PaddleSeg
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Overview
HEALTH SCORE
Concerning*
Partial score (2/3 categories)
20out of 65
Development cadence is the lead risk. Maintainer coverage is present but not enough to offset the structural risk. Security & Supply Chain is unavailable, so weights were redistributed.
LIFECYCLE
Active
Consistent commits, responsive maintainers, regular releases, and healthy issue triage.
Health breakdown
Concerning*(20/65)
Maintainer availability, known risks and supply chain posture, and whether the project is actively developed or appropriately stable.
Maintainer responsiveness
Median response time is 47 days, but most repositories have response times over 90 days.
Bus factor
No data available. Repository has not been indexed for bus factor.
Organization Diversity
Contributors span 23 organizations.
Project Achievements
Leaderboards
About
PaddleSeg is a deep learning image segmentation toolkit based on PaddlePaddle framework that provides high-performance semantic segmentation, interactive segmentation, and panoptic segmentation models along with training and deployment solutions
First commit
Software value
$6.9M
Tags
autonomous-driving
human-segmentation
image-matting
image-segmentation
interactive-segmentation
lane-detection
medical-image-segmentation
panoptic-segmentation
semantic-segmentation
transformer
video-segmentation
License(s)
Apache-2.0
Data sources
Git
GitHub