Instructions to use touati-kamel/yolov8s-forest-fire-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use touati-kamel/yolov8s-forest-fire-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("touati-kamel/yolov8s-forest-fire-detection", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
YOLOv8-Small Forest Fire Detection Model
This model is trained to detect forest fires and related phenomena including:
- Fire
- Fire-smoke
- Fog
- Factory-smoke
Model Details
- Architecture: YOLOv8-Small
- Input size: 640x640
- Classes: 6 classes
- Training: Enhanced with class separation techniques
Usage
from ultralytics import YOLO
model = YOLO('touatikamel/yolov8s-forest-fire-detection')
results = model.predict('path/to/image.jpg')
- Downloads last month
- 300