Flask API with Octave Runtime Integration

This project implements a Flask REST API that interfaces with Octave/MATLAB through the oct2py Python module.

Prerequisites

Before setting up the project, ensure you have the following installed on your system:

• Python 3.8 or higher
• GNU Octave 6.0 or higher
• pip (Python package manager)

Installing GNU Octave

Windows

1. Download the Octave installer from GNU Octave Downloads
2. Run the installer and follow the installation wizard
3. Add Octave to your system PATH

Linux (Ubuntu/Debian)

sudo apt update
sudo apt install octave

macOS

brew install octave

Project Setup

1. Clone the repository

git clone https://github.com/AliAkrem/image-processing-playground-back-end
cd image-processing-playground-back-end

2. Create and activate a virtual environment

python -m venv venv
# On Windows
venv\Scripts\activate
# On Unix or MacOS
source venv/bin/activate

3. Install required Python packages

pip install -r requirements.txt

Running the Application

1. Start the Flask development server

flask run

2. The API will be available at http://localhost:5000

API Endpoints

Endpoint                       Methods  Rule                          
-----------------------------  -------  ------------------------------
api.health_check               GET      /api/health             
api.add_gaussian_noise         POST     /api/add-gaussian-noise       
api.add_slat_and_pepper_noise  POST     /api/add-salt-and-pepper-noise
api.average_filter             POST     /api/average_filter           
api.enhance_image_v1           POST     /api/enhance_v1               
api.enhance_image_v2           POST     /api/enhance_v2               
api.gaussian_filter            POST     /api/gaussian_filter                
api.max_filter                 POST     /api/max_filter               
api.median_filter              POST     /api/median_filter            
api.min_filter                 POST     /api/min_filter               
api.nagao_filter               POST     /api/nagao_filter             
api.prewitt_edge_detection     POST     /api/prewitt_edge_detection  

Development

To contribute to this project:

1. Create a new branch for your feature
2. Make your changes
3. Submit a pull request

License

MIT