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
| 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> | |
| ) | |
| } | |