Object Detection
ultralytics
ONNX
Safetensors
helmet-detection
yolo
image-classification
cctv
anpr
india
Instructions to use vivekvar/helmet-v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use vivekvar/helmet-v5 with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("vivekvar/helmet-v5") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
File size: 668 Bytes
e90abd8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | import React from 'react'
export default function CameraSelector({ cameras, recordedMap, current, onSwitch }) {
return (
<select
value={current.cam_id || ''}
onChange={(e) => onSwitch(e.target.value, current.mode || 'recorded')}
className="bg-bg border border-line text-text px-3 py-1.5 rounded text-[13px] min-w-[280px]
focus:outline-none focus:border-accent"
>
<option value="" disabled>— select camera —</option>
{cameras.map(c => (
<option key={c.id} value={c.id}>
{c.id} · {c.label} ({c.district}){recordedMap[c.id] ? ' · rec' : ''}
</option>
))}
</select>
)
}
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