Computer Vision and Image Processing

Table of Contents

• Introduction
• Project Overview
• Installation
• Usage
• Features
• Contributions
• License

Introduction

Computer Vision is a fascinating field of artificial intelligence that grants machines the ability to perceive, understand, and interpret the visual world. It is all about giving machines the ability to see and process images in a way that resembles human vision. This project delves into image processing and basic computer vision tasks using Python libraries like NumPy, Pillow, and OpenCV.

Project Overview

In this project, I explored the following key aspects of computer vision and image processing:

• Loading and Displaying Images:
  This project covers the process of loading and displaying images using Python libraries like NumPy, Matplotlib, and Pillow.
• Image Filtering:
  Image filtering techniques are demonstrated, allowing users to extract specific features from images by filtering by color channels (Red, Green, Blue).
• Image Manipulation:
  Users can learn how to manipulate images, including resizing, rotating, and applying filters. This project includes examples of converting images to grayscale.
• Creating an Image Canvas:
  This project provides guidance on generating blank canvases and programmatically drawing shapes such as rectangles, circles, and more, allowing for custom image creation.
• Creating a Traffic Light:
  An example illustrates the process of creating a simple traffic light using OpenCV to draw the red, yellow, and green lights.

These aspects collectively offer a foundational understanding of basic image processing and computer vision tasks using Python libraries and tools.

Installation

To get started with this project, make sure to install the necessary dependencies.
You can install the required Python libraries using Conda by running: conda install Pillow

Usage

This project includes various components for image processing and computer vision tasks:

• Loading and Displaying Images:
  Learn how to load and display images using Python libraries like NumPy, Matplotlib, and Pillow.
• Image Filtering:
  Explore filtering techniques by color channels (Red, Green, and Blue) to extract specific image features.
• Image Manipulation:
  Resize, rotate, and apply filters to images, including grayscale conversion.
• Creating an Image Canvas:
  Generate blank canvases and draw shapes such as rectangles, circles, and more programmatically.
• Creating a Traffic Light:
  An example of creating a simple traffic light using OpenCV to draw the red, yellow, and green lights.

Features

• Basic image processing using Python with NumPy, Pillow, and OpenCV.
• Working with image data as structured arrays.
• Understanding and manipulating color channels (Red, Green, Blue).
• Creating and drawing graphics and shapes programmatically.

Contributions

Contributions to this project are very welcome. If you have any ideas, improvements, or fixes, please open an issue or submit a pull request.

License

This project is licensed under the MIT License. Feel free to use, modify, and distribute it according to the terms of the license.

Resources

For more information and resources related to computer vision and image processing, visit:
what is a digital image?
Real Python image processing
Open CV documentation
Pillow Documentation
Image processing