Fire Detection Computer Vision Model
How to use the Fire Detection Detection API
Try This Model
Drop an image here or click to upload
Or try a test image
Model type: fire-detection-sejra-lrfvy-1-yolo11s-t1
Dataset: fire-detection-sejra-lrfvy/1 (15643 images)
Model ID: achfairuz-9tsc7/fire-detection-sejra-lrfvy-1-yolo11s-t1
Jul 1, 2026
Code Snippets
from inference_sdk import InferenceHTTPClient
CLIENT = InferenceHTTPClient(
api_url="https://serverless.roboflow.com",
api_key="API_KEY"
)
result = CLIENT.infer("YOUR_IMAGE.jpg", model_id="achfairuz-9tsc7/fire-detection-sejra-lrfvy-1-yolo11s-t1")Give your agent everything it needs
Or, Use Free Fire, Smoke and Other Detection API
Powered by general detection model
Code
pip install inference-sdk# 1. Import the library
from inference_sdk import InferenceHTTPClient
# 2. Connect to your workspace
client = InferenceHTTPClient(
api_url="https://serverless.roboflow.com",
api_key="API_KEY"
)
# 3. Run your workflow on an image
result = client.run_workflow(
workspace_name="<YOUR_WORKSPACE>",
workflow_id="<YOUR_WORKFLOW_ID>",
images={
"image": "YOUR_IMAGE.jpg" # Path to your image file
},
parameters={
"classes": "fire, smoke, other"
},
use_cache=True # cache workflow definition for 15 minutes
)
# 4. Get your results
print(result)Run on custom image
Drop an image here or click to upload
Detecting classes:
Or try a test image
About Fire Detection Model
This project provides a comprehensive computer vision resource for the early identification of fire and smoke hazards. Containing nearly 9,000 images, this dataset is designed to help developers build object detection systems that can distinguish between active flames, smoke plumes, and non-threatening environmental factors, significantly improving the speed and accuracy of fire safety monitoring.
Ways to Use Fire Detection Dataset
- Outdoor Wildfire Surveillance: Deploy the model on forest watchtower cameras or high-altitude drones to detect early smoke signatures in remote areas, enabling rapid response before fires spread uncontrollably.
- Industrial Site Monitoring: Integrate the detection system into chemical plants or oil refineries to provide a visual layer of protection, identifying localized fire breakouts that traditional thermal or gas sensors might miss.
- Smart City Fire Safety: Implement the model within urban CCTV networks to automatically alert fire departments to vehicle fires or structure fires in densely populated areas, reducing emergency response times.
- Waste Management and Landfill Safety: Monitor landfill sites for spontaneous combustion by detecting surface smoke or small flames, preventing large-scale environmental hazards and costly subterranean fires.
- False Alarm Filtering: Use the "other" class to train safety systems to recognize common visual distractors (like sunlight reflections or steam), ensuring that emergency protocols are only triggered by genuine fire or smoke events.
Roboflow Agent
Tell the agent what you want to build.
Cite This Project
LicenseCC BY 4.0If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{ fire-detection-sejra-lrfvy_dataset,
title = { Fire Detection Dataset },
type = { Open Source Dataset },
author = { achfairuz },
howpublished = { \url{ https://universe.roboflow.com/achfairuz-9tsc7/fire-detection-sejra-lrfvy } },
url = { https://universe.roboflow.com/achfairuz-9tsc7/fire-detection-sejra-lrfvy },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2026 },
month = { jun },
note = { visited on 2026-07-29 },
}