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sudo docker pull kbyai/fire-smoke-detection:latest
sudo docker run -v ./license.txt:/home/openvino/kby-ai-fire/license.txt -p 8081:8080 -p 9001:9000 kbyai/fire-smoke-detection:latest

Fire-Smoke-Detection

Overview

This repository demonstrates Fire/Smoke Detection SDK which transforms your CCTV system into an early warning sensor for fire & smoke through docker image pre-built by KBY-AI.
Fire and smoke are common hazards that can cause severe damage to life and property. Fires often begin in quiet, low-traffic areas—electrical rooms, loading docks, storage areas—where nobody’s watching. KBY-AI's fire/smoke detection SDK turns your existing CCTV into smart fire sentries, instantly detecting smoke or flames before they spiral into a crisis. Perfect for warehouses, industrial sites, and logistics hubs.

We can customize the SDK to align with customer's specific requirements.

Try the API

Online Demo

To try KBY-AI's Fire/Smoke Detection SDK online, please visit here

Postman

The API can be evaluated through Postman tool. Here are the endpoints for testing:

• Test with an image file: Send a POST request to http://127.0.0.1:8081/fire.
• Test with a base64-encoded image: Send a POST request to http://127.0.0.1:8081/fire_base64.

SDK License

This project demonstrates KBY-AI's Fire/Smoke Detection SDK, which requires a license per machine.

• The code below shows how to use the license:

  Fire-Smoke-Detection-Docker/app.py

  Lines 17 to 28 in e2f68c8

  	machineCode = getMachineCode()
  	print("\nmachineCode: ", machineCode.decode('utf-8'))
  	try:
  	with open(licensePath, 'r') as file:
  	license = file.read().strip()
  	except IOError as exc:
  	print("failed to open license.txt: ", exc.errno)
  	print("\nlicense: ", license)
  	ret = setActivation(license.encode('utf-8'))

• To request the license, please provide us with the machine code obtained from the getMachineCode function.
  

Please contact us:

🧙Email: contact@kby-ai.com
🧙Telegram: @kbyai
🧙WhatsApp: +19092802609
🧙Discord: KBY-AI
🧙Teams: KBY-AI

How to run

1. System Requirements

• CPU: 2 cores or more (Recommended: 2 cores)
• RAM: 4 GB or more (Recommended: 8 GB)
• HDD: 4 GB or more (Recommended: 8 GB)
• OS: Ubuntu 20.04 or later
• Dependency: ncnn (Version: 2024.12.26)

2. Setup and Test

• Clone the project:

  git clone https://github.com/kby-ai/Fire-Smoke-Detection-Docker.git

  cd Fire-Smoke-Detection-Docker

• Build the Docker image:

  sudo docker build --pull --rm -f Dockerfile -t kby-ai-fire:latest .

• Read machine code

  sudo docker run -e LICENSE="xxxxx" kby-ai-fire:latest
  

• Send us machine code obtained.

• Update the license.txt file by overwriting the license key that you received from KBY-AI team.

• Run the Docker container:

  sudo docker run -v ./license.txt:/home/openvino/kby-ai-fire/license.txt -p 8081:8080 -p 9001:9000 kby-ai-fire:latest

  

• Here are the endpoints to test the API through Postman: Test with an image file: Send a POST request to http://{xx.xx.xx.xx}:8081/fire.
  Test with a base64-encoded image: Send a POST request to http://{xx.xx.xx.xx}:8081/fire_base64.
  

3. Execute the Gradio demo

• Setup Gradio Ensure that the necessary dependencies are installed.
  Gradio requires Python 3.7 or above.
  Install Gradio using pip by running the following command:

  pip install -r requirements.txt

• Run the demo with the following command:

  cd gradio
  python demo.py

• SDK can be tested on the following URL: http://127.0.0.1:9000