🖼️ Image Processing Vision Project

A comprehensive Image Processing and Vision web application built with Python and Streamlit. This interactive tool demonstrates various computer vision algorithms, filters, and transformations for educational and practical purposes.

📌 Overview

This project provides an intuitive interface for applying advanced image processing techniques in real-time. Users can upload images and instantly see the effects of different algorithms, making it an excellent learning tool for computer vision concepts and a practical utility for image enhancement.

✨ Features

Image Enhancement

• Brightness and contrast adjustment
• Image sharpening
• Histogram equalization
• Various blur filters (Gaussian, Median, Bilateral)

Image Transformation

• Rotation and flipping
• Resize with aspect ratio control
• Geometric transformations

Advanced Filtering

• Gaussian blur
• Median filtering
• Bilateral filtering
• Custom kernel operations

Edge Detection

• Sobel operator
• Canny edge detector
• Laplacian edge detection
• Other edge detection algorithms

Morphological Operations

• Erosion and dilation
• Opening and closing
• Advanced morphological transformations

Color Space Conversions

• RGB to Grayscale
• HSV color space
• LAB color space
• Multiple color space transformations

Special Effects

• Image inversion
• Custom filters
• Advanced visual effects

🚀 Quick Start

Prerequisites

• Python 3.8 or higher
• pip package manager

Installation

1. Clone the repository

   git clone https://github.com/yourusername/image-processing-vision-project.git
   cd image-processing-vision-project

2. Create a virtual environment (recommended)

   python -m venv venv
   
   # On Windows
   venv\Scripts\activate
   
   # On macOS/Linux
   source venv/bin/activate

3. Install dependencies

   pip install -r requirements.txt

4. Run the application

   streamlit run app.py

5. Open your browser

   The app will automatically open at http://localhost:8501

📦 Dependencies

Core dependencies include:

• Streamlit - Web application framework
• OpenCV - Computer vision library
• NumPy - Numerical computing
• Pillow - Image processing
• scikit-image - Advanced image algorithms

For a complete list, see requirements.txt

🎯 Usage

1. Upload an Image: Use the sidebar to upload JPG, JPEG, or PNG files
2. Choose Operation: Select from categorized tabs (Basic, Color, Edge Detection, etc.)
3. Adjust Parameters: Fine-tune settings using interactive sliders and controls
4. View Results: See real-time preview of processed images
5. Compare: View original and processed images side-by-side

📂 Project Structure

image-processing-vision-project/
├── app.py                 # Main Streamlit application
├── requirements.txt       # Python dependencies
├── README.md             # Project documentation
├── LICENSE               # MIT License
├── CONTRIBUTING.md       # Contribution guidelines
├── SECURITY.md          # Security policy
├── .gitignore           # Git ignore rules
├── .gitattributes       # Git attributes
└── .env.example         # Environment variables template

🤝 Contributing

Contributions are welcome! Please read our Contributing Guidelines before submitting pull requests.

1. Fork the repository
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

🔒 Security

This project follows security best practices:

• No hardcoded credentials or API keys
• Environment variables for sensitive data
• Regular dependency updates
• Security scanning with GitGuardian

Please report security vulnerabilities via our Security Policy.

📚 Learning Outcomes

• Practical understanding of image processing algorithms
• Experience with computer vision techniques
• Knowledge of OpenCV and related libraries
• Web application development with Streamlit
• Best practices for Python project structure

🛠️ Tech Stack

Technology	Purpose
Python 3.8+	Core programming language
Streamlit	Interactive web framework
OpenCV	Computer vision operations
NumPy	Numerical computations
Pillow	Image manipulation
scikit-image	Advanced image processing

📄 License

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

🙏 Acknowledgments

• Built as a comprehensive image processing learning platform
• Inspired by computer vision course curricula
• Thanks to the open-source community for the amazing libraries

📧 Contact

For questions, suggestions, or issues, please open an issue on GitHub.

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Made with ❤️ using Python and Streamlit