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Edge Detection App

A simple web app for applying edge-detection algorithms to images. The backend is a Flask API that processes uploaded images and returns the result. Frontend is served from Backend/templates/index.html and static files in Backend/static/.

Features

  • Multiple edge detection algorithms: Canny, Sobel, Laplacian
  • Adjustable sensitivity control for each algorithm
  • Preview original and processed images
  • Lightweight Flask backend using Pillow for image processing

Tech stack

  • Python 3.8+
  • Flask
  • Pillow (PIL)
  • Flask-CORS
  • HTML / CSS / JavaScript frontend

File structure

Edge Detection App/
├─ Backend/
│  ├─ app.py                # Flask backend and endpoints
│  ├─ edge_detector.py      # (optional) helper for algorithms (if present)
│  ├─ templates/
│  │  └─ index.html         # Frontend page
│  └─ static/
│     ├─ style.css          # App styles
│     └─ script.js          # Frontend JS

Requirements

Install Python 3.8 or later. The project depends on:

  • flask
  • pillow
  • flask-cors

You can install them with pip:

PowerShell (recommended):

cd "d:\5th Semester\Digital Signal Image Processing\End Semester Exam\Edge Detection App\Backend"
python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install flask pillow flask-cors

Or using system Python:

pip install flask pillow flask-cors

(Optionally create a requirements.txt with flask\npillow\nflask-cors.)

Running the app

From the Backend folder run:

cd "d:\5th Semester\Digital Signal Image Processing\End Semester Exam\Edge Detection App\Backend"
python .\app.py

By default the app runs on http://localhost:5000 and serves the frontend at /.

API

  • GET /algorithms — returns available algorithms and short descriptions
  • GET /health — health check
  • POST /upload — upload an image (multipart/form-data) and receive processed PNG

Example curl request (replace image.jpg with your file):

curl -X POST "http://localhost:5000/upload" -F "file=@image.jpg" -F "algorithm=canny" -F "sensitivity=5" --output result.png

Styling notes

I updated the app's Backend/static/style.css with a clean minimal theme (indigo & amber) and simplified layout. If you'd like a different preset or a dark mode toggle, I can add it.


🔗 Connect with Me


If you want, I can also:

  • Add a requirements.txt file
  • Add a short CONTRIBUTING guide
  • Add a GitHub Actions workflow to run a lint/test step

Feel free to tell me which of these you'd like next.

About

A web-based edge detection tool implementing Canny, Sobel, and Laplacian algorithms for computer vision applications.

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