This is the PyTorch implement of ResNeXt (train on ImageNet dataset)

Paper: Aggregated Residual Transformations for Deep Neural Networks

Usage

Prepare data

This code takes ImageNet dataset as example. You can download ImageNet dataset and put them as follows. I only provide

ILSVRC2012_dev_kit_t12

ILSVRC2012_img_train

ILSVRC2012_img_val

├── train.py # train script
├── resnext.py # network of resnext
├── read_ImageNetData.py # ImageNet dataset read script
├── ImageData # train and validation data
    ├── ILSVRC2012_img_train
        ├── n01440764
        ├──    ...
        ├── n15075141
    ├── ILSVRC2012_img_val
    ├── ILSVRC2012_dev_kit_t12
        ├── data
            ├── ILSVRC2012_validation_ground_truth.txt
            ├── meta.mat # the map between train file name and label

Train

• If you want to train from scratch, you can run as follows:

python train.py --batch-size 256 --gpus 0,1,2,3

• If you want to train from one checkpoint, you can run as follows(for example train from

  epoch_4.pth.tar

  , the

  --start-epoch

  parameter is corresponding to the epoch of the checkpoint):

python train.py --batch-size 256 --gpus 0,1,2,3 --resume output/epoch_4.pth.tar --start-epoch 4