Computer Vision Projects Repository

Welcome to my Computer Vision Projects Repository! 🚀

This repository contains a diverse range of projects related to computer vision, deep learning, and more. From studies and research about computer vision to practical implementations such as Object detection, people tracking, reinforcement learning, classification, and graph neural networks (GNN), you'll find a variety of interesting projects here.

About

In this repository, I explore various aspects of computer vision and its applications using Python. Whether you're interested in learning about cutting-edge techniques, experimenting with new algorithms, or building practical solutions, you'll find something exciting to explore.

Key Features

• Study and Research: Dive into the world of computer vision with in-depth studies and research projects.
• Practical Implementations: Explore practical implementations of computer vision techniques in real-world scenarios.
• Diverse Projects: From people tracking to reinforcement learning, classification, and graph neural networks, there's a diverse range of projects to explore.
• Python Usage: Most of the projects are implemented using Python, making it easy to understand and extend.

Project Structure

The repository is organized into different directories, each containing projects related to specific aspects of computer vision. Here's a brief overview:

• Studies: Research papers, literature reviews, and theoretical studies related to computer vision.
• Object Detection: Projects focusing on detection in images or videos.
• People Tracking: Projects focusing on tracking people in images or videos.
• Reinforcement Learning: Applications of reinforcement learning techniques in computer vision tasks.
• Classification: Image classification projects using various deep learning architectures.
• Graph Neural Networks (GNN): Projects exploring the application of GNNs in computer vision tasks.

Usage

Feel free to explore the projects in this repository, experiment with the code, and learn from the implementations. If you have any questions, suggestions, or feedback, don't hesitate to reach out!

Technologies Used

• Python
• Deep Learning Libraries (e.g., TensorFlow, PyTorch)
• OpenCV
• Various other Python libraries and frameworks such as Numpy, Pandas, Scipy....

Get Started

Ready to dive in? Check out the projects in this repository and start exploring the fascinating world of computer vision!