- class torchvision.transforms.v2.Normalize(mean: Sequence[float], std: Sequence[float], inplace: bool = False)¶
[BETA] Normalize a tensor image or video with mean and standard deviation.
The Normalize transform is in Beta stage, and while we do not expect disruptive breaking changes, some APIs may slightly change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753.
This transform does not support PIL Image. Given mean:
nchannels, this transform will normalize each channel of the input
output[channel] = (input[channel] - mean[channel]) / std[channel]
This transform acts out of place, i.e., it does not mutate the input tensor.
mean (sequence) – Sequence of means for each channel.
std (sequence) – Sequence of standard deviations for each channel.
inplace (bool,optional) – Bool to make this operation in-place.