yolov3 and yolov5-pip

These tools are competitors, with A being an earlier model version by Ultralytics and B being a separately packaged and enhanced version of Ultrometric's subsequent YOLOv5 model, offering additional features beyond the original.

yolov3
71
Verified
yolov5-pip
49
Emerging
Maintenance 20/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 23/25
Stars: 10,563
Forks: 3,448
Downloads:
Commits (30d): 7
Language: Python
License: AGPL-3.0
Stars: 294
Forks: 70
Downloads:
Commits (30d): 0
Language: Python
License: GPL-3.0
No Package No Dependents
Stale 6m No Package No Dependents

About yolov3

ultralytics/yolov3

YOLOv3 in PyTorch > ONNX > CoreML > TFLite

Implements multi-scale feature pyramids and anchor-based detection with spatial attention mechanisms for improved accuracy on small objects. Provides built-in training pipelines with data augmentation, mixed-precision support, and batch normalization optimization across PyTorch, ONNX, CoreML, and TFLite export targets for seamless deployment across cloud and edge devices.

About yolov5-pip

fcakyon/yolov5-pip

Packaged version of ultralytics/yolov5 + many extra features

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