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yolov10n-forest-fire-detection
touati-kamel/yolov10n-forest-fire-detection
yolov10n-forest-fire-detection is a object detection model from touati-kamel. Use it when you need objects located in an image. It is set up for ultralytics.
This model is trained to detect forest fires and related phenomena including: - Fire - Fire-smoke - Fog - Factory-smoke
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.pt11.5 MB · 100%
At a glance
- Task
- Object Detection
- Library
- ultralytics
- Access
- Public
- Created
- Jul 7, 2025
- Updated
- Jul 7, 2025
- SHA
- 7215d64b
Datasets
Model card
From the Hugging Face model README
YOLOv10n 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: YOLOv10n
- Input size: 640x640
- Classes: 6 classes
- Training: Enhanced with class separation techniques and checkpointing
Usage
from ultralytics import YOLO
model = YOLO('touatikamel/yolov10n-forest-fire-detection')
results = model.predict('path/to/image.jpg')
Checkpoints
This repository includes training checkpoints saved every 10 epochs:
checkpoints/best.pt- Best performing modelcheckpoints/latest.pt- Latest checkpointcheckpoints/epoch_N.pt- Checkpoint from epoch N
Training Resume
To resume training from a checkpoint:
# Download checkpoint and resume training
checkpoint_path, metadata = download_checkpoint_from_hf("latest")
model = YOLO(checkpoint_path)
model.train(data="path/to/dataset.yaml", resume=True)
- Task
- Object Detection
- Library
- ultralytics
- Created
- Jul 7, 2025
- Updated
- Jul 7, 2025