Video Object Detection with YOLOv8

A Python-based solution for detecting objects in video streams using Ultralytics YOLOv8. Detects 80+ common objects (people, vehicles, animals, etc.) and displays them with bounding boxes and labels.

📺 Demo

Click the image above to watch the demo video

Technologies

Backend:

• Python 3.8+
• Flask (Web Framework)
• YOLOv8 (Object Detection)
• OpenCV (Video Processing)
• PyTorch (Deep Learning Backend)

Frontend:

• HTML5/CSS3
• JavaScript

Dataset:

• COCO (Common Objects in Context) 80-class

Deployment:

• Docker
• Kubernetes
• Virtual Environment

How It Works

1. Video Input: Reads video frames using OpenCV
2. Object Detection:
   • Uses YOLOv8n (nano version) for fast inference
   • Processes each frame through the neural network
3. Visualization:
   • Draws bounding boxes around detected objects
   • Labels objects with text

Installation

1. Clone Repository

2. Choose a Deployment Method:

   Option 1: Using Kubernetes

   • Pull Docker Image:

   docker pull ghcr.io/aryanp123/myapp:1.0.0

   • Apply Deployment and Service:

     kubectl apply -f deployment.yaml
     kubectl apply -f service.yaml

   • Access Web Interface: Open http://localhost

   Option 2: Using Docker Compose

   • Start Application:

     docker-compose up -d

   • Access Web Interface: Open http://localhost:3000 in your browser.

   Option 3: Using a Virtual Environment (without Docker)

   • Set Up Virtual Environment:

     python -m venv venv
     source venv/bin/activate  # Linux/MacOS
     venv\Scripts\activate     # Windows

   • Install Dependencies:

     pip install --no-cache-dir \
       flask \
       ultralytics \
       torch \
       opencv-python-headless

   • Start Development Server:

     python app.py

   • Access Web Interface: Open http://localhost:3000 in your browser.

Usage

1. Upload & Process Video

   1. Click "Choose File" and select an MP4 video.
   2. Click "Upload & Process".
   3. View real-time detection results.

Acknowledgments

• YOLOv8 by Ultralytics
• COCO Dataset by Microsoft
• OpenCV for video processing