ultralytics/yolov3
PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export. observed · 2026-08-28
Health v2 · maintenance only
67/100
- Activity 98
- Release rhythm 8
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 2929
- days_rel: n/a
- days_push: 13
- n_releases_24m: 0
Adoption not part of the score
10596 stars · 3429 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Ultralytics' PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection. It provides training, validation, inference, and multi-format model export (ONNX, TensorRT, CoreML) tooling.
Use cases
- detect objects in images and videos in real time
- train a YOLOv3 model on a custom dataset
- run object detection inference on GPU or edge devices
- export a detection model to ONNX, TensorRT, or CoreML
- validate object detection accuracy on COCO-style datasets
- deploy a lightweight detector with YOLOv3-tiny
When to choose
- you specifically need the classic YOLOv3 architecture or its tiny/SPP variants
- you want a mature, well-documented PyTorch detection codebase with export tooling
- you need real-time detection on resource-constrained edge hardware
When to avoid
- you want the latest Ultralytics models and features - use the ultralytics package with YOLO11/YOLO26 instead
- you need segmentation, pose estimation, or tracking rather than plain detection
- you require a permissive license - AGPL-3.0 restricts commercial use without an enterprise license
Facets
library · maturity maintenance
machine-learning deep-learning computer-vision image-processing computer-vision deep-learning machine-learning artificial-intelligence python cross-platform yolov3 object-detection pytorch real-time-detection model-training onnx tensorrt coreml edge-ai model-export gpu docker
8 sources
- readme: https://github.com/ultralytics/yolov3 · fetched 2026-08-28 · acd37f33c405
- homepage: https://docs.ultralytics.com/models/yolov3/ · fetched 2026-08-29 · bc6e3fceaedc
- site_page: https://docs.ultralytics.com/quickstart · fetched 2026-08-29 · 1c588270a735
- site_page: https://docs.ultralytics.com/integrations · fetched 2026-08-29 · a82fee1740bf
- site_page: https://docs.ultralytics.com/ · fetched 2026-08-29 · fba5847c3417
- site_page: https://docs.ultralytics.com/modes/train · fetched 2026-08-29 · 5f6f930f49db
- site_page: https://docs.ultralytics.com/modes/predict · fetched 2026-08-29 · cf4c377dca7d
- site_page: https://docs.ultralytics.com/tasks/detect · fetched 2026-08-29 · ac9cb5538b5f
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| ultralytics/yolov3 | main | 67 |
For agents
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Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem