YOLOv8 Object Detection for AMA Computer College Students

This project provides a hands-on introduction to real-time object detection using the YOLOv8 model. This guide will walk you through setting up your development environment and running the project.

Table of Contents

• Prerequisites
• Project Setup
• How to Run
• Project Structure

Prerequisites

Before you begin, you need to have Python and Visual Studio Code installed on your computer.

1. Installing Visual Studio Code

Visual Studio Code (VS Code) is a free and powerful code editor that we will use for this project.

1. Download VS Code:

   • Go to the official VS Code website: https://code.visualstudio.com/
   • Download the installer for your operating system (Windows, macOS, or Linux).

2. Install VS Code:

   • Run the installer you downloaded.
   • Follow the on-screen instructions. It is recommended to keep the default settings, especially the option to "Add to PATH" (on Windows).

3. Install Python Extension for VS Code:

   • Open VS Code.
   • Go to the Extensions view by clicking on the Extensions icon in the Activity Bar on the side of the window or by pressing Ctrl+Shift+X.
   • Search for "Python" and install the extension provided by Microsoft.

2. Installing Python

Python is the programming language we will use.

1. Download Python:

   • Go to the official Python website: https://www.python.org/downloads/
   • Download the latest stable version of Python (e.g., Python 3.9 or higher).

2. Install Python:

   • Run the Python installer.
   • Important: On the first screen of the installer, make sure to check the box that says "Add Python to PATH". This will make it easier to run Python from the command line.
   • Click "Install Now" and follow the on-screen instructions.

3. Verify the Installation:

   • Open a new terminal or command prompt.
   • Type python --version and press Enter. You should see the Python version you installed.

Project Setup

Now that you have the prerequisites, let's set up the project.

1. Download the Project:

   • Download the project files as a ZIP folder and extract them to a location of your choice (e.g., your Desktop).

2. Open the Project in VS Code:

   • Open VS Code.
   • Go to File > Open Folder and select the folder where you extracted the project files.

3. Install Required Libraries:

   • Open the terminal in VS Code by going to Terminal > New Terminal.
   • In the terminal, run the following command to install the necessary Python libraries from the requirements.txt file:

     pip install -r requirements.txt

4. Download YOLOv8 Model Weights:

   • The project is configured to use yolov8n.pt by default. This file is included in the project.
   • If you want to use a different model, you can download it from the Ultralytics YOLOv8 repository and place it in the project's root directory.

How to Run

1. Add a Video:

   • Create a folder named videos in the project directory.
   • Place any video file you want to analyze inside this videos folder.

2. Run the Script:

   • Make sure you are in the VS Code terminal.
   • Run the main script with the following command:

     python main.py

3. Follow On-Screen Prompts:

   • The script will ask you to choose a video source:
     • Enter 1 to select a video from the videos folder.
     • Enter 2 to provide a full file path to a video on your computer.

4. View the Output:

   • A new window will open, showing the video with objects being detected and labeled in real-time.

5. Quit the Program:

   • To stop the video and close the application, press the 'q' key on your keyboard.

Project Structure

.
├── main.py             # The main Python script for object detection
├── requirements.txt    # A list of project dependencies (Python libraries)
├── yolov8n.pt          # The pre-trained YOLOv8 model weights
└── videos/             # A directory to store your video files
    └── your_video.mp4