🔥 Invisible/Fire Detection System using YOLOv8 (Colab Notebook)

An AI-based fire detection system built entirely in a Google Colab notebook. It uses the YOLOv8 object detection model to identify fire in real-time from a webcam or video input. The system is lightweight, easy to set up, and can be extended with thermal filtering and IoT device integration.

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🚀 Features

• 🔍 Real-time fire detection using webcam or video
• 🤖 Fine-tuned YOLOv8 model on fire datasets
• can detect invisible flames
• ⚙️ Runs entirely on Google Colab (no setup needed!)
• 📸 Supports webcam access using Colab + JavaScript hack
• 🔔 Logs fire detection and can be extended with alert systems
• 🧠 Future-ready for thermal-style filtering and ESP32 integration

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🛠️ Tech Stack

• Python
• YOLOv8 (Ultralytics)
• OpenCV – for real-time video processing
• Google Colab – GPU-powered training and testing
• (Planned) ESP32 + GPIO alert system

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📓 How to Use

1. Open the notebook:
   👉 [Click here to open the Fire Detection Notebook]

2. Follow the cells step-by-step:

   • Install dependencies
   • Train or load YOLOv8 model
   • Upload a video or enable webcam
   • Run detection loop

3. Webcam Access (optional):
   You can use JavaScript in Colab to access your webcam like this:

   from IPython.display import display, Javascript
   display(Javascript('''navigator.mediaDevices.getUserMedia({ video: true })'''))