emla2805 / Vision Transformer
Tensorflow implementation of the Vision Transformer (An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale)
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Vision Transformer (ViT)
Tensorflow implementation of the Vision Transformer (ViT) presented in An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale, where the authors show that Transformers applied directly to image patches and pre-trained on large datasets work really well on image classification.
Install dependencies
Create a Python 3 virtual environment and activate it:
virtualenv -p python3 venv
source ./venv/bin/activate
Next, install the required dependencies:
pip install -r requirements.txt
Train model
Start the model training by running:
python train.py --logdir path/to/log/dir
To track metrics, start Tensorboard
tensorboard --logdir path/to/log/dir
and then go to localhost:6006.
Citation
@inproceedings{
anonymous2021an,
title={An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale},
author={Anonymous},
booktitle={Submitted to International Conference on Learning Representations},
year={2021},
url={https://openreview.net/forum?id=YicbFdNTTy},
note={under review}
}
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