I am currently using the transforms.ToTensor(). As per the document it converts data in the range 0-255 to 0-1.
However, the transform work on data whose values ranges between negative to positive values? Any ideas how this transform work. And the transformed values no longer strictly positive.
In most tutorials regarding the finetuning using pretrained models, the data is normalized with [0.485, 0.456, 0.406], [0.229, 0.224, 0.225]). I would like to know how these values are computed? Are they computed by attained by using mean & std value of each channel from the entire training data?