Image Processing Project Overview This project implements comprehensive image processing techniques using Python, Pillow and OpenCV libraries. Features Image Transformations: Flip, rotate, resize and crop images. Filter Applications: Apply blur, grayscale, sepia, edge detection and emboss filters. Image Sharpening and Smoothing: Apply sharpening, smoothing and Gaussian blur filters. Text and Shape Overlay: Add customizable text, shapes and watermarks. Image Effects: Apply vignette, film grain and solarize effects. Color Adjustments: Adjust brightness, contrast, saturation and hue. Batch Processing: Process multiple images sequentially. Web Interface: Upload and process images through a simple web interface. README.md: Project summary. requirements.txt: Dependencies list. Learning Outcomes Comprehensive image processing understanding. Proficiency in Pillow, OpenCV and NumPy libraries. Python programming and problem-solving experience. Familiarity with advanced image effects and processing concepts. Enhancements Real-time processing with OpenCV. Machine learning integration with TensorFlow/PyTorch. Advanced effects implementation. Image segmentation. Usage Clone the repository. Install requirements: pip install pillow opencv-python numpy flask. Run the application: python app.py. Open a web browser: http://localhost:5000. Upload an image to apply transformations. File Structure app.py: Main application file.