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| datasets | 6 years ago | |
| facades/github | 6 years ago | |
| models | 6 years ago | |
| myutils | 6 years ago | |
| pretrained_models | 6 years ago | |
| transforms | 6 years ago | |
| README.md | 6 years ago | |
| kernel.mat | 6 years ago | |
| misc.py | 6 years ago | |
| test_face_deblur.py | 6 years ago | |
| train_face_deblur.py | 6 years ago | |
README.md
UMSN-Face-Deblurring
Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks
Rajeev Yasarla, Federico Perazzi, Vishal M. Patel
Prerequisites:
- Linux
- Python 2 or 3
- CPU or NVIDIA GPU + CUDA CuDNN (CUDA 8.0)
To test UMRL:
python2.7 test_face_deblur.py --dataroot ./facades/github/ --valDataroot <path_to_test_data> --netG ./pretrained_models/Deblur_epoch_Best.pth
To train UMRL:
python2.7 train_face_deblur.py --dataroot <path_to_train_data> --valDataroot ./facades/github/ --exp ./face_deblur --batchSize 10
- input should be clean image. blurry images for trained are generated by the code it self.