Instructions to use wesjos/YOLO-head-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use wesjos/YOLO-head-detection 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("wesjos/YOLO-head-detection", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
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README.md
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# YOLO Head Detection
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A collection of **seven YOLO checkpoints** trained to detect **human heads** in images —
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useful for crowd counting, privacy blurring, and as a first stage before face recognition.
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# YOLO Head Detection
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> Note: This is not a face detection model. Models trained on camera datasets are used for crowd counting, including two angles: one is a top-down view and the other is an oblique view camera.
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A collection of **seven YOLO checkpoints** trained to detect **human heads** in images —
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useful for crowd counting, privacy blurring, and as a first stage before face recognition.
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