kbyai/fire-smoke-detection repository overview

⁠

⁠Product & Resources

For more information, visit KBY AI's GitHub Repository⁠.

⁠Fire/Smoke Detection-Docker

⁠Overview

This repository demonstrates Fire/Smoke Detection SDK with unmatched accuracy and precision by applying SOTA(State-of-the-art) deep learning techniques.
KBY-AI's Fire/Smoke Detection solutions utilizes artificial intelligence and machine learning to greatly surpass legacy solutions. Now, in real-time, users can detect fire or smoke from static image or video frame through API. The repository includes features that allow for testing Fire/Smoke Detection against images using both image files and base64-encoded images.

⁠Docker Run

• Pull docker image.

sudo docker pull kbyai/fire-smoke-detection:latest

• Run docker container with license key file.

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

⁠SDK License

This project demonstrates KBY-AI's Fire/Smoke Detection SDK, which requires a license for each machine or instance on which it runs.

• To get the machine code for license, use the following syntax:

sudo docker run -e LICENSE="xxxxx" kbyai/fire-smoke-detection:latest

• To request the license, please provide us with the machine code obtained from your console.

Contact us:
�Email: [email protected]⁠
🧙Telegram: @kbyaisupport⁠
�WhatsApp: +13348402323⁠
�Discord: KBY-AI⁠
�Teams: KBY-AI⁠

⁠Online Demo

This SDK can be tested on online test demo page 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.