fire-detection Computer Vision Model
How to use the fire-detection Detection API
Try This Model
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Or try a test image
Model type: Roboflow 3.0 Object Detection (Fast)
Dataset: fire-detection-xcrur/1 (1695 images)
Checkpoint: COCO
Feb 23, 2025
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="fire-detection-xcrur/1")Give your agent everything it needs
Or, Use Free Fire, Smoke and Not_fire 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, not_fire"
},
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
detecção de fogo em tempo real, identificando tbm possíveis erros
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-xcrur_dataset,
title = { fire-detection Dataset },
type = { Open Source Dataset },
author = { Debora },
howpublished = { \url{ https://universe.roboflow.com/debora-6ftyj/fire-detection-xcrur } },
url = { https://universe.roboflow.com/debora-6ftyj/fire-detection-xcrur },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2025 },
month = { may },
note = { visited on 2026-07-29 },
}