Edge Detection CNN Web Application

This is a web application that utilizes Convolutional Neural Networks (CNN) for edge detection on images. Built with Streamlit, the app allows users to upload an image and apply various edge detection filters, showcasing the power of CNNs in real-time image processing.

LIVE AT : https://edgedetector.streamlit.app/

WhatsApp.Video.2025-01-02.at.16.49.00.mp4

Features:

• Image Upload: Upload your image via the user-friendly interface.
• Edge Detection Filters: Apply up to 15 different edge detection filters to your image and see the results instantly.
• Interactive UI: Seamlessly explore how different filters affect your image, with clear visualizations and the ability to select different filters from a dropdown.
• Real-Time Output: The filtered image and its corresponding edge detection results are displayed instantly.

How It Works:

The app uses convolutional filters to process the uploaded image and detect edges based on various criteria. These filters help highlight areas of high intensity change, often used for image preprocessing in computer vision tasks.

How to Run:

1. Clone this repository.
2. Install the necessary dependencies using pip install -r requirements.txt.
3. Run the app with streamlit run edgeDetectionOnImage.py.
4. Upload an image and enjoy exploring the edge detection results!

Video Demo:

A detailed demo of how the application works can be found below:

[Insert Link to Video]

Tech Stack:

• Python
• Streamlit
• OpenCV
• NumPy

Feel free to explore the code, and don't hesitate to reach out for any questions or improvements!