DIYer22 / stereo_matching_crestereo

Effortlessly deploy CREStereo in PyTorch with a simple pip install.

Effortlessly deploy CREStereo in PyTorch with a simple pip install.

Features

• Super performance and generalization enabled by CREStereo
• Effortlessly deploy by pip install
• PyTorch version of CREStereo
• Support both CUDA and CPU
• Combining with calibrating to calibrate stereo cameras and get aligned pair of RGB and depth

Install

# Install
pip install git+https://github.com/DIYer22/stereo_matching_crestereo.git

# Run stereo matching demo
python -m stereo_matching_crestereo.stereo_matching

Python example

from stereo_matching_crestereo import CrestereoMatching
matching = CrestereoMatching()
disparity = matching(rgb1, rgb2)["disparity"]

# Combining with calibrating's stereo to get aligned pair of RGB and depth
# https://github.com/DIYer22/calibrating
stereo.set_stereo_matching(matching)
re = stereo.get_depth(rgb1, rgb2)
depth = re['unrectify_depth']
img1_undistort = re['undistort_img1']

Citation

If you find the code or datasets helpful in your research, please cite:

@inproceedings{li2022practical,
  title={Practical stereo matching via cascaded recurrent network with adaptive correlation},
  author={Li, Jiankun and Wang, Peisen and Xiong, Pengfei and Cai, Tao and Yan, Ziwei and Yang, Lei and Liu, Jiangyu and Fan, Haoqiang and Liu, Shuaicheng},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={16263--16272},
  year={2022}
}