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ROI-Nets-pytorch

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Pytorch implementation of "Action Unit Detection with Region Adaptation, Multi-labeling Learning and Optimal Temporal Fusing"

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# ROI-Nets pytorch version
## Pytorch implementation of [Action Unit Detection with Region Adaptation, Multi-labeling Learning and Optimal Temporal Fusing](https://arxiv.org/abs/1704.03067)
## How to use:
- clone codes
- download vgg pretrained parameters [vgg16](https://download.pytorch.org/models/vgg16-397923af.pth) in `data` directory
- prepare labels for every image, the format is shown in `data/labels_224_landmarks_sample.txt`
- modify parameters in `lib/train_test.py`, like `image_dir`,`save_dir`,`person_batch`
- run code: `cd lib; CUDA_VISIBLE_DEVICES=0 python train_test.py`
## Result:
1. train loss  
![train loss](https://raw.githubusercontent.com/SilverFI/ROI-Nets-pytorch/master/data/loss.png)
2. train f1  
![train f1](https://raw.githubusercontent.com/SilverFI/ROI-Nets-pytorch/master/data/f1.png)
3. result  
![result](https://raw.githubusercontent.com/SilverFI/ROI-Nets-pytorch/master/data/result.png)
### Reference: https://github.com/AlexHex7/DRML_pytorch and https://github.com/wiibrew/EAC-Net

ROI-Nets-pytorch

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