FR Carte Grise

The Python SDK supports the Mindee V1 Carte Grise API.

Product Specifications

Specification	Details
Endpoint Name	carte_grise
Recommended Version	v1.1
Supports Polling/Webhooks	❌ No
Support Synchronous HTTP Calls	✔️ Yes
Geography	🇫🇷 France

Quick-Start

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

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.fr.CarteGriseV1,
    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: 4443182b-57c1-4426-a288-01b94f226e84
:Filename: default_sample.jpg

Inference
#########
:Product: mindee/carte_grise v1.1
:Rotation applied: Yes

Prediction
==========
:a: AB-123-CD
:b: 1998-01-05
:c1: DUPONT YVES
:c3: 27 RUE DES ROITELETS 59169 FERIN LES BAINS FRANCE
:c41: 2 DELAROCHE
:c4a: EST LE PROPRIETAIRE DU VEHICULE
:d1:
:d3: MODELE
:e: VFS1V2009AS1V2009
:f1: 1915
:f2: 1915
:f3: 1915
:g: 3030
:g1: 1307
:i: 2009-12-04
:j: N1
:j1: VP
:j2: AA
:j3: CI
:p1: 1900
:p2: 90
:p3: GO
:p6: 6
:q: 006
:s1: 5
:s2:
:u1: 77
:u2: 3000
:v7: 155
:x1: 2011-07-06
:y1: 17835
:y2:
:y3: 0
:y4: 4
:y5: 2.5
:y6: 178.35
:Formula Number: 2009AS05284
:Owner's First Name: YVES
:Owner's Surname: DUPONT
:MRZ Line 1:
:MRZ Line 2: CI<<MARQUES<<<<<<<MODELE<<<<<<<2009AS0528402

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

Page 0
------
:a: AB-123-CD
:b: 1998-01-05
:c1: DUPONT YVES
:c3: 27 RUE DES ROITELETS 59169 FERIN LES BAINS FRANCE
:c41: 2 DELAROCHE
:c4a: EST LE PROPRIETAIRE DU VEHICULE
:d1:
:d3: MODELE
:e: VFS1V2009AS1V2009
:f1: 1915
:f2: 1915
:f3: 1915
:g: 3030
:g1: 1307
:i: 2009-12-04
:j: N1
:j1: VP
:j2: AA
:j3: CI
:p1: 1900
:p2: 90
:p3: GO
:p6: 6
:q: 006
:s1: 5
:s2:
:u1: 77
:u2: 3000
:v7: 155
:x1: 2011-07-06
:y1: 17835
:y2:
:y3: 0
:y4: 4
:y5: 2.5
:y6: 178.35
:Formula Number: 2009AS05284
:Owner's First Name: YVES
:Owner's Surname: DUPONT
:MRZ Line 1:
:MRZ Line 2: CI<<MARQUES<<<<<<<MODELE<<<<<<<2009AS0528402

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 Carte Grise V1:

a

a (StringField): The vehicle's license plate number.

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

b

b (DateField): The vehicle's first release date.

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

c1

c1 (StringField): The vehicle owner's full name including maiden name.

print(result.document.inference.prediction.c1.value)

c3

c3 (StringField): The vehicle owner's address.

print(result.document.inference.prediction.c3.value)

c41

c41 (StringField): Number of owners of the license certificate.

print(result.document.inference.prediction.c41.value)

c4a

c4a (StringField): Mentions about the ownership of the vehicle.

print(result.document.inference.prediction.c4a.value)

d1

d1 (StringField): The vehicle's brand.

print(result.document.inference.prediction.d1.value)

d3

d3 (StringField): The vehicle's commercial name.

print(result.document.inference.prediction.d3.value)

e

e (StringField): The Vehicle Identification Number (VIN).

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

f1

f1 (StringField): The vehicle's maximum admissible weight.

print(result.document.inference.prediction.f1.value)

f2

f2 (StringField): The vehicle's maximum admissible weight within the license's state.

print(result.document.inference.prediction.f2.value)

f3

f3 (StringField): The vehicle's maximum authorized weight with coupling.

print(result.document.inference.prediction.f3.value)

Formula Number

formula_number (StringField): The document's formula number.

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

g

g (StringField): The vehicle's weight with coupling if tractor different than category M1.

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

g1

g1 (StringField): The vehicle's national empty weight.

print(result.document.inference.prediction.g1.value)

i

i (DateField): The car registration date of the given certificate.

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

j

j (StringField): The vehicle's category.

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

j1

j1 (StringField): The vehicle's national type.

print(result.document.inference.prediction.j1.value)

j2

j2 (StringField): The vehicle's body type (CE).

print(result.document.inference.prediction.j2.value)

j3

j3 (StringField): The vehicle's body type (National designation).

print(result.document.inference.prediction.j3.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)

Owner's First Name

owner_first_name (StringField): The vehicle's owner first name.

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

Owner's Surname

owner_surname (StringField): The vehicle's owner surname.

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

p1

p1 (StringField): The vehicle engine's displacement (cm3).

print(result.document.inference.prediction.p1.value)

p2

p2 (StringField): The vehicle's maximum net power (kW).

print(result.document.inference.prediction.p2.value)

p3

p3 (StringField): The vehicle's fuel type or energy source.

print(result.document.inference.prediction.p3.value)

p6

p6 (StringField): The vehicle's administrative power (fiscal horsepower).

print(result.document.inference.prediction.p6.value)

q

q (StringField): The vehicle's power to weight ratio.

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

s1

s1 (StringField): The vehicle's number of seats.

print(result.document.inference.prediction.s1.value)

s2

s2 (StringField): The vehicle's number of standing rooms (person).

print(result.document.inference.prediction.s2.value)

u1

u1 (StringField): The vehicle's sound level (dB).

print(result.document.inference.prediction.u1.value)

u2

u2 (StringField): The vehicle engine's rotation speed (RPM).

print(result.document.inference.prediction.u2.value)

v7

v7 (StringField): The vehicle's CO2 emission (g/km).

print(result.document.inference.prediction.v7.value)

x1

x1 (StringField): Next technical control date.

print(result.document.inference.prediction.x1.value)

y1

y1 (StringField): Amount of the regional proportional tax of the registration (in euros).

print(result.document.inference.prediction.y1.value)

y2

y2 (StringField): Amount of the additional parafiscal tax of the registration (in euros).

print(result.document.inference.prediction.y2.value)

y3

y3 (StringField): Amount of the additional CO2 tax of the registration (in euros).

print(result.document.inference.prediction.y3.value)

y4

y4 (StringField): Amount of the fee for managing the registration (in euros).

print(result.document.inference.prediction.y4.value)

y5

y5 (StringField): Amount of the fee for delivery of the registration certificate in euros.

print(result.document.inference.prediction.y5.value)

y6

y6 (StringField): Total amount of registration fee to be paid in euros.

print(result.document.inference.prediction.y6.value)