https://arxiv.org/abs/2104.06757

https://openaccess.thecvf.com/content/ICCV2021W/CVAMD/html/Kamran_VTGAN_Semi-Supervised_Retinal_Image_Synthesis_and_Disease_Prediction_Using_Vision_ICCVW_2021_paper.html

https://ieeexplore.ieee.org/document/9607858

@INPROCEEDINGS{9607858,
  author={Kamran, Sharif Amit and Hossain, Khondker Fariha and Tavakkoli, Alireza and Zuckerbrod, Stewart Lee and Baker, Salah A.},
  booktitle={2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)}, 
  title={VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers}, 
  year={2021},
  volume={},
  number={},
  pages={3228-3238},
  doi={10.1109/ICCVW54120.2021.00362}
}

sudo add-apt-repository ppa:deadsnakes/ppa
sudo apt install python3.7

sudo pip3 install tensorflow-gpu
sudo pip3 install keras

sudo pip3 install -r requirements.txt

https://sites.google.com/site/hosseinrabbanikhorasgani/datasets-1/fundus-fluorescein-angiogram-photographs--colour-fundus-images-of-diabetic-patients

@article{hajeb2012diabetic,
  title={Diabetic retinopathy grading by digital curvelet transform},
  author={Hajeb Mohammad Alipour, Shirin and Rabbani, Hossein and Akhlaghi, Mohammad Reza},
  journal={Computational and mathematical methods in medicine},
  volume={2012},
  year={2012},
  publisher={Hindawi}
}

├── Dataset
|   ├──ABNORMAL
|   ├──NORMAL

python3 random_crop.py --output_dir=data --input_dim=512 --datadir=Dataset

    '--input_dim', type=int, default=512
    '--n_crops', type=int, default=50
    '--datadir', type=str, required=True, help='path/to/data_directory',default='Dataset'
    '--output_dir', type=str, default='data'   

python3 convert_npz.py --outfile_name=vtgan --input_dim=512 --datadir=data --n_crops=50

    '--input_dim', type=int, default=512
    '--n_crops', type=int, default=50
    '--datadir', type=str, required=True, help='path/to/data_directory',default='data'
    '--outfile_name', type=str, default='vtgan'
    '--n_images', type=int, default=17

python3 train.py --npz_file=vtgan --batch=2 --epochs=100 --savedir=VTGAN

    '--epochs', type=int, default=100
    '--batch_size', type=int, default=2
    '--npz_file', type=str, default='vtgan', help='path/to/npz/file'
    '--input_dim', type=int, default=512
    '--n_patch', type=int, default=64
    '--savedir', type=str, required=False, help='path/to/save_directory',default='VTGAN'
    '--resume_training', type=str, required=False,  default='no', choices=['yes','no']