Image Processing Web Application

An interactive image processing web application built with Python and Streamlit, showcasing a wide range of image processing techniques. This project allows users to apply various filters, enhancements, and transformations on images while learning about underlying image processing concepts.

🚀 Project Overview

This web application provides an intuitive interface to explore several image processing techniques. Key features include basic operations like resizing and flipping images, noise reduction methods, image compression algorithms, and more advanced topics like segmentation and enhancement.

🌟 Key Features

1️⃣ Basic Operations

• Convert images to grayscale
• Adjust intensity of red, green, and blue channels individually
• Flip, sharpen, blur, invert, resize, and rescale images

2️⃣ Noise Reduction

• Explore noise types:
  • Gaussian
  • Salt & Pepper
  • Speckle
  • Poisson
• Apply denoising techniques:
  • Gaussian Blur
  • Median Blur
  • Bilateral Filtering
  • Non-Local Means Denoising
  • Morphological Opening

3️⃣ Image Compression

• Learn about JPEG Compression and its underlying algorithm

4️⃣ Image Enhancement

• Enhance image contrast using Histogram Equalization

5️⃣ Image Segmentation

• Explore thresholding, Watershed Algorithm, contours, and k-means clustering for image segmentation

👥 Team Members

• Adarsh Tayde
• Aashish Vishwakarma
• Tushar Singh

💻 Tech Stack

• Framework: Streamlit
• Libraries: NumPy, Pandas, OpenCV, Pillow

🌐 Live Demo

Explore the web application at: Image Processing Web App

📦 Installation

To run this project locally, follow these steps:

1. Clone the repository

git clone https://github.com/yourusername/image-processing-web-app.git

2. Install the required dependencies

Run the following command to install the required dependencies:

cd image-processing-web-app pip install -r requirements.txt

3. Run the Streamlit application

Use the following command to start the application:

streamlit run app.py

📄 Requirements

The project requires the following libraries:

• streamlit
• numpy
• pandas
• opencv-python
• Pillow

To install them, run:

pip install streamlit numpy pandas opencv-python Pillow

📣 Contributing

We welcome contributions to enhance this project! Feel free to:

1. Fork this repository.
2. Create a branch for your feature or bug fix.
3. Submit a pull request.

For any issues or feature suggestions, please create an issue in this repository.