vanillacappuccino/pytorch-imagenet

PyTorch based Imagenet Training Code

PyTorch-ImageNet

Preprocessing

Normalization

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 at least 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]. You can use the following transform to normalize:

normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],
                                 std=[0.229, 0.224, 0.225])

Pretrained models

Model	#Params	Weight File Size(Byte)	Top1Acc(%)
YOLOv3TinyBackbone(=tiny)	7,323,487	29,309,647	58.97