Computer Vision labs

This repository contains a collection of laboratory exercises for my university course in Computer Vision. Each lab explores key concepts and techniques in computer vision, implemented using Python 3.10 and OpenCV.

Introduction

In this course, we explore foundational techniques in computer vision, from camera calibration to advanced image processing and feature extraction.

This repository will be updated continuously as new labs are added throughout the semester.

Lab List

Lab 1: Camera Calibration

Objective: Calibrate a camera to determine intrinsic and extrinsic parameters, and correct for lens distortion.

Topics Covered:

• Camera intrinsic and extrinsic parameters
• Distortion coefficients
• Projection matrix
• Re-projection error

Getting Started

To run the code in this repository, you need Python and several packages installed. You can use the following commands to set up your environment:

1. Clone the repository

   git clone https://github.com/Hamza-cpp/Coputer_Vision_Labs.git
   cd Coputer_Vision_Labs

2. Create and activate a python virtual environment (recommended)

   python -m venv .venv # creation
   source .venv/bin/activate # Linux & macOS
   .venv\Scripts\activate # Windows

3. Install the required dependencies

   pip install -r requirements.txt

Note: If you're using Kaggle or Google Colab, you can upload and run these files directly without setting up a virtual environment.

License

This repository is licensed under the MIT License. See the LICENSE file for more details.