The WEBAT (Wind Energy with Bat AI-based Tracker) is a Python-based bat tracking software, integrating machine learning and computer vision with infrared thermal sensors to enhance the monitoring and protection of bats in proximity to wind turbines. This software supports extracting 2D (pixelwise coordinates) and 3D (real-world coordinates) flight trajectories of bat, bird, and insects.
To download the full codes, including large-sized model, git-lfs needs to be installed first.
For MacOS:
brew install git-lfs
git lfs install # Update global git config
git lfs install --system # Update system git config
For Windows:
git lfs install
For Ubuntu:
sudo apt install git-lfs
git lfs install
Then, proceed git clone and set up the environment with conda.
git clone git@github.com:NatLabRockies/WEBAT.git
conda env create --name webat-env -f environment.yml
conda activate webat-env
Please additionally install cudatoolkit, cudnn, cuda if you wish to use GPU.
Relased under software record NREL/SWR-24-121
- Sora Ryu, National Renewable Energy Laboratory, sora.ryu@nlr.gov
Ryu, Sora, Yarbrough, John, Rooney, Samantha, and Hein, Cris. WEBAT (Wind Energy with Bat AI-based Tracker) [SWR-24-121]. Computer Software. https://github.com/NREL/WEBAT. USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office. 06 Nov. 2024. Web. doi:10.11578/dc.20241119.3.