Omar-Chakroun/Tunisian_ID_OCR

# Te9et Taarif - ID Card Recognition System A full-stack application for Tunisian ID card detection and text extraction using computer vision and OCR. ## Project Structure ``` te9et_taarif-main/ ├── te9et_taarif_backend/ # Django REST API backend │ ├── inference/ # Main app with ID card detection logic │ ├── media/ # Uploaded and processed images │ ├── manage.py │ └── requirements.txt └── te9et_taarif_frontend/ # Vue.js frontend └── taarif-frontend/ ├── src/ └── package.json ``` ## Tech Stack ### Backend - **Django 5.1.2** - Web framework - **Django REST Framework** - API - **OpenCV** - Image processing - **Pytesseract** - OCR - **Roboflow Inference SDK** - ID card detection - **SQLite** - Database ### Frontend - **Vue.js 3** - Frontend framework - **Vite** - Build tool - **Tailwind CSS** - Styling - **Axios** - HTTP client ## Prerequisites Before running the project, ensure you have: - **Python 3.12+** installed - **Node.js 16+** and npm installed - **Tesseract OCR** installed on your system: ```bash # Ubuntu/Debian sudo apt-get install tesseract-ocr # macOS brew install tesseract ``` ## First Time Setup ### 1. Backend Setup ```bash # Navigate to backend directory cd te9et_taarif_backend # Create virtual environment (if not exists) python3 -m venv ../.venv # Activate virtual environment source ../.venv/bin/activate # On Linux/Mac # OR ..\.venv\Scripts\activate # On Windows # Install Python dependencies pip install -r requirements.txt # Run migrations python manage.py migrate # (Optional) Create superuser for admin access python manage.py createsuperuser ``` ### 2. Frontend Setup ```bash # Navigate to frontend directory cd te9et_taarif_frontend/taarif-frontend # Install npm dependencies npm install ``` ## How to Start the Project ### Option 1: Manual Start (Two Terminals) **Terminal 1 - Backend:** ```bash cd te9et_taarif_backend source ../.venv/bin/activate python manage.py runserver ``` **Te …