iMoonLab/yolov13
YOLOv13 is a real-time object detection model using hypergraph-enhanced visual perception, implemented in Python with support for mobile and cloud deployment.
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This repository provides an official implementation of the YOLOv13 object detection model. It includes training code, pre-trained model weights, and deployment options such as FastAPI REST API, Android (via NCNN), and Huawei Ascend/Rockchip conversion. The model uses hypergraph learning to enhance visual feature representation for object detection tasks. Users can run inference via provided scripts or interact with the model through HuggingFace Spaces demos.
Frequently asked
- What is iMoonLab/yolov13?
- YOLOv13 is a real-time object detection model using hypergraph-enhanced visual perception, implemented in Python with support for mobile and cloud deployment.
- Is yolov13 open source?
- Yes — iMoonLab/yolov13 is open source, released under the AGPL-3.0 license.
- What language is yolov13 written in?
- iMoonLab/yolov13 is primarily written in Python.
- How popular is yolov13?
- iMoonLab/yolov13 has 1.7k stars on GitHub.
- Where can I find yolov13?
- iMoonLab/yolov13 is on GitHub at https://github.com/iMoonLab/yolov13.