# CREStereo-Pytorch
 Non-official Pytorch implementation of the CREStereo (CVPR 2022 Oral) model converted from the original MegEngine implementation.

![!CREStereo-Pytorch stereo detph estimation](https://github.com/ibaiGorordo/CREStereo-Pytorch/blob/main/doc/img/output.jpg)
 
# Important
- This is just an effort to try to implement the CREStereo model into Pytorch from MegEngine due to the issues of the framework to convert to other formats (https://github.com/megvii-research/CREStereo/issues/3).
- I am not the author of the paper, and I am don't fully understand what the model is doing. Therefore, there might be small differences with the original model that might impact the performance.
- I have not added any license, since the repository uses code from different repositories. Check the License section below for more detail.

# Pretrained model
- Download the model from [here](https://drive.google.com/file/d/1D2s1v4VhJlNz98FQpFxf_kBAKQVN_7xo/view?usp=sharing) and save it into the **[models](https://github.com/ibaiGorordo/CREStereo-Pytorch/tree/main/models)** folder.
- The model was covnerted from the original **[MegEngine weights](https://drive.google.com/file/d/1Wx_-zDQh7BUFBmN9im_26DFpnf3AkXj4/view)** using the `convert_weights.py` script. Place the MegEngine weights (crestereo_eth3d.mge) file into the **[models](https://github.com/ibaiGorordo/CREStereo-Pytorch/tree/main/models)** folder before the conversion.

# Licences:
- CREStereo (Apache License 2.0): https://github.com/megvii-research/CREStereo/blob/master/LICENSE
- RAFT (BSD 3-Clause):https://github.com/princeton-vl/RAFT/blob/master/LICENSE
- LoFTR (Apache License 2.0):https://github.com/zju3dv/LoFTR/blob/master/LICENSE

# References:
- CREStereo: https://github.com/megvii-research/CREStereo
- RAFT: https://github.com/princeton-vl/RAFT
- LoFTR: https://github.com/zju3dv/LoFTR
- Grid sample replacement: https://zenn.dev/pinto0309/scraps/7d4032067d0160
- torch2mge: https://github.com/MegEngine/torch2mge