GANet

GA-Net: Guided Aggregation Net for End-to-end Stereo Matching

Building Environment

gcc: >= 5.3

GPU memory: >= 6.5G (for testing)

Pytorch: >= 1.0

Cuda: >=9.2

My platform/settings: ubuntu 18.04 + cuda 10.1 + python 3.6

Requirements

• pip install torch torchvision
• pip install scikit-image
• pip install opencv-python==3.4.2.17 opencv-contrib-python==3.4.2.17

Compile

sh compile.sh

Download pre-trained weight and compile

Run

With GPU:

python main.py --input-left="./data/Synthetic/TL0.png" --input-right="./data/Synthetic/TR0.png" --output="./result/Synthetic/TL0.pfm"

Without GPU:

python main.py --input-left="./data/Synthetic/TL0.png" --input-right="./data/Synthetic/TR0.png" --output="./result/Synthetic/TL0.pfm" --cuda False

• --input-left "path to left image"
• --input-right "path to right image"
• --output "path to output PFM file"
• --cuda use GPU or not (default=True)

Reference:

@inproceedings{Zhang2019GANet,
  title={GA-Net: Guided Aggregation Net for End-to-end Stereo Matching},
  author={Zhang, Feihu and Prisacariu, Victor and Yang, Ruigang and Torr, Philip HS},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={185--194},
  year={2019}
}