Easy OCR Nestjs

A NestJS application that uses EasyOCR to extract text from images. Currently supports BCA Form OCR processing.

Prerequisites

Before you begin, ensure you have installed:

• Node.js (v16 or higher)
• Python (v3.8 or higher)
• pip (Python package manager)

Installation

1. Clone the repository

git clone <repository-url>
cd ocr

2. Install Node.js dependencies

npm install

3. Install Python dependencies

# Install EasyOCR and its dependencies
pip install easyocr pillow numpy

# If you're using Windows and encounter issues, you might need:
pip install torch torchvision torchaudio

4. Create required directories

mkdir uploads

Project Structure

ocr/
├── src/
│   ├── controllers/
│   │   └── ocr.controller.ts
│   ├── services/
│   │   ├── ocr-base.service.ts
│   │   └── bca-form.service.ts
│   ├── types/
│   │   └── bca-form.type.ts
│   ├── app.module.ts
│   └── main.ts
├── python/
│   └── bca_form_ocr.py
├── uploads/        # Temporary storage for uploaded files
└── README.md

Usage

1. Start the server

# Development mode
npm run start:dev

# Production mode
npm run build
npm run start:prod

2. API Endpoints

Process BCA Form

POST /ocr/bca-form
Content-Type: multipart/form-data

body:
  - image: <file>

Example using cURL:

curl -X POST -F "image=@/path/to/your/image.jpg" http://localhost:3000/ocr/bca-form

Response:

{
  "form_type": "DPBCA",
  "form_title": "Formulir Pengunduran Diri Sebagai Peserta Dana Pensiun BCA",
  "peserta": {
    "nama": "Example Name",
    "nip": "12345678",
    "alamat": "Example Address",
    "email": "example@email.com",
    "hp": "081234567890",
    "tanggal_dokumen": "01 Jan 2024"
  },
  "pengunduran_diri": {
    "tanggal": "15 Jan 2024",
    "alasan": ""
  },
  "rekening": {
    "bank": "BCA",
    "nomor": "1234567890",
    "pemilik": "Example Name"
  },
  "kontak_darurat": {
    "nama": "Emergency Contact",
    "telepon": "081234567890"
  }
}

Features

• Image text extraction using EasyOCR
• Support for BCA Form processing
• Automatic file cleanup after processing
• File type validation (jpg, jpeg, png, pdf)
• File size limit (5MB)
• Error handling
• Type-safe responses

Development

Add New Form Type

1. Create new type definition in src/types/
2. Create new service extending OcrBaseService
3. Add new Python script in python/
4. Add new endpoint in OcrController

Testing

# unit tests
npm run test

# e2e tests
npm run test:e2e

# test coverage
npm run test:cov

Error Handling

The API returns error responses in the following format:

{
  "error": "Error message description"
}

Common errors:

• File type not supported
• File size exceeds limit
• OCR processing failed
• Invalid or corrupted image

License

MIT License

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

This README provides:
1. Clear installation instructions
2. Project structure overview
3. Usage examples with API documentation
4. Development guidelines
5. Testing information
6. Error handling details
7. License and contribution guidelines

You can customize it further based on your specific needs or add more sections as the project grows.