yolo12s-road-damage-rdd2022
rezzzq/yolo12s-road-damage-rdd2022
Tracked by OpenModelStats since August 24, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 500
- Total downloadsCumulative all-time download counter reported by the source platform.
- 1,710
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- —
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 3
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #104 among tracked Object Detection models.
- #28,188
- 25468(down 25468 places)this week
- Parameters
- —
- Last source update
- Dec 7, 2025
- It moved from #11 to #104 among tracked Object Detection models this week.
Downloads over time
Cumulative total downloads observed by OpenModelStatsNot enough tracked history yet for a chart.
OpenModelStats began tracking this model on 2026-08-24. Charts appear as daily observations accumulate.
Likes over time
Not enough tracked history yet for a chart.
OpenModelStats began tracking this model on 2026-08-24. Charts appear as daily observations accumulate.
Rank among tracked models
Lower is betterNot enough tracked history yet for a chart.
OpenModelStats began tracking this model on 2026-08-24. Charts appear as daily observations accumulate.
Overview
yolo12s-road-damage-rdd2022 is a object detection model published by rezzzq. OpenModelStats has tracked the model since Aug 24, 2026, most recently observing it 4h ago.
- Published
- Dec 7, 2025
- Last updated
- Dec 7, 2025
- Library
- ultralytics
- License
- mit
- Task
- Object Detection
- Parameters
- —
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- —
ultralyticsyolov12object-detectionroad-damagepytorchdataset:RDD2022license:mitendpoints_compatibleregion:us
Publisher
rezzzqView publisher statistics →Similar models
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