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helmet-v4
vivekvar/helmet-v4
helmet-v4 is a object detection model from vivekvar. Use it when you need objects located in an image. It is set up for ultralytics. The card lists the license as apache-2.0.
Predecessor to vivekvar/helmet-v5. Single YOLO model trained directly on helmet/no-helmet crops from Andhra Pradesh RTGS CCTV.
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At a glance
- Task
- Object Detection
- Library
- ultralytics
- License
- apache-2.0
- Access
- Public
- Created
- Apr 22, 2026
- Updated
- Apr 22, 2026
- SHA
- 41a745b7
Model card
From the Hugging Face model README
Helmet v4 — single-stage YOLO helmet detector
Predecessor to vivekvar/helmet-v5. Single YOLO model trained directly on helmet/no-helmet crops from Andhra Pradesh RTGS CCTV.
Files
best.pt— best YOLO checkpoint from trainingtrain_helmet_v4.py— training scripttraining_log.json,train.log— metricscrops/— training crop dataset (withlabels.dbSQLite)
Why superseded
v4 was a single-stage detector — the model had to simultaneously find the rider and classify helmet presence. This led to:
- Wrong-body-part boxing on multi-bike frames
- Helmets misclassified as no-helmet on profile / back views
- Accuracy plateau at F1 ≈ 0.53
v5 splits this into detect (YOLO fine-tuned) → localize driver head (pose) → classify (EfficientNet-B0), hitting F1 = 0.864 on head crops and mAP50 = 0.979 on detection.
- Task
- Object Detection
- Library
- ultralytics
- License
- apache-2.0
- Created
- Apr 22, 2026
- Updated
- Apr 22, 2026