face-parsing.PyTorch
                                
                                
                                
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                        Using modified BiSeNet for face parsing in PyTorch
face-parsing.PyTorch
Contents
- Training
 - Demo
 - References
 
Training
- 
Prepare training data: -- download CelebAMask-HQ dataset
-- change file path in the
prepropess_data.pyand run 
python prepropess_data.py
- Train the model using CelebAMask-HQ dataset: Just run the train script:
 
    $ CUDA_VISIBLE_DEVICES=0,1 python -m torch.distributed.launch --nproc_per_node=2 train.py
If you do not wish to train the model, you can download our pre-trained model and save it in res/cp.
Demo
- Evaluate the trained model using:
 
# evaluate using GPU
python test.py
Face makeup using parsing maps
| Hair | Lip | |
|---|---|---|
| Original Input | ![]()  | 
![]()  | 
| Color | ![]()  | 
![]()  | 
	


