Deep GrabCut (DeepGC)

This is a PyTorch implementation of Deep GrabCut, for object segmentation. We use DeepLab-v2 instead of DeconvNet in this repository.

The code was tested with Python 3.5. To use this code, please do:

Clone the repo:

git clone https://github.com/jfzhang95/DeepGrabCut-PyTorch
cd DeepGrabCut-PyTorch

Install dependencies:

pip install pytorch torchvision -c pytorch
pip install matplotlib opencv pillow

You can download pretrained model from GoogleDrive, and then put the model into models/
To try the demo of Deep GrabCut, please run:
```
python demo.py
```

If installed correctly, the result should look like this:

To train Deep GrabCut on PASCAL (or PASCAL + SBD), please follow these additional steps:

Download the pre-trained PSPNet model for semantic segmentation, taken from this repository.

cd models/
chmod +x download_pretrained_psp_model.sh
./download_pretrained_psp_model.sh
cd ..

Set the paths in mypath.py, so that they point to the location of PASCAL/SBD dataset.
Run python train.py to train Deep Grabcut.

zxplsec/DeepGrabCut-PyTorch