# What's the range of the input value desired to use pretrained resnet152 and vgg19?

**URL:** <https://discuss.pytorch.org/t/whats-the-range-of-the-input-value-desired-to-use-pretrained-resnet152-and-vgg19/1683>\
**Category:** vision\
**Created:** [April 6, 2017, 4:16am UTC](https://discuss.pytorch.org/t/whats-the-range-of-the-input-value-desired-to-use-pretrained-resnet152-and-vgg19/1683 "2017-04-06T04:16:36Z")\
**Posts on this page:** 1\
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**Author:** ![smth](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/smth/32/13_2.png) [@smth](https://discuss.pytorch.org/u/smth)\
**Post date:** [April 6, 2017, 4:33am UTC](https://discuss.pytorch.org/t/whats-the-range-of-the-input-value-desired-to-use-pretrained-resnet152-and-vgg19/1683/2 "2017-04-06T04:33:58Z")

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input image is first loaded to range [0, 1] and then this normalization is applied to RGB image as described here:

> **[GitHub - pytorch/vision: Datasets, Transforms and Models specific to Computer...](https://github.com/pytorch/vision#models)**
>
> Datasets, Transforms and Models specific to Computer Vision - GitHub - pytorch/vision: Datasets, Transforms and Models specific to Computer Vision

> All pre-trained models expect input images normalized in the same way, i.e. mini-batches of 3-channel RGB images of shape (3 x H x W), where H and W are expected to be atleast 224.
> 
> The images have to be loaded in to a range of [0, 1] and then normalized using mean=[0.485, 0.456, 0.406] and std=[0.229, 0.224, 0.225]
> 
> An example of such normalization can be found in the imagenet example here [https://github.com/pytorch/examples/blob/42e5b996718797e45c46a25c55b031e6768f8440/imagenet/main.py#L89-L101](https://github.com/pytorch/examples/blob/42e5b996718797e45c46a25c55b031e6768f8440/imagenet/main.py#L89-L101)

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