https://github.com/chenmnz/smmix
[ICCV 23]This is a Pytorch implementation of our paper "SMMix: Self-Motivated Image Mixing for Vision Transformers"
https://github.com/chenmnz/smmix
Last synced: 5 months ago
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[ICCV 23]This is a Pytorch implementation of our paper "SMMix: Self-Motivated Image Mixing for Vision Transformers"
- Host: GitHub
- URL: https://github.com/chenmnz/smmix
- Owner: ChenMnZ
- Created: 2022-12-23T10:30:22.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-07-14T09:02:15.000Z (almost 2 years ago)
- Last Synced: 2024-08-03T23:13:41.342Z (9 months ago)
- Language: Python
- Homepage:
- Size: 984 KB
- Stars: 16
- Watchers: 2
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Dei: deit.py
Awesome Lists containing this project
- Awesome-Mixup - [Code
README
# SMMix: Self-Motivated Image Mixing for Vision Transformers (ICCV 2023)
This a Pytorch implementation of our paper [SMMix: Self-Motivated Image Mixing for Vision Transformers](https://arxiv.org/abs/2212.12977)
## Requirements
- python 3.8.0
- pytorch 1.7.1
- torchvision 0.8.2
## Data Preparation
- The ImageNet dataset should be prepared as follows:
```
ImageNet
├── train
│ ├── folder 1 (class 1)
│ ├── folder 2 (class 2)
│ ├── ...
├── val
│ ├── folder 1 (class 1)
│ ├── folder 2 (class 2)
│ ├── ...
```
## Pre-trained Models
|Model|Top-1 Accuracy|Dowmload|
|-----|:-------:|---------|
|DeiT-T| 73.6 |[model](https://drive.google.com/file/d/1cclVfL_dCs7uQIdEvUoTsdMnc2gN7tZD/view?usp=sharing) & [log](https://drive.google.com/file/d/13VcsQeX1X6ONEI4pZp9biPtmOeXl9EsV/view?usp=sharing)|
|DeiT-S| 81.1 |[model](https://drive.google.com/file/d/1FYRglSq7EFVDVAE1sOZ81bBm_fZj_9bz/view?usp=share_link) & [log](https://drive.google.com/file/d/1rd3_HzHyCAhocLbO78tzAaXsyJUzQJGy/view?usp=share_link)|
|PVT-T | 76.4 |[model](https://drive.google.com/file/d/11ULLrgyPbeBr3TZXEh7xIb3HXjozCKFL/view?usp=sharing) & [log](https://drive.google.com/file/d/1e7m8K57fWcPawAEtUtkTDaTlZXJbU1gz/view?usp=sharing)|
|PVT-S | 81.0 |[model](https://drive.google.com/file/d/18QH-IEOI6KYpbST0xMyjJBTJeKFxtw2U/view?usp=sharing) & [log](https://drive.google.com/file/d/1yKgfi1dpb0puFhZy-pZJF-1vBWHM_scs/view?usp=sharing)|
|PVT-M | 82.2 |[model](https://drive.google.com/file/d/1AEN7iiIYABmaHCkK9ds9A-owEuBIX2mU/view?usp=sharing) & [log](https://drive.google.com/file/d/1hgycht1Szor9aUePbCyOyoDyId9yBkNf/view?usp=sharing)|
|PVT-L | 82.7 |[model](https://drive.google.com/file/d/1IG-XONNBfv-Rg5ETZfTfVa2i5qk11lNr/view?usp=sharing) & [log](https://drive.google.com/file/d/1aojFiCSv_eZtYJBaCuRwCTZFQqOT-sYu/view?usp=sharing)|
## Evaluation
```
./script/eval.sh --data-path DATASET_PATH --model MODEL_NAME --resume CHECKPOINT_PATH
```
examples:
```
./script/eval.sh --data-path /media/DATASET/ImageNet --model pvt_small --resume ./checkpoints/pvt_small_smmix.pth
```
```
./script/eval.sh --data-path /media/DATASET/ImageNet --model vit_deit_small_patch16_224 --resume ./checkpoints/deit_small_smmix.pth
```
## Training
```
./script/train.sh --data-path DATASET_PATH --model MODEL_NAME --output_dir LOG_PATH --batch_size 256
```
examples:
```
./script/train.sh --data-path /media/DATASET/ImageNet --model pvt_small --output_dir ./log/pvt_small_smmix --batch_size 256
```
```
./script/train.sh --data-path /media/DATASET/ImageNet --model vit_deit_small_patch16_224 --output_dir ./log/deit_small_smmix --batch_size 256
```