*Stereo depth estimation on the cones images from the Middlebury dataset (https://vision.middlebury.edu/stereo/data/scenes2003/)*
# 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.
- The model has not been fully tested, I have tested parts of the model, but since I don't have the weight in Pytorch, I cannot test the actual output.
- Any help (checking errors, test to train the model, suggestions...) will be gratly appreciated.
- 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.