I am new to Pytorch, I was just trying out some datasets. While using the
torchvision.transforms.Normalize I noted that most of the example out there were using 0.5 as mean and std to normalize the images in range (-1,1) but this will only work if our image data is already in (0,1) form and when i tried out normalizing my data (using mean and std as 0.5) by myself, my data was converted to range (-1,1), this means that when I loaded the data it was converted into (0,1) some where in the code.
Am I right that Pytorch automatically Normalizes Image to (0,1) when we load it and if yes which line of code is doing this?
import torch from torchvision import transforms, datasets Transformations = transforms.Compose([transforms.RandomSizedCrop(224), transforms.ToTensor(), transforms.Normalize(mean=[0.5, 0.5, 0.5],std=[0.5, 0.5, 0.5]) ]) image_data = datasets.ImageFolder('C:/users/sharm/OneDrive/Desktop/Mnist/dogImages/train', transform = Transformations) data_loader = torch.utils.data.DataLoader(image_data, batch_size = 50, shuffle = True) iteration = iter(data_loader) images, labels = iteration.next() print (images)