International ID OCR

Automatically extract data from Identity documents.

Mindee’s International ID API uses deep learning to automatically, accurately, and instantaneously parse your documents details. In a few seconds, the API extracts a set of data from your PDFs or photos of ID’s from all locations, including:

  • Document Type
  • Document Number
  • Surnames
  • Given Names
  • Sex
  • Birth Date
  • Birth Place
  • Nationality
  • Personal Number
  • Country of Issue
  • State of Issue
  • Issue Date
  • Expiration Date
  • Address
  • MRZ Line 1
  • MRZ Line 2
  • MRZ Line 3

Set up the API

📘

Before making any API calls, you need to have created your API key.

  1. You'll need an ID Card or a passport or any other identification document. You can use one of the sample documents provided below.


  1. Access your document by clicking on the corresponding product card in the Document Catalog

  1. From the left navigation, go to documentation > API Reference, you'll find sample code in popular languages and command line.
from mindee import Client, product, AsyncPredictResponse

# Init a new client
mindee_client = Client(api_key="my-api-key-here")

# Load a file from disk
input_doc = mindee_client.source_from_path("/path/to/the/file.ext")

# Load a file from disk and enqueue it.
result: AsyncPredictResponse = mindee_client.enqueue_and_parse(
    product.InternationalIdV2,
    input_doc,
)

# Print a brief summary of the parsed data
print(result.document)
const mindee = require("mindee");
// for TS or modules:
// import * as mindee from "mindee";

// Init a new client
const mindeeClient = new mindee.Client({ apiKey: "my-api-key-here" });

// Load a file from disk
const inputSource = mindeeClient.docFromPath("/path/to/the/file.ext");

// Parse the file
const apiResponse = mindeeClient.enqueueAndParse(
  mindee.product.InternationalIdV2,
  inputSource
);

// Handle the response Promise
apiResponse.then((resp) => {
  // print a string summary
  console.log(resp.document.toString());
});
using Mindee;
using Mindee.Input;
using Mindee.Product.InternationalId;

string apiKey = "my-api-key-here";
string filePath = "/path/to/the/file.ext";

// Construct a new client
MindeeClient mindeeClient = new MindeeClient(apiKey);

// Load an input source as a path string
// Other input types can be used, as mentioned in the docs
var inputSource = new LocalInputSource(filePath);

// Call the product asynchronously with auto-polling
var response = await mindeeClient
    .EnqueueAndParseAsync<InternationalIdV2>(inputSource);

// Print a summary of all the predictions
System.Console.WriteLine(response.Document.ToString());

// Print only the document-level predictions
// System.Console.WriteLine(response.Document.Inference.Prediction.ToString());
require 'mindee'

# Init a new client
mindee_client = Mindee::Client.new(api_key: 'my-api-key-here')

# Load a file from disk
input_source = mindee_client.source_from_path('/path/to/the/file.ext')

# Parse the file
result = mindee_client.enqueue_and_parse(
  input_source,
  Mindee::Product::InternationalId::InternationalIdV2
)

# Print a full summary of the parsed data in RST format
puts result.document

# Print the document-level parsed data
# puts result.document.inference.prediction
API_KEY='my-api-key-here'
ACCOUNT='mindee'
ENDPOINT='international_id'
VERSION='2'
FILE_PATH='/path/to/your/file.png'

# Maximum amount of retries to get the result of a queue
MAX_RETRIES=10

# Delay between requests
DELAY=6

# Enqueue the document for async parsing
QUEUE_RESULT=$(curl -sS --request POST \
  -H "Authorization: Token $API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "document=@$FILE_PATH" \
  "https://api.mindee.net/v1/products/$ACCOUNT/$ENDPOINT/v$VERSION/predict_async")

# Status code sent back from the server
STATUS_CODE=$(echo "$QUEUE_RESULT" | grep -oP "[\"|']status_code[\"|']:[\s][\"|']*[a-zA-Z0-9-]*" | rev | cut --complement -f2- -d" " | rev)

# Check that the document was properly queued
if [ -z "$STATUS_CODE" ] || [ "$STATUS_CODE" -gt 399 ] || [ "$STATUS_CODE" -lt 200 ]
then
  if [ -z "$STATUS_CODE" ]
  then
    echo "Request couldn't be processed."
    exit 1
  fi
  echo "Error $STATUS_CODE was returned by API during enqueuing. "

  # Print the additional details, if there are any:
  ERROR=$(echo "$QUEUE_RESULT" | grep -oP "[\"|']error[\"|']:[\s]\{[^\}]*" | rev | cut --complement -f2- -d"{" | rev)
  if [ -z "$ERROR" ]
  then
    exit 1
  fi

