https://github.com/aliakrem/image-processing-playground-back-end
This project implements a Flask REST API that interfaces with Octave/MATLAB through the oct2py Python module.
https://github.com/aliakrem/image-processing-playground-back-end
flask-application matlab oct2py octave python-matlab
Last synced: 2 months ago
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This project implements a Flask REST API that interfaces with Octave/MATLAB through the oct2py Python module.
- Host: GitHub
- URL: https://github.com/aliakrem/image-processing-playground-back-end
- Owner: AliAkrem
- License: mit
- Created: 2024-12-17T11:38:40.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-12T13:26:16.000Z (over 1 year ago)
- Last Synced: 2025-04-07T06:43:45.075Z (about 1 year ago)
- Topics: flask-application, matlab, oct2py, octave, python-matlab
- Language: Python
- Homepage:
- Size: 19.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 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](https://octave.org/download)
2. Run the installer and follow the installation wizard
3. Add Octave to your system PATH
#### Linux (Ubuntu/Debian)
```bash
sudo apt update
sudo apt install octave
```
#### macOS
```bash
brew install octave
```
## Project Setup
1. Clone the repository
```bash
git clone https://github.com/AliAkrem/image-processing-playground-back-end
cd image-processing-playground-back-end
```
2. Create and activate a virtual environment
```bash
python -m venv venv
# On Windows
venv\Scripts\activate
# On Unix or MacOS
source venv/bin/activate
```
3. Install required Python packages
```bash
pip install -r requirements.txt
```
## Running the Application
1. Start the Flask development server
```bash
flask run
```
2. The API will be available at `http://localhost:5000`
## API Endpoints
```base
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