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
due to the restriction of memory, in other words, you need download ILSVRC2012_img_train
and ILSVRC2012_img_val
.
βββ train.py # train script
βββ resnext.py # network of resnext
βββ read_ImageNetData.py # ImageNet dataset read script
βββ ImageData # train and validation data
βββ ILSVRC2012_img_train
βββ n01440764
βββ ...
βββ n15075141
βββ ILSVRC2012_img_val
βββ ILSVRC2012_dev_kit_t12
βββ data
βββ ILSVRC2012_validation_ground_truth.txt
βββ 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