Grayscale Image Equalization & Enhancement Filter

A simple Streamlit application that allows users to upload images, convert them to grayscale, generate histograms, and apply basic image filters like contrast enhancement or histogram equalization.

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Table of Contents

• About the Project
• Features
• Getting Started
• Prerequisites
• Installation
• Running Script
• Expectations When Running This App
• Demo
• Acknowledgments
• License

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About the Project

This app is a simple yet powerful demonstration of image processing using Python, Streamlit, and Pillow.

It provides an intuitive interface to:

• Upload images
• Convert them to grayscale
• Visualize histograms of pixel intensities
• Apply basic filters like contrast enhancement or histogram equalization

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Features

Feature	Description
Image Upload	Supports JPG, JPEG, and PNG formats.
Grayscale Conversion	Converts uploaded image to grayscale using Pillow's ImageOps.grayscale() method.
Histogram Generation	Displays a histogram of pixel intensities using Matplotlib.
Image Filters	Includes options for contrast enhancement or histogram equalization.

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Getting Started

Clone the repository and set up your environment to run the app.

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Prerequisites

Before running this application, make sure you have the following installed:

• Python 3.8+
• Streamlit (pip install streamlit)
• Pillow (pip install pillow)
• Matplotlib (pip install matplotlib)
• Numpy (pip install numpy)

You can install all dependencies with:

pip install streamlit pillow matplotlib numpy

or run the provided requirements.txt file.

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Installation

1. Clone the repository (or download it as a ZIP):

   git clone https://github.com/your-repo-url.git

2. Navigate to the project directory:

   cd image-to-grayscale-converter

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Running Script

To run the app, use the following command in your terminal:

streamlit run app.py

This will start a local development server and open the Streamlit app in your browser.

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Expectations When Running This App

• Upload an image file (JPG, JPEG, or PNG).
• The original image is displayed alongside its grayscale version.
• A histogram of pixel intensities is shown for the grayscale image.
• You can apply filters like enhance or equalize to further process the image.

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Demo

Here's a quick overview of how the app works:

grayify-eq-enh-filter.mp4

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Acknowledgments

• Streamlit – For creating the web interface.
• Pillow – For handling and manipulating images.
• Matplotlib – For generating histograms.
• Numpy – For array operations.

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License

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