## Prerequisites
- Linux or macOS
- Python 3
- CPU or NVIDIA GPU + CUDA CuDNN

## Setting enviroments(Installation)

-创建环境： conda create --name FA_generation python=3.6
-激活环境： conda activate FA_generation
-依赖库安装： pip install -r requirements.txt


### 1. Train/Test (Only CycleGAN)

- Train the model :
```
python train.py --dataroot ./datasets/FFA_detect --name FA_detect_cycle --model cycle_gan

```

- Test the model:
```
python test.py --dataroot ./datasets/FFA_detect --name FA_detect_cycle --model cycle_gan

```

### 2. Train/Test (CycleGAN + CBAM)

- Train the model :
```
python train.py --dataroot ./datasets/FFA_detect --name FA_detect_CBAM --model cycle_gan --netG attention_resnet_9blocks

```

- Test the model:
```
python test.py --dataroot ./datasets/FFA_detect --name FA_detect_CBAM --model cycle_gan --netG attention_resnet_9blocks

```

### 3. Train/Test (CycleGAN + CBAM + cam_mask loss) (Final Model!!!)

- Train the model :
```
python train.py --dataroot ./datasets/FFA_detect --name FA_detect_CAM --model cycle_gan_cam --netG attention_resnet_9blocks --lambda_mask 10.0

```

- Test the model:
```
python test.py --dataroot ./datasets/FFA_detect --name FA_detect_CAM --model cycle_gan_cam --netG attention_resnet_9blocks --lambda_mask 10.0

```