try to used TransFG to do the Fine-grained Recognition

TransFG: A Transformer Architecture for Fine-grained Recognition

Official PyTorch code for the paper: TransFG: A Transformer Architecture for Fine-grained Recognition
Implementation based on DeiT pretrained on ImageNet-1K with distillation fine-tuning will be released soon.

Framework

Dependencies:

• Python 3.7.3
• PyTorch 1.5.1
• torchvision 0.6.1
• ml_collections

Reproduce Submission

To reproduce the submission, do the following step:

1. Download this project and Install required packages

Install dependencies with the following command:

pip3 install -r requirements.txt

2. Download pretrained TransFG model

• Pretrained TransFG model

Please download the model and put it into the output folder

3. used the following command to inference

python inference.py --test_img_path {testing image path} --pretrained_model_path {TransFG pretrained model path, default is in "output"}

Report

• Report

Citation

If you find our work helpful in your research, please cite it as:

@article{he2021transfg,
  title={TransFG: A Transformer Architecture for Fine-grained Recognition},
  author={He, Ju and Chen, Jieneng and Liu, Shuai and Kortylewski, Adam and Yang, Cheng and Bai, Yutong and Wang, Changhu and Yuille, Alan},
  journal={arXiv preprint arXiv:2103.07976},
  year={2021}
}

Acknowledgement

Many thanks to ViT-pytorch for the PyTorch reimplementation of An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale