arakattack/ocr-ktp repository overview

⁠OCR KTP Flask Application

This Flask application performs Optical Character Recognition (OCR) on Indonesian KTP (Identity Card) images. The app uses EasyOCR and Tesseract to extract and process text from uploaded KTP images.

⁠Features

• OCR Processing: Extracts text from KTP images using EasyOCR or Tesseract.
• API Key Authentication: Secures the API using an API key.
• Error Handling: Graceful handling of various error scenarios, including invalid file types, missing data, and internal server errors.

⁠Requirements

• Python 3.10+
• Flask
• EasyOCR
• PyTesseract
• Pillow
• pytest (for testing)

⁠Installation

1. Create a virtual environment (recommended) and activate it.

2. Install the required dependencies:

   pip install --no-cache-dir -r requirements.txt
   

   Copy

3. Create a file named .env in your project directory and add the following environment variables, replacing the placeholders with your actual values:

   API_KEY=your-api-key  # (Optional, for API access control)
   

   Copy

⁠Configuration

• Update the environment variables in .env API_KEY=your-api-key for static API Key authentication.

⁠Usage

1. Start the application:

   python app.py
   

   Copy

   The application runs on http://0.0.0.0:5000 (localhost) by default in debug mode.

2. Make a POST request to the / endpoint with an image file in the image field of your multipart form data and ocr_choice easyocr or pytesseract ocr engine switch. The API key needs to be included in the request header (if configured).

⁠Example Request (using cURL)

curl -X POST http://localhost:5000/ \
  -H "X-API-KEY: your_api_key" \
  -F "[email protected]" -F 'ocr_choice="easyocr"'

⁠Example Response (JSON)

{
    "error": false,
    "message": "OCR Success!",
    "data": {
        "nik": "3026061812510006",
        "nama": "WIDIARSO",
        "tempat_lahir": "PEMALANG,",
        "tgl_lahir": "18-12-1959",
        "jenis_kelamin": "LAKI-LAKI",
        "agama": "ISLAM",
        "status_perkawinan": "KAWIN",
        "pekerjaan": "KARYAWAN SWASTA",
        "alamat": {
            "name": "SKU JLSUMATRA BLOK B78/15",
            "rt_rw": "0037004",
            "kel_desa": "MEKARSARI",
            "kecamatan": "TAMBUN SELATAN",
            "kabupaten": "KABUPATEN BEKASI",
            "provinsi": "PROVINSI JAWA BARAT\n-"
        },
        "time_elapsed": 2.512
    }
}

⁠Testing

Implement unit tests for your functions using a framework like pytest. Manually test the API endpoint using tools like Postman or cURL as demonstrated in the “Usage” section.

⁠Deployment (Docker Compose)

run docker-compose up

version: "3"

services:
  ocr:
    build:
      context: .
      dockerfile: Dockerfile
    image: ocr
    container_name: ocr
    environment:
      API_KEY: "your_value"
    restart: unless-stopped
    ports:
      - "8000:8000"
    networks:
      - ocr-network
    command: gunicorn app:app -w 4 -t 90 --log-level=debug -b 0.0.0.0:8000 --reload --threads 2 --worker-class gevent --keep-alive 5 --timeout 60 --worker-connections 1000
networks:
  ocr-network:
    driver: bridge