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Visual-Geometric Collaborative Guidance for Affordance Learning

PyTorch implementation of our VCR-Net models [pdf].

  1. Requirements
  2. Download CAL dataset
  3. Test
  4. Citation

Requirements <a name="1"></a>

Environment installation as follows Segformer

pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.9.0/index.html
pip install scipy
pip install einops
pip install torchcontrib
pip install ipython
pip install attr
pip install termcolor
pip install transformers
pip install scikit-image
pip install scikit-learn

Download CAL dataset <a name="2"></a>

Test <a name="3"></a>

You can test the trained model by running test.py.

Download the pretrained models from [ Onedrive | Baidu Pan(7itq) ] and place it in the pretrained/ folder

Download the Bert model from [ Onedrive | Baidu Pan(p468) ] and place it in the bert-base-cased/ folder

Download the models from [ Onedrive | Baidu Pan(2sd3) ] and place it in the save_models/ folder

 python test.py  

Citation <a name="4"></a>