforms.Resize(256),
transforms.CenterCrop(224),
transforms.ToTensor()]))
loader = data.DataLoader(dataset,
batch_size=10,
num_workers=0,
shuffle=False)
mean = 0.0
for images, _ in loader:
batch_samples = images.size(0)
images = images.view(batch_samples, images.size(1), -1)
mean += images.mean(2).sum(0)
mean = mean / len(loader.dataset)
var = 0.0
for images, _ in loader:
batch_samples = images.size(0)
images = images.view(batch_samples, images.size(1), -1)
var += ((images - mean.unsqueeze(1))**2).sum([0,2])
std = torch.sqrt(var / (len(loader.dataset)*224*224))
This also gives reasonable values for std, but different from ptrblck std.