# open-mmlab/mmyolo

OpenMMLab YOLO series toolbox and benchmark. Implemented RTMDet, RTMDet-Rotated,YOLOv5, YOLOv6, YOLOv7, YOLOv8,YOLOX, PPYOLOE, etc.

Repository: https://github.com/open-mmlab/mmyolo
Canonical: https://ross.abutalabs.com/products/mmyolo
Homepage: https://mmyolo.readthedocs.io/zh_CN/dev/
Language: Python
License: GPL-3.0
License Family: copyleft
Topics: object-detection, pytorch, yolo, yolov5, yolov6, yolox, rtmdet, yolov7, yolov8, ppyoloe, deep-learning, rotated-object-detection
Last push: 2024-07-14T02:44:12+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 1446, "days_push": 780, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3468, forks 630 (observed 2026-08-28T04:08:05.882288+00:00)

## What it is
MMYOLO is the OpenMMLab toolbox and benchmark for the YOLO series of object detection models, implemented on PyTorch. It provides unified implementations of RTMDet, YOLOv5-v8, YOLOX, PPYOLOE, and rotated-box variants with a model zoo, training, and deployment tooling.

## Use cases
- train a custom YOLOv8 object detection model
- benchmark YOLO model variants on my dataset
- detect rotated objects like oriented bounding boxes
- deploy YOLO models to production
- compare YOLOv5 vs YOLOX accuracy and speed
- fine-tune a pretrained object detection model in PyTorch

## When to choose
- you want a unified PyTorch framework covering many YOLO variants
- you need rotated/oriented object detection support
- you want modular config-driven training with a model zoo of pretrained weights

## When to avoid
- you need a lightweight single-model inference library
- you want the newest models or frequent updates, as development has slowed
- you prefer non-PyTorch frameworks or avoid GPL-3.0 licensing

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, computer-vision, image-processing, benchmarking
- domain: computer-vision, deep-learning, machine-learning
- platform: python
- tags: yolo, object-detection, pytorch, rotated-object-detection, model-zoo, openmmlab, linux, gpu

## Member repositories
- open-mmlab/mmyolo (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:05.882288+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:36:40.603705+00:00, confidence not recorded.
  - readme: https://github.com/open-mmlab/mmyolo (fetched 2026-08-28T04:08:05.882288+00:00, sha 070ee9458670)
  - registry_pypi: https://pypi.org/pypi/mmyolo/json (fetched 2026-08-29T09:31:15.681673+00:00, sha a3a300c9a1a5)
- Data as of 2026-08-30T08:39:29.467469+00:00.