This project is an Image Processing and Vision application implementing a variety of methods, algorithms, filters, and functions from the syllabus and beyond.
It features an interactive web app built with Python Streamlit, enabling users to upload images, apply processing techniques, and view results instantly.
The project serves as both a learning tool and a demonstration platform for image enhancement, transformation, and analysis.
- Image Enhancement – Apply filters, adjust brightness/contrast, sharpen, and more.
- Image Transformation – Rotate, resize, crop, and perform geometric transformations.
- Filtering Techniques – Gaussian, median, bilateral, and custom kernel filters.
- Edge Detection – Sobel, Canny, Laplacian, and other operators.
- Morphological Operations – Erosion, dilation, opening, and closing.
- Color Space Conversions – RGB ↔ Grayscale, HSV, LAB, etc.
- Custom Algorithms – Includes advanced techniques beyond the syllabus.
- Interactive Interface – Real-time preview with adjustable parameters.
- Python – Core programming language.
- Streamlit – For building the interactive web application.
- OpenCV – Image processing and computer vision operations.
- NumPy – Numerical computations and matrix manipulations.
- Pillow – Image manipulation and format handling.
- Hands-on experience with multiple image processing algorithms.
- Understanding of computer vision concepts through interactive experimentation.
- Experience in building and deploying a web application using Streamlit.
- This project is licensed under the MIT License.