Image Processing Project

A web-based image processing application that allows users to apply various filters and transformations to images directly in their browser. Built with HTML, CSS, and JavaScript, this project provides an intuitive interface for real-time image manipulation.

Features

• Image Upload: Easy drag-and-drop or file selection interface
• Multiple Filters: Apply various image filters including:
  • Grayscale
  • Sepia
  • Blur
  • Brightness adjustment
  • Contrast adjustment
  • Saturation control
  • And more...
• Real-time Preview: See changes instantly as you apply filters
• Download Processed Images: Save your edited images locally
• Responsive Design: Works seamlessly on desktop and mobile devices
• User-friendly Interface: Clean and intuitive UI/UX design

Project Structure

Image-Processing-Project/
│
├── index.html          # Main HTML file with structure
├── styles.css          # Styling and layout
└── script.js           # Image processing logic and functionality

Technologies Used

• HTML5: Structure and Canvas API for image manipulation
• CSS3: Styling and responsive design
• JavaScript: Core image processing logic and DOM manipulation

Usage

1. Clone this repository:

   git clone https://github.com/RITHESH218/Image-Processing-Project.git

2. Navigate to the project directory:

   cd Image-Processing-Project

3. Open index.html in your web browser:

   • Double-click the file, or
   • Use a local server (recommended for best performance)

4. Upload an image using the upload button or drag-and-drop

5. Apply filters and adjustments using the available controls

6. Download your processed image when satisfied with the results

Demo

Check out the live demo: Image Processing Project Demo

How It Works

The application uses the HTML5 Canvas API to manipulate image pixels directly in the browser. When you upload an image:

1. The image is loaded onto a canvas element
2. Pixel data is extracted using getImageData()
3. Filters are applied by modifying pixel values
4. The processed image is rendered back to the canvas
5. Users can download the result using toDataURL()

Contributing

Contributions are welcome! If you'd like to contribute to this project:

1. Fork the repository
2. Create a new branch (git checkout -b feature/improvement)
3. Make your changes
4. Commit your changes (git commit -am 'Add new feature')
5. Push to the branch (git push origin feature/improvement)
6. Create a Pull Request

Please ensure your code follows the existing style and includes appropriate comments.

License

This project is open source and available under the MIT License.

Author

RITHESH218

• GitHub: @RITHESH218

Acknowledgments

• Thanks to the open-source community for inspiration and resources
• Built as a learning project to explore web-based image processing techniques

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