ultralytics and mmyolo

YOLO v8 is the official implementation from Ultralytics, while MMYolo is an open-source framework that implements multiple YOLO variants (including v5-v8) alongside other architectures, making them competitors for users seeking a standardized YOLO training/inference solution, though MMYolo offers broader algorithmic coverage.

ultralytics
100
Verified
mmyolo
67
Established
Maintenance 25/25
Adoption 25/25
Maturity 25/25
Community 25/25
Maintenance 0/25
Adoption 18/25
Maturity 25/25
Community 24/25
Stars: 54,333
Forks: 10,447
Downloads: 10,095,391
Commits (30d): 138
Language: Python
License: AGPL-3.0
Stars: 3,421
Forks: 622
Downloads: 2,263
Commits (30d): 0
Language: Python
License: GPL-3.0
No risk flags
Stale 6m

About ultralytics

ultralytics/ultralytics

Ultralytics YOLO 🚀

Supports multi-task computer vision workflows including object tracking, instance segmentation, image classification, and pose estimation through a unified PyTorch-based architecture. Offers both CLI and Python API interfaces with pre-trained model weights, enabling rapid deployment across detection, segmentation, and estimation pipelines without extensive configuration.

About mmyolo

open-mmlab/mmyolo

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

Scores updated daily from GitHub, PyPI, and npm data. How scores work