# KTP-Indonesian_ID_Card-OCR
This project aims to create an API that can scan and convert important data (NIK, Name, Place and Date of Birth) from a KTP image into text using PyTesseract Optical Character Recognition (OCR). In addition there is also a deep learning (CNN) based KTP detector that can classify the image whether the image is KTP or not. Thanks to the developers who have developed most of the contents of this system before.

## Prerequisites
* Flask
```
pip install flask
```
* Numpy
```
pip install numpy
```
* OpenCV
```
pip install opencv-contrib-python==4.5.1.48
```
* Pandas
```
pip install pandas
```
* PIL
```
pip install pillow
```
* PyTesseract
```
sudo apt-get install tesseract-ocr
sudo apt-get install tesseract-ocr-ind
pip install pytesseract
```
* TextDistance
```
pip install textdistance
```

## Running the Program
To run the program, use the command below:
```
export FLASK_APP=api.py
flask run
```
or alternatively using this command:
```
python api.py
```

### Request Parameter
Parameter | Data Type | Mandatory | Notes
--- | --- | :---: | ---
image | Image Files | M | Foto KTP

### Response Parameter

Parameter | Description
--- | ---
nik | NIK dari hasil OCR
nama | Nama dari hasil OCR
tempat_lahir | Nama tempat lahir dari hasil OCR
tgl_lahir | Tanggal lahir dari hasil OCR (DD-MM-YYYY)
time_elapsed | Waktu yang pemrosesan yang dibutuhkan (detik)

### Success Response Example
```
{
    "error": false,
    "message": "Proses OCR Berhasil",
    "result": {
        "nik": "1234567890123456",
        "nama": "RIJAL MUHYIDIN",
        "tempat_lahir": "PALEMBANG",
        "tgl_lahir": "10-10-1999",
        "jenis_kelamin": "LAKI-LAKI",
        "agama": "ISLAM",
        "status_perkawinan": "BELUM KAWIN",
        "pekerjaan": "PELAJAR/MAHASISWA",
        "kewarganegaraan": "WNI",
        "alamat": {
            "name": "DUSUN 1 OGAN 5",
            "rt_rw": "001/002",
            "kel_desa": "SUNGAI ARE",
            "kecamatan": "ALANG-ALANG LEBAR",
            "kabupaten": "OGAN ILIR",
            "provinsi": "SUMATERA SELATAN"
        },
        "time_elapsed": "6.306"
    }
}
```

### Notes for KTP Detection using CNN
1. Create new folder, data/cnn
2. Insert model.h5 in that folder. (https://drive.google.com/file/d/12TJDTv0lnwE3lfkHRLuDt3J85FbyFD8R/view?usp=sharing)
4. Run the program

## Acknowledgments
* https://github.com/enningxie/KTP-OCR
* https://github.com/jeffreyevan/OCR