  # Details on the potential error:
  ERROR_CODE=$(echo "$ERROR" | grep -oP "[\"|']code[\"|']:[\s]\"[^(\"|\')]*" | rev | cut --complement -f2- -d"\"" | rev)
  MESSAGE=$(echo "$QUEUE_RESULT" | grep -oP "[\"|']message[\"|']:[\s]\"[^(\"|\')]*" | rev | cut --complement -f2- -d"\"" | rev)
  DETAILS=$(echo "$QUEUE_RESULT" | grep -oP "[\"|']details[\"|']:[\s]\"[^(\"|\')]*" | rev | cut --complement -f2- -d"\"" | rev)
  echo "This was the given explanation:"
  echo "-------------------------"
  echo "Error Code: $ERROR_CODE"
  echo "Message: $MESSAGE"
  echo "Details: $DETAILS"
  echo "-------------------------"
  exit 1
else

  echo "File sent, starting to retrieve from server..."

  # Get the document's queue ID
  QUEUE_ID=$(echo "$QUEUE_RESULT" | grep -oP "[\"|']id[\"|']:[\s][\"|'][a-zA-Z0-9-]*" | rev | cut --complement -f2- -d"\"" | rev)

  # Amount of attempts to retrieve the parsed document were made
  TIMES_TRIED=1

  # Try to fetch the file until we get it, or until we hit the maximum amount of retries
  while [ "$TIMES_TRIED" -lt "$MAX_RETRIES" ]
  do
    # Wait for a bit at each step
    sleep $DELAY

    # Note: we use -L here because the location of the file might be behind a redirection
    PARSED_RESULT=$(curl -sS -L \
      -H "Authorization: Token $API_KEY" \
      "https://api.mindee.net/v1/products/$ACCOUNT/$ENDPOINT/v$VERSION/documents/queue/$QUEUE_ID")

    # Isolating the job (queue) & the status to monitor the document
    JOB=$(echo "$PARSED_RESULT" | grep -ioP "[\"|']job[\"|']:[\s]\{[^\}]*" | rev | cut --complement -f2- -d"{" | rev)
    QUEUE_STATUS=$(echo "$JOB" | grep -ioP "[\"|']status[\"|']:[\s][\"|'][a-zA-Z0-9-]*" | rev | cut --complement -f2- -d"\"" | rev)
    if [ "$QUEUE_STATUS" = "completed" ]
    then
      # Print the result
      echo "$PARSED_RESULT"

      # Optional: isolate the document:
      # DOCUMENT=$(echo "$PARSED_RESULT" | grep -ioP "[\"|']document[\"|']:[\s].*([\"|']job[\"|'])" | rev | cut -f2- -d"," | rev)
      # echo "{$DOCUMENT}"

      # Remark: on compatible shells, fields can also be extracted through the use of tools like jq:
      # DOCUMENT=$(echo "$PARSED_RESULT" | jq '.["document"]')
      exit 0
    fi
    TIMES_TRIED=$((TIMES_TRIED+1))
  done
fi

echo "Operation aborted, document not retrieved after $TIMES_TRIED tries"
exit 1
<?php

use Mindee\Client;
use Mindee\Product\InternationalId\InternationalIdV2;

// Init a new client
$mindeeClient = new Client("my-api-key-here");

// Load a file from disk
$inputSource = $mindeeClient->sourceFromPath("/path/to/the/file.ext");

// Parse the file asynchronously
$apiResponse = $mindeeClient->enqueueAndParse(InternationalIdV2::class, $inputSource);

echo $apiResponse->document;

  • Replace my-api-key-here with your new API key, or use the "select an API key" feature and it will be filled automatically.
  • Copy and paste the sample code of your desired choice in your application, code environment or terminal.
  • Replace /path/to/my/file with the path to your document.

❗️

Always remember to replace your API key!

  1. Run your code. You will receive a JSON response with the Id document details.

API Response

Here is the full JSON response you get when you call the API:

{
    "api_request": {
        "error": {},
        "resources": [
            "document",
            "job"
        ],
        "status": "success",
        "status_code": 200,
        "url": "https://api.mindee.net/v1/products/mindee/international_id/v2/documents/65c0af55-2247-45a4-bdea-e0908bca9df9"
    },
    "document": {
        "id": "65c0af55-2247-45a4-bdea-e0908bca9df9",
        "inference": {
            "extras": {},
            "finished_at": "2024-10-25T13:42:20.489000",
            "is_rotation_applied": true,
            "pages": [
                {
                    "extras": {},
                    "id": 0,
                    "orientation": {
                        "value": 0
                    },
                    "prediction": {}
                }
            ],
            "prediction": {...},
            "processing_time": 2.647,
            "product": {
                "features": [
                    "document_type",
                    "document_number",
                    "surnames",
                    "given_names",
                    "sex",
                    "birth_date",
                    "birth_place",
                    "nationality",
                    "personal_number",
                    "country_of_issue",
                    "state_of_issue",
                    "issue_date",
                    "expiry_date",
                    "address",
                    "mrz_line1",
                    "mrz_line2",
                    "mrz_line3"
                ],
                "name": "mindee/international_id",
                "type": "standard",
                "version": "2.1"
            },
            "started_at": "2024-10-25T13:42:17.554000"
        },
        "n_pages": 1,
        "name": "michelle_obama.jpg"
    },
    "job": {
        "available_at": "2024-10-25T13:42:20.499000",
        "error": {},
        "id": "c1e1cf27-f4a3-43cb-8bf0-0651a57756eb",
        "issued_at": "2024-10-25T13:42:17.554000",
        "status": "completed"
    }
}

