This is an improved document dewarping method based on Control Points.
git clone https://github.com/NikLi66/Improved_Control_Points icp
cd icp
bash ddp_train.sh
Note: you could change the output path, data path and the number of gpus if necessary.
bash test.sh
python eval.py
- Rewritting most part of the original codes to make it more readable.
- Adding CBAM modules.
- Adding Coord Conv modules.
- Adding some data augmentations widely used in dewarp task.
- Optimizing the loss function by adding a weight mask.
I strongly recommend you slightly change the codes in dataset/dataloader.py to make it works for your onw dataset. You only need to change the codes in getitem and init functions I suppose. The data format used in this project is following Control Points. Please find more details in that repository if you like.