ImageNet example Instruction

Here is the instruction of preparing the datasets and use a ResNet model in torchvision for training.

Preparing the datasets

Download

1. Download the dataset on ILSVRC.
   http://www.image-net.org/challenges/LSVRC/2012/nnoupb/ILSVRC2012_img_test.tar http://www.image-net.org/challenges/LSVRC/2012/nnoupb/ILSVRC2012_img_val.tar http://www.image-net.org/challenges/LSVRC/2012/nnoupb/ILSVRC2012_img_train.tar http://www.image-net.org/challenges/LSVRC/2012/nnoupb/ILSVRC2012_devkit_t12.tar http://www.image-net.org/challenges/LSVRC/2012/nnoupb/ILSVRC2012_bbox_train_v2.tar

2. Download the dataset on http://bt.byr.cn/torrents.php

Organize

To quickly use the ImageNet example given by the author, we should organize the datasets as train and val directories respectively.

1. Organize the train directory:

mkdir train && mv ILSVRC2012_img_train.tar train/ && cd train
tar -xvf ILSVRC2012_img_train.tar && rm -f ILSVRC2012_img_train.tar
find . -name "*.tar" | while read NAME ; do mkdir -p "${NAME%.tar}"; tar -xvf "${NAME}" -C "${NAME%.tar}"; rm -f "${NAME}"; done
cd ..

1. Extract the validation data and move images to subfolders:

mkdir val && mv ILSVRC2012_img_val.tar val/ && cd val && tar -xvf ILSVRC2012_img_val.tar
wget -qO- https://raw.githubusercontent.com/soumith/imagenetloader.torch/master/valprep.sh | bash

reference: download-the-imagenet-dataset

Use ResNet to train ImageNet

Here is a implemented code in pytorch to use ResNet for training ImageNet. See here