Implementation for DeepRFT to CPU.
Paper: https://arxiv.org/abs/2111.11745
 |
Overall Framework of DeepRFT |
For installing, follow these intructions, this is an implementation for CPU.
conda create -n pytorch python=3.10
conda activate pytorch
conda install pytorch==1.11.0 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=11.1 -c pytorch -c conda-forge
pip install matplotlib scikit-image opencv-python yacs joblib natsort h5py tqdm kornia tensorboard ptflops
Install warmup scheduler
cd pytorch-gradual-warmup-lr; python setup.py install; cd ..
To test the pre-trained models of Deblur and Defocus Google Drive on your own images, run
python test.py --weights ckpt_path_here --input_dir path_to_images --result_dir save_images_here --win_size 256 # deblur
python test.py --weights ckpt_path_here --input_dir path_to_images --result_dir save_images_here --win_size 512 # defocus
Here is an example to train:
python train.py
Experiment for image deblurring.
 |
 |
 |
 |
 |
 |