
## Begin to train

1. run the following scripts to train ISTA-Net models.

    ```bash
    # CS ratio 1, 4, 10, 25, 30, 40, 50
    python Train_CS_ISTA_Net.py --cs_ratio 50 --layer_num 9
    ```
    
2. run the following scripts to tune SAISTA-Net models.
    ```bash
     # CS ratio 1, 4, 10, 25, 30, 40, 50
    python Tune_CS_ISTA_NET.py --cs_ratio 50 --layer_num 9
    ```

## Begin to test

1. run the following scripts to train ISTA-Net models.
    ```bash
    # CS ratio 1, 4, 10, 25, 30, 40, 50
    python TEST_CS_ISTA_Net.py --epoch_num 200 --cs_ratio 50 --layer_num 9

    ```
    
2. run the following scripts to tune SAISTA-Net models.
    ```bash
    # CS ratio 1, 4, 10, 25, 30, 40, 50
    python TEST_CS_ISTA_Net.py --epoch_num 40 --cs_ratio 50 --layer_num 9  --group_num 13 --sam --tune
    ```

training data should be download at https://github.com/jianzhangcs/ISTA-Net-pytorch in section `Prepare training data`
    
## Citation
If you find the code helpful in your resarch or work, please cite the following papers.
```
@inproceedings{zhang2018ista,
  title={ISTA-Net: Interpretable optimization-inspired deep network for image compressive sensing},
  author={Zhang, Jian and Ghanem, Bernard},
  booktitle={CVPR},
  pages={1828--1837},
  year={2018}
}
```
## Acknowledgements
