High-Performance Image Processing API

A robust web application and REST API designed for digital image processing. This project features a collection of custom-implemented algorithms optimized for performance using vectorization and multiprocessing.

Key Features

• Custom Algorithm Implementation: Core image filters and processing logic built from scratch using NumPy and OpenCV for low-level data handling.

• Optimized Performance: Leverages Python's multiprocessing for parallel execution and vectorization to handle large image matrices efficiently.

• Modern Web Interface: Clean and responsive UI built with React.

Tech Stack

• Backend: Python, Flask, NumPy, OpenCV.

• Frontend: React, JavaScript (ES6+).

• DevOps: Docker, Docker Compose.

Implementation Details

Every filter includes detailed documentation, including pseudocode and logic explanations. You can explore the core implementations in the documentacion-implementacion/ directory:

Main Project: Mosaic Filter

Getting Started

Prerequisites

• Docker
• Docker Compose

Installation & Deployment

Clone the repository:

git clone https://github.com/JAntonioBarrientos/Digital-Image-Processing-Project.git

cd Digital-Image-Processing-Project

Setup Mosaic Library(Optional)

If you wish to use the Mosaic filter, place your source image library in:

     backend/models/data/image_library/

Run with Docker

Launch the entire stack (Frontend + Backend) with a single command:

docker compose up --build

Access the App

Open your browser and navigate to:

http://localhost:3000

Manual Setup (Development Mode)

If you prefer to run the components separately without Docker:

Backend (Flask)

cd backend
python3 -m venv venv
source venv/bin/activate  # Or venv\Scripts\activate on Windows
pip install -r requirements.txt
python app.py

Frontend (React)

cd frontend
npm install
npm start

Optimization Note

The core of this project focuses on reducing computational time. By replacing standard nested loops with NumPy vectorization, we achieved significant speedups in matrix manipulation, while the Multiprocessing module ensures that CPU-intensive filters utilize all available cores.

License

Distributed under the MIT License. See LICENSE for more information.