Unofficial pytorch implementation: Attentive Generative Adversarial Network for Raindrop Removal from A Single Image (CVPR'2018)
Reference: https://github.com/rui1996/DeRaindrop
Fork from https://github.com/shleecs/DeRaindrop_unofficial . Try to change the GPUs' problems.
- Linux
- Python 3.7
- NVIDIA GPU + CUDA CuDNN (CUDA 10.0)
- Pytorch 1.4.1
- TensorboardX
python train.py --gpu 0,1 --train_dataset ../dataset/Derain/train/train/ --eval_dataset ../dataset/Derain/test_a/test_a/ ../dataset/Derain/test_b/test_b/ --batch_size 4
The demo pictures are put under the directory ./demo/input/
and ./demo/output/
is a sample of the ouput of the model. If you want to generate your own, use the following code:
CUDA_VISIBLE_DEVICES=gpu_id python predict.py --mode demo --input_dir ./demo/input/ --output_dir ./demo/output/
Please change the line 60 of predict.py to your own G.pth dir
Training source / loss implementation / dataloader ...
The whole dataset can be find in author pages(https://github.com/rui1996/DeRaindrop)