YOLO Object Detection App

A modern web application for real-time object detection in images and videos using powerful YOLO models. Built with a FastAPI backend and a dynamic JavaScript frontend.

🎥 Watch Demo on YouTube
📁 GitHub Repository

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Features

• Real-time object detection (YOLO11)
• Upload image or video easily (drag & drop)
• Choose model type: Fast / Balanced / Accurate
• Smart streaming for video results
• Dark mode styled UI
• Reset and upload new file anytime

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Getting Started

1. Clone this repo

   git clone https://github.com/Raafat-Nagy/YOLO-Object-Detection-App.git
   cd YOLO-Object-Detection-App
   

2. Install dependencies

   pip install -r requirements.txt

3. Download YOLO models Put your models (e.g. yolo11n.pt) in the models/ directory. Get them from: Ultralytics Official Models

4. Run the app

   uvicorn app.main:app --reload

5. Open http://127.0.0.1:8000 in your browser.

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Project Structure

YOLO-Object-Detection-App/
├── app/                # FastAPI backend
│   ├── image_processor.py
│   ├── main.py
│   ├── model_loader.py
│   └── stream_processor.py
├── static/             # Frontend JS/CSS
│   ├── script.js
│   └── style.css
├── templates/          # HTML template
│   └── index.html
├── models/             # YOLO .pt models
│   ├── yolo11m
│   ├── yolo11n
│   └── yolo11s
├── requirements.txt
└── README.md

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Demo

📸 Here’s how it works:

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Tech Stack

• FastAPI – lightweight Python backend
• Ultralytics YOLO – object detection engine
• JavaScript + HTML + CSS – frontend
• Font Awesome – icons

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License

This project is licensed under the MIT License.

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Contact

Feel free to reach out or contribute via pull request or issue!

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