YORU (Your Optimal Recognition Utility)

“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.

Features

• Comprehensive Behavior Detection: Recognizes both single-animal and social behaviors, and allows for user-defined animal appearances using deep learning techniques.

• Online/Offline Analysis: Supports real-time and post-experiment data analysis.

• Closed-Loop Manipulation: Enables interactive experiments with live feedback control.

• User-Friendly Interface: Provide the GUI-based software.

• Customizable: Allows you to customize various hardware manipulations in closed-loop system.

Quick install

Follow these steps to install YORU quickly:

1. Download or clone the YORU project.

   cd "Path/to/download"
   git clone https://github.com/Kamikouchi-lab/YORU.git 
   

2. Install the appropriate GPU driver and the CUDA toolkit.

3. Create a virtual environment.

   Use YORU.yml file to create a conda environment:

   conda env create -f "Path/to/YORU.yml"
   

4. Activate the virtual environment in the command prompt or Anaconda prompt.

   conda activate yoru
   

5. Install Pytorch corresponding to the CUDA versions.

   • For CUDA==11.8

   pip install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 --index-url https://download.pytorch.org/whl/cu118
   

   • 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.)

6. Run YORU in the command prompt or Anaconda prompt.

   Navigate to the YORU project folder and execute:

   conda activate yoru
   cd "Path/to/YORU/project/folder"
   python -m yoru
   

Learn about YORU

• User guides

• Step-by-step Tutorial

• Testing Guide

Requirements

OS

• Windows 10 or later

Hardware

• Memory: 16 GB RAM or more
• GPU: NVIDIA GPU compatible with the required CUDA version

Development environments

• OS: Windows 11
• CPU: Intel Core i9 (11th)
• GPU: NVIDIA RTX 3080
• Memory: DDR4 32 GB

Reference

• Yamanouchi, H. M., Takeuchi, R. F., Chiba, N., Hashimoto, K., Shimizu, T., Osakada, F., Tanaka, R., & Kamikouchi, A. (2026). YORU: Animal behavior detection with object-based approach for real-time closed-loop feedback. Science Advances, 12(7). https://doi.org/10.1126/sciadv.adw2109

License:

AGPL-3.0 License: YORU is intended for research/academic/personal use only. See the LICENSE file for more details.

Third-Party Libraries and Licenses

This project includes code from the following repositories:

• LabelImg: Licensed under the MIT License

• yolov5: Licensed under the AGPL-3.0 License