Object Detection
ultralytics
ONNX
English
computer-vision
yolo
yolov11
helmet-detection
safety
traffic-monitoring
cctv
Instructions to use Smolry/Helmet-classifer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use Smolry/Helmet-classifer with ultralytics:
from huggingface_hub import hf_hub_download from ultralytics import YOLO # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("Smolry/Helmet-classifer", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Download helmet.engine from Smolry/Helmet-classifer: direct link, hf CLI and curl.
- Browser
- Download file 45.9 MB
-
https://huggingface.co/Smolry/Helmet-classifer/resolve/main/helmet.engine
- Command line
-
hf download hf://Smolry/Helmet-classifer/helmet.engine
-
curl -L -o helmet.engine https://huggingface.co/Smolry/Helmet-classifer/resolve/main/helmet.engine
45.9 MB
- Xet hash:
- aae30e65819f27391d46ee9fe2f45c2e22d45108dcb63b5a9cbe75e9e5338028
- Size of remote file:
- 45.9 MB
- SHA256:
- 61496aadb744a57eb1982db732cafd09447e44f708c729f5e28b51080bb9791e
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