Web Application for Image Edge Detection and Computer Vision Algorithms

The web application allows users to upload an image for edge detection and analysis using advanced computer vision techniques. Upon uploading, the application processes the image using popular algorithms such as the Canny edge detector, Sobel operator, or Laplacian of Gaussian to highlight edges and contours in the image. The interface provides real-time results and interactive visualizations, allowing users to compare original and processed images.

The app also includes additional features for applying other computer vision algorithms like object detection, image segmentation, and feature extraction. Users can adjust parameters for edge detection and experiment with different algorithms to better understand how image processing works. The backend of the application is powered by Python and utilizes libraries like OpenCV and scikit-image for image processing and manipulation.

Key Features:

Edge detection using Canny, Sobel, and Laplacian algorithms. Real-time image processing and preview. Adjustable parameters for custom edge detection settings. Integration with other computer vision algorithms (e.g., object detection). Image uploading, downloading, and sharing capabilities. Interactive comparison between original and processed images. The application aims to provide an intuitive interface for users interested in computer vision, from beginners to advanced users, to experiment and learn about edge detection and image processing techniques.