YOLOv5
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Overview
HEALTH SCORE
Healthy
76out of 100
Solid maintainer coverage and development cadence. Security posture keeps the score from reaching Excellent.
LIFECYCLE
Active
Consistent commits, responsive maintainers, regular releases, and healthy issue triage.
Health breakdown
Healthy(76/100)
Maintainer availability, known risks and supply chain posture, and whether the project is actively developed or appropriately stable.
Maintainer responsiveness
Median response time is 1 day.
Bus factor
3 active maintainers currently have merge rights.
Organization Diversity
Contributors span 193 organizations.
Project Achievements
Leaderboards
About
YOLOv5 is a computer vision model and framework for real-time object detection, offering state-of-the-art performance, easy training and deployment capabilities, and extensive documentation. It implements the YOLO (You Only Look Once) architecture with improvements for speed and accuracy.
First commit
Software value
$784K
Tags
coreml
deep-learning
ios
machine-learning
ml
object-detection
onnx
pytorch
tflite
ultralytics
yolo
yolov3
yolov5
License(s)
AGPL-3.0
Data sources
Git
GitHub