“YORU” (Your Optimal Recognition Utility) is an open-source animal behavior recognition system using Python. YORU can detect animal behaviors, not only single-animal behaviors but also social behaviors. YORU also provides online/offline analysis and closed-loop manipulation.
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Comprehensive Behavior Detection: Recognizes both single-animal and social behaviors, and allows for user-defined animal appearances using deep learning techniques.
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Online/Offline Analysis: Supports real-time and post-experiment data analysis.
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Closed-Loop Manipulation: Enables interactive experiments with live feedback control.
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User-Friendly Interface: Provide the GUI-based software.
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Customizable: Allows you to customize various hardware manipulations in closed-loop system.
For detailed documentation, visit the YORU Documents
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Download or clone the YORU project.
cd "Path/to/download" git clone https://github.com/Kamikouchi-lab/YORU.git -
Install the GPU driver and CUDA toolkit.
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Create a virtual environment using YORU.yml in command prompt or Anaconda prompt.
conda env create -f "Path/to/YORU.yml" -
Activate the virtual environment in the command prompt or Anaconda prompt.
conda activate yoru -
Install Pytorch depending on the CUDA versions.
- For CUDA==12.1
pip install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 --index-url https://download.pytorch.org/whl/cu121- (torch, torchvision and torchaudio will be installed.)
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Run YORU in the command prompt or Anaconda prompt.
conda activate yoru cd "Peth/to/YORU/project/folder" python -m yoru
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Learn step-by-step: Tutorial
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Learn by reading: TBA
- Windows 10 or later
- Memory: 16 GB or more
- OS: Windows 11
- CPU: Intel Core i9 (11th)
- GPU: NVIDIA RTX 3080
- Memory: DDR4 32 GB
- Yamanouchi, H. M., Takeuchi, R. F., Chiba, N., Hashimoto, K., Shimizu, T., Tanaka, R., & Kamikouchi, A. (2024). YORU: social behavior detection based on user-defined animal appearance using deep learning. bioRxiv (p. 2024.11.12.623320). https://doi.org/10.1101/2024.11.12.623320
AGPL-3.0 License: YORU is intended for research/academic/personal use only. See the LICENSE file for more details.
This project includes code from the following repositories: