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🚀 YOLOE: Real-Time Zero-Shot Object Detection

YOLOE is a real-time zero-shot object detection model that can detect any object in real-time. It provides a new solution for object detection tasks.

🚀 Quick Start

This section provides a quick guide to getting started with YOLOE, including installation steps and basic usage instructions.

📦 Installation

To install YOLOE, you need to run the following commands:

pip install git+https://github.com/THU-MIG/yoloe.git#subdirectory=third_party/CLIP
pip install git+https://github.com/THU-MIG/yoloe.git#subdirectory=third_party/ml-mobileclip
pip install git+https://github.com/THU-MIG/yoloe.git#subdirectory=third_party/lvis-api
pip install git+https://github.com/THU-MIG/yoloe.git

wget https://docs-assets.developer.apple.com/ml-research/datasets/mobileclip/mobileclip_blt.pt

📚 Documentation

Prediction

For prediction instructions, please refer to Prediction Section.

Transferring

For transferring instructions, please refer to Transferring Section.

Validation

For validation instructions, please refer to Validation Section.

Training

For training instructions, please refer to Training Section.

BibTeX Entry and Citation Info

If you use this model in your research, please cite it using the following BibTeX entry:

@misc{wang2025yoloerealtimeseeing,
      title={YOLOE: Real-Time Seeing Anything}, 
      author={Ao Wang and Lihao Liu and Hui Chen and Zijia Lin and Jungong Han and Guiguang Ding},
      year={2025},
      eprint={2503.07465},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2503.07465}, 
}

📄 License

This project is licensed under the AGPL-3.0 license.