CREStereo_RealSense

This is non-official PyTorch implementation of CREStereo for realtime inference on RealSense cameras (model converted from the original MegEngine implementation).

Dependencies

I used the following dependencies (maybe it will work in older versions):

• Python: 3.10.12
• CUDA: 12.8
• PyTorch: 2.7.1
• numpy: 1.26.4
• opencv-python: 4.12.0.88
• Open3D: 0.19.0

Table of Contents

• realtime_rgbd_image.py: realtime depth estimation, ~3-5 fps (PyTorch inference)
• realtime_rgbd_image_onnx_model.py: it also works, but very slowly (ONNX inference)
• point_cloud_visualization.py: visualization of a point cloud using Open3D (PyTorch inference)

Pretrained model

Download models from here and save it into the models folder.

• crestereo_eth3d.pth for PyTorch inference.
• crestereo.onnx and crestereo_without_flow.onnx for ONNX inference.

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.
• 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.

References:

• CREStereo: https://github.com/megvii-research/CREStereo
• CREStereo-Pytorch: https://github.com/ibaiGorordo/CREStereo-Pytorch
• intel RealSense: https://github.com/IntelRealSense/librealsense
• Open3D: https://github.com/isl-org/Open3D