You can find the prediction within the prediction key found in  document > inference > prediction for document-level predictions: it contains the different fields extracted at the document level, meaning that for multi-pages PDFs, we reconstruct a single receipt object using all the pages.


{
    "document": {
				    ...
            "prediction": {
                "address": {
                    "value": null
                },
                "birth_date": {
                    "value": "1964-01-17"
                },
                "birth_place": {
                    "value": "ILLINOIS, U.S.A."
                },
                "country_of_issue": {
                    "value": "USA"
                },
                "document_number": {
                    "value": "910239248"
                },
                "document_type": {
                    "value": "PASSPORT"
                },
                "expiry_date": {
                    "value": "2018-12-05"
                },
                "given_names": [
                    {
                        "value": "MICHELLE"
                    }
                ],
                "issue_date": {
                    "value": "2013-12-06"
                },
                "mrz_line1": {
                    "value": "P<USAOBAMA<<MICHELLE<<<<<<<<<<<<<<<<<<<<<<<<"
                },
                "mrz_line2": {
                    "value": "9102392482USA6401171F1812051900781200<129676"
                },
                "mrz_line3": {
                    "value": null
                },
                "nationality": {
                    "value": "USA"
                },
                "personal_number": {
                    "value": null
                },
                "sex": {
                    "value": "F"
                },
                "state_of_issue": {
                    "value": null
                },
                "surnames": [
                    {
                        "value": "OBAMA"
                    }
                ]
            },
            ...
     }

Extracted data

Using the above Bill of Lading example the following are the basic fields that can be extracted.

Document Type

  • document_type: The type of personal identification document. Classification among the following values: IDENTIFICATION_CARD, PASSPORT, DRIVER_LICENCE, VISA, RESIDENCY_CARD, VOTER_REGISTRATION
{
  "document_type": {
    "value": "PASSPORT"
  }
}

Document Number

  • document_number: The unique identifier assigned to the document.
{
  "document_number": {
    "value": "910239248"
  }
}

Surnames

  • surnames: The list of document holder’s family names.
{
  "surnames": [
    {
      "value": "OBAMA"
    }
  ]
}

Given Names

  • given-names: The list of the document holder’s given names.
{
  "given_names": [
    {
      "value": "MICHELLE"
    }
  ]
}

Sex

  • sex: The biological sex of the document holder.
{
  "sex": {
    "value": "F"
  }
}

Birth Date

  • birth_date: The date of birth of the document holder.
{
  "birth_date": {
    "value": "1964-01-17"
  }
}

Birth Place

  • birth_place: The place of birth of the document holder.
{
  "birth_place": {
    "value": "ILLINOIS, U.S.A."
  }
}

Nationality

  • nationality: The country of citizenship of the document holder.
{
  "nationality": {
    "value": "USA"
  }
}

Personal Number

  • personal_number: The unique identifier assigned to the document holder.
{
  "personal_number": {
    "value": null
  }
}

Country of Issue

  • country_of_issue: The country where the document was issued.
{
 "country_of_issue": {
   "value": "USA"
  }
}

State of Issue

state_of_issue: The state or territory where the document was issued

{
 "state_of_issue": {
   "value": Null
  }
}

Issue Date

  • issue_date: The date when the document was issued.
{
 "issue_date": {
   "value": "2013-12-06"
  }
}

Expiration Date

  • expiration_date: The date when the document becomes invalid.
{
 "expiration_date": {
   "value": "2018-12-05"
  }
}

Address

  • address: The physical address of the document holder.
{
  "address": {
    "value": null
  }
}

MRZ

  • mrz_line1: the Machine Readable zone, first line.
{
  "mrz_line1": {
    "value": "P<USAOBAMA<<MICHELLE<<<<<<<<<<<<<<<<<<<<<<<<"
  }
}
  • mrz_line2: the Machine Readable zone, second line.
{
  "mrz_line2": {
    "value": "9102392482USA6401171F1812051900781200<129676"
  }
}
  • mrz_line3: the Machine Readable zone, third line.
{
  "mrz_line3": {
    "value": null
  }
}

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