A practical walkthrough of setting up FlameGuard, connecting a custom YOLO model, and debugging a full-stack Computer Vision application.

Introduction

I recently explored FlameGuard , an open-source fire detection application built with YOLO, FastAPI, and Next.js.

I wanted to understand how a trained object detection model works inside a complete web application.

I used the original FlameGuard repository and adapted it to work with my own trained fire detection model.

Here's a breakdown of the implementation and what I learned.

Tech Stack

Technology Purpose

Python Backend development

YOLO Fire detection

OpenCV Image processing

FastAPI REST API

SQLite Detection history

Next.js Frontend

React User interface

Conda Dependency management

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