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🤖 YOLOv10 Object Tracking

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This repository contains a Python script for real-time object tracking using YOLOv10 and OpenCV. It allows you to select an object in a video frame, track it, and display its coordinates in real-time.

📋 Table of Contents

🚀 Features

  • Real-time object tracking using YOLOv10 and OpenCV.
  • User-friendly interface for selecting objects in video frames.
  • Real-time display of object coordinates.
  • 360° video support for enhanced video experiences.

📖 Requirements

easydict==1.13
gdown==5.2.0
ipdb==0.13.13
motmetrics==1.4.0
numpy==1.24.4
opencv_python==4.8.1.78
pandas==1.5.3
PyYAML==6.0.1
scipy==1.11.4
torch==2.3.0
torchvision==0.18.0
ultralytics

📦 Installation

  1. Clone this repository to your local machine:

    git clone https://github.com/MAVERICK-VF142/Object_tracking_in_360_video.git
    
  2. Install the required dependencies:

    pip install -r requirements.txt
    
  3. Download the YOLOv10 model weights (yolov10e.pt) and place them in the root directory of this repository.

▶️ Usage

  1. Run the script app.py:

    python app.py
    
  2. Select an object in the video frame by clicking on it. The script will track the selected object and display its coordinates in real-time.

  3. Press 'q' to quit the application.

🛠️ Contributing

Contributions are welcome! Here's how you can contribute:

  1. Fork the repository to your GitHub account.

  2. Clone the forked repository to your local machine:

    git clone https://github.com/your-username/Object_tracking_in_360_video.git
    
  3. Create a new branch for your feature or bug fix:

    git checkout -b feature-name
    

    Replace feature-name with a descriptive name for your feature or bug fix.

  4. Make your changes and commit them:

    git add .
    git commit -m "Description of your changes"
    
  5. Push your changes to your forked repository:

    git push origin feature-name
    
  6. Create a pull request from your forked repository to the main repository's master branch. Note: Please ensure your pull request adheres to the repository's contribution guidelines. Thank you for contributing to this project!

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

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  • Python 97.4%
  • Cuda 0.8%
  • Shell 0.7%
  • Dockerfile 0.5%
  • C++ 0.4%
  • C 0.2%