Image Filtering and Kernel Visualization with OpenCV

This repository contains examples of applying various image filters using OpenCV in Python. The examples demonstrate how to visualize kernels, apply different types of filters, and detect edges in an image.

Table of Contents

• Overview
• Setup
• Usage
• License

Overview

This project showcases different image processing techniques using OpenCV. It includes:

• Visualizing custom kernels.
• Applying averaging filters with different kernel sizes.
• Using Gaussian filters.
• Detecting edges using Sobel filters.

Setup

To run the code in this repository, follow these steps:

1. Clone the Repository

   git clone https://github.com/your-username/image-filtering-opencv.git
   cd image-filtering-opencv

2. Install Dependencies Make sure you have Python and the required libraries installed. You can install the dependencies using pip:

   pip install numpy opencv-python matplotlib

Usage

You can run the provided Python script to see the image filtering and kernel visualization in action.

1. Prepare your image

   • Place your image in the images directory and update the file path in the script if necessary.

2. Run the script

   python image_filters.py

License

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