You can deploy this model and start earning money today!

sreeharivp23/
fire-segmentation-yolo11n

Name: fire-segmentation-yolo11n
Availability: InStock

ultralytics

yolo

yolo11

instance-segmentation

sreeharivp23/fire-segmentation-dataset

agpl-3.0

Views

No views yet

Fire Segmentation — YOLO11n-seg

A YOLO11n instance-segmentation model fine-tuned to detect fire with pixel-accurate masks. Unlike bounding-box fire detectors, it reports the exact flame region, which makes it possible to measure how much of a frame is burning and to draw precise overlays for monitoring/alerting systems.

Usage

python

from ultralytics import YOLO

model = YOLO("fire_seg_yolo11n.pt")

# image, video file, folder, URL or webcam index all work
results = model.predict("fire_video.mp4", conf=0.35)

for r in results:
    if r.masks is not None:
        print(f"fire instances: {len(r.masks)}")
    r.show()  # or r.save()

Or from the CLI:

yolo segment predict model=fire_seg_yolo11n.pt source=fire_video.mp4 conf=0.35

Model details


Base model	`yolo11n-seg.pt` (Ultralytics YOLO11 nano, segmentation)
Task	Instance segmentation, 1 class: `fire`
Input size	640 × 640
Epochs	60
Mask mAP50	0.54
Mask mAP50-95	0.29
Box mAP50	0.55

Training data

The full auto-labelled dataset is published at sreeharivp23/fire-segmentation-dataset: ~1,100 fire images from the CAIR Fire-Detection-Image-Dataset and the DeepQuestAI Fire-Smoke-Dataset, plus 250 no-fire negatives.

Segmentation labels were machine-generated: a pretrained YOLOv8 fire/smoke bounding-box detector proposed fire regions, SAM 2.1 (base) converted each box into a pixel mask, and masks were polygonised into YOLO-seg format. An HSV flame-colour heuristic covered images the detector missed. Validation metrics above are measured against these auto-generated labels, not human annotations.

Limitations

Labels are machine-generated; expect some mask noise, especially around smoke/glow boundaries and small or occluded flames.
Trained mostly on visible orange/yellow flames; performance on blue flames, night-vision or thermal imagery is untested.
Not a certified fire-safety system. Do not use as a substitute for smoke/fire alarms.

License

Fine-tuned from Ultralytics YOLO11, which is released under AGPL-3.0; these weights inherit that license.

sreeharivp23/fire-segmentation-yolo11n