Passport

The Python SDK supports the Mindee V1 Passport API.

Product Specifications

Specification
Details

Endpoint Name

passport

Recommended Version

v1.1

Supports Polling/Webhooks

❌ No

Support Synchronous HTTP Calls

✔️ Yes

Geography

🌐 Global

Quick-Start

Using the sample below, we are going to illustrate how to extract the data that we want using the SDK.

Passport Sample

Sample Code

#
# Install the Python client library by running:
# pip install mindee
#

from mindee import Client, PredictResponse, product

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

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

# Load a file from disk and parse it.
result: PredictResponse = mindee_client.parse(
    product.PassportV1,
    input_doc,
)

# Print a summary of the API result
print(result.document)

# Print the document-level summary
# print(result.document.inference.prediction)

Sample Output (rST)

########
Document
########
:Mindee ID: 18e41f6c-16cd-4f8e-8cd2-00ca02a35764
:Filename: default_sample.jpg

Inference
#########
:Product: mindee/passport v1.0
:Rotation applied: Yes

Prediction
==========
:Country Code: GBR
:ID Number: 707797979
:Given Name(s): HENERT
:Surname: PUDARSAN
:Date of Birth: 1995-05-20
:Place of Birth: CAMTETH
:Gender: M
:Date of Issue: 2012-04-22
:Expiry Date: 2017-04-22
:MRZ Line 1: P<GBRPUDARSAN<<HENERT<<<<<<<<<<<<<<<<<<<<<<<
:MRZ Line 2: 7077979792GBR9505209M1704224<<<<<<<<<<<<<<00

Page Predictions
================

Page 0
------
:Country Code: GBR
:ID Number: 707797979
:Given Name(s): HENERT
:Surname: PUDARSAN
:Date of Birth: 1995-05-20
:Place of Birth: CAMTETH
:Gender: M
:Date of Issue: 2012-04-22
:Expiry Date: 2017-04-22
:MRZ Line 1: P<GBRPUDARSAN<<HENERT<<<<<<<<<<<<<<<<<<<<<<<
:MRZ Line 2: 7077979792GBR9505209M1704224<<<<<<<<<<<<<<00

Standard Fields

These fields are generic and used in several products.

BaseField

Each prediction object contains a set of fields that inherit from the generic BaseField class. A typical BaseField object will have the following attributes:

  • value (Union[float, str]): corresponds to the field value. Can be None if no value was extracted.

  • confidence (float): the confidence score of the field prediction.

  • bounding_box ([Point, Point, Point, Point]): contains exactly 4 relative vertices (points) coordinates of a right rectangle containing the field in the document.

  • polygon (List[Point]): contains the relative vertices coordinates (Point) of a polygon containing the field in the image.

  • page_id (int): the ID of the page, always None when at document-level.

  • reconstructed (bool): indicates whether an object was reconstructed (not extracted as the API gave it).

A Point simply refers to a list of two numbers ([float, float]).

Aside from the previous attributes, all basic fields have access to a custom __str__ method that can be used to print their value as a string.

DateField

Aside from the basic BaseField attributes, the date field DateField also implements the following:

  • date_object (Date): an accessible representation of the value as a python object. Can be None.

StringField

The text field StringField only has one constraint: its value is an Optional[str].

Attributes

The following fields are extracted for Passport V1:

Date of Birth

birth_date (DateField): The date of birth of the passport holder.

print(result.document.inference.prediction.birth_date.value)

Place of Birth

birth_place (StringField): The place of birth of the passport holder.

print(result.document.inference.prediction.birth_place.value)

Country Code

country (StringField): The country's 3 letter code (ISO 3166-1 alpha-3).

print(result.document.inference.prediction.country.value)

Expiry Date

expiry_date (DateField): The expiry date of the passport.

print(result.document.inference.prediction.expiry_date.value)

Gender

gender (StringField): The gender of the passport holder.

print(result.document.inference.prediction.gender.value)

Given Name(s)

given_names (List[StringField]): The given name(s) of the passport holder.

for given_names_elem in result.document.inference.prediction.given_names:
    print(given_names_elem.value)

ID Number

id_number (StringField): The passport's identification number.

print(result.document.inference.prediction.id_number.value)

Date of Issue

issuance_date (DateField): The date the passport was issued.

print(result.document.inference.prediction.issuance_date.value)

MRZ Line 1

mrz1 (StringField): Machine Readable Zone, first line

print(result.document.inference.prediction.mrz1.value)

MRZ Line 2

mrz2 (StringField): Machine Readable Zone, second line

print(result.document.inference.prediction.mrz2.value)

Surname

surname (StringField): The surname of the passport holder.

print(result.document.inference.prediction.surname.value)

Last updated

Was this helpful?