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Finger Gesture-Based Scaling of Docker Instances using Machine Learning

Introduction

This project aims to provide an innovative and interactive way to scale Docker instances using finger gestures. By leveraging machine learning techniques, users can perform specific gestures to dynamically scale their Docker environment, making it more intuitive and user-friendly.

Features

Gesture Recognition: The system uses computer vision and machine learning algorithms to recognize finger gestures made by the user in real-time. Dynamic Scaling: Users can perform different predefined finger gestures to scale Docker instances up or down based on their resource requirements. Intuitive Interface: The finger gesture-based control provides a unique and engaging user experience, reducing the complexity of manually configuring Docker scaling. Automation: The system can be set up to automatically scale Docker instances based on predefined rules and gesture patterns.

Requirements

Anaconda (python) OpenCV (for computer vision tasks) AWS Docker (for containerization)

Acknowledgments

This project is inspired by the concept of gesture-based control and aims to simplify the process of scaling Docker instances. We would like to thank the open-source community for their valuable contributions.

Contact

For any questions or inquiries, please contact project maintainer Mayank Sharma at mayank07082001@gmail.com

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