Resumen
A PyTorch-based object detection project with training, inference and export workflows. The repository is maintained under ultralytics on GitHub. Its primary language is Python. See the [project README](https://github.com/ultralytics/yolov5#readme) for the supported workflows.
Características principales
- A PyTorch-based object detection project with training, inference and export workflows.
Requisitos, instalación y guía rápida
Use the repository installation guide to select the runtime and any required model weights. Verify operating-system and GPU compatibility before starting.
[Read the upstream installation and quickstart instructions](https://github.com/ultralytics/yolov5#readme).
[Read the upstream installation and quickstart instructions](https://github.com/ultralytics/yolov5#readme).
Uso
Try the documented image or video example with your own test material, inspect the results, then integrate the relevant API or processing workflow.
[Usage examples and configuration reference](https://github.com/ultralytics/yolov5#readme).
[Usage examples and configuration reference](https://github.com/ultralytics/yolov5#readme).
Compatibilidad de modelos y casos de uso
La compatibilidad del modelo no se indica en los metadatos del repositorio.
Notas sobre la licencia y los riesgos
GitHub reports AGPL-3.0 for this repository. Review the upstream license file; model weights, datasets and dependencies may have separate terms.
Source review 2026-09-05: GitHub search metadata and repository README. No runtime benchmark performed. License metadata: AGPL-3.0.
Lanzamiento y mantenimiento
[View upstream releases](https://github.com/ultralytics/yolov5/releases).