FR Carte Grise

The Java 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

import com.mindee.MindeeClient;
import com.mindee.input.LocalInputSource;
import com.mindee.parsing.common.PredictResponse;
import com.mindee.product.fr.cartegrise.CarteGriseV1;
import java.io.File;
import java.io.IOException;

public class SimpleMindeeClient {

  public static void main(String[] args) throws IOException {
    String apiKey = "my-api-key";
    String filePath = "/path/to/the/file.ext";

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

    // Load a file from disk
    LocalInputSource inputSource = new LocalInputSource(filePath);

    // Parse the file
    PredictResponse<CarteGriseV1> response = mindeeClient.parse(
        CarteGriseV1.class,
        inputSource
    );

    // Print a summary of the response
    System.out.println(response.toString());

    // Print a summary of the predictions
//  System.out.println(response.getDocument().toString());

    // Print the document-level predictions
//    System.out.println(response.getDocument().getInference().getPrediction().toString());

    // Print the page-level predictions
//    response.getDocument().getInference().getPages().forEach(
//        page -> System.out.println(page.toString())
//    );
  }

}

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

Field Types

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:

confidence (Double): the confidence score of the field prediction.
boundingBox (Polygon): contains exactly 4 relative vertices (points) coordinates of a right rectangle containing the field in the document.
polygon (Polygon): contains the relative vertices coordinates (polygon extends List<Point>) of a polygon containing the field in the image.
pageId (Integer): the ID of the page, always null when at document-level.

A Point simply refers to a List of Double.

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

StringField

The text field StringField extends BaseField, but also implements:

value (String): corresponds to the field value.
rawValue (String): corresponds to the raw value as it appears on the document.

DateField

The date field DateField extends BaseField, but also implements:

value (LocalDate): an accessible representation of the value as a Java object. Can be null.

Attributes

The following fields are extracted for Carte Grise V1:

a

a: The vehicle's license plate number.

System.out.println(
  result.getDocument().getInference().getPrediction().getA().value
);

b

b: The vehicle's first release date.

System.out.println(
  result.getDocument().getInference().getPrediction().getB().value
);

c1

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

System.out.println(
  result.getDocument().getInference().getPrediction().getC1().value
);

c3

c3: The vehicle owner's address.

System.out.println(
  result.getDocument().getInference().getPrediction().getC3().value
);

c41

c41: Number of owners of the license certificate.

System.out.println(
  result.getDocument().getInference().getPrediction().getC41().value
);

c4a

c4A: Mentions about the ownership of the vehicle.

System.out.println(
  result.getDocument().getInference().getPrediction().getC4A().value
);

d1

d1: The vehicle's brand.

System.out.println(
  result.getDocument().getInference().getPrediction().getD1().value
);

d3

d3: The vehicle's commercial name.

System.out.println(
  result.getDocument().getInference().getPrediction().getD3().value
);

e

e: The Vehicle Identification Number (VIN).

System.out.println(
  result.getDocument().getInference().getPrediction().getE().value
);

f1

f1: The vehicle's maximum admissible weight.

System.out.println(
  result.getDocument().getInference().getPrediction().getF1().value
);

f2

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

System.out.println(
  result.getDocument().getInference().getPrediction().getF2().value
);

f3

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

System.out.println(
  result.getDocument().getInference().getPrediction().getF3().value
);

Formula Number

formulaNumber: The document's formula number.

System.out.println(
  result.getDocument().getInference().getPrediction().getFormulaNumber().value
);

g

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

System.out.println(
  result.getDocument().getInference().getPrediction().getG().value
);

g1

g1: The vehicle's national empty weight.

System.out.println(
  result.getDocument().getInference().getPrediction().getG1().value
);

i

i: The car registration date of the given certificate.

System.out.println(
  result.getDocument().getInference().getPrediction().getI().value
);

j

j: The vehicle's category.

System.out.println(
  result.getDocument().getInference().getPrediction().getJ().value
);

j1

j1: The vehicle's national type.

System.out.println(
  result.getDocument().getInference().getPrediction().getJ1().value
);

j2

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

System.out.println(
  result.getDocument().getInference().getPrediction().getJ2().value
);

j3

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

System.out.println(
  result.getDocument().getInference().getPrediction().getJ3().value
);

MRZ Line 1

mrz1: Machine Readable Zone, first line.

System.out.println(
  result.getDocument().getInference().getPrediction().getMrz1().value
);

MRZ Line 2

mrz2: Machine Readable Zone, second line.

System.out.println(
  result.getDocument().getInference().getPrediction().getMrz2().value
);

Owner's First Name

ownerFirstName: The vehicle's owner first name.

System.out.println(
  result.getDocument().getInference().getPrediction().getOwnerFirstName().value
);

Owner's Surname

ownerSurname: The vehicle's owner surname.

System.out.println(
  result.getDocument().getInference().getPrediction().getOwnerSurname().value
);

p1

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

System.out.println(
  result.getDocument().getInference().getPrediction().getP1().value
);

p2

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

System.out.println(
  result.getDocument().getInference().getPrediction().getP2().value
);

p3

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

System.out.println(
  result.getDocument().getInference().getPrediction().getP3().value
);

p6

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

System.out.println(
  result.getDocument().getInference().getPrediction().getP6().value
);

q

q: The vehicle's power to weight ratio.

System.out.println(
  result.getDocument().getInference().getPrediction().getQ().value
);

s1

s1: The vehicle's number of seats.

System.out.println(
  result.getDocument().getInference().getPrediction().getS1().value
);

s2

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

System.out.println(
  result.getDocument().getInference().getPrediction().getS2().value
);

u1

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

System.out.println(
  result.getDocument().getInference().getPrediction().getU1().value
);

u2

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

System.out.println(
  result.getDocument().getInference().getPrediction().getU2().value
);

v7

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

System.out.println(
  result.getDocument().getInference().getPrediction().getV7().value
);

x1

x1: Next technical control date.

System.out.println(
  result.getDocument().getInference().getPrediction().getX1().value
);

y1

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

System.out.println(
  result.getDocument().getInference().getPrediction().getY1().value
);

y2

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

System.out.println(
  result.getDocument().getInference().getPrediction().getY2().value
);

y3

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

System.out.println(
  result.getDocument().getInference().getPrediction().getY3().value
);

y4

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

System.out.println(
  result.getDocument().getInference().getPrediction().getY4().value
);

y5

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

System.out.println(
  result.getDocument().getInference().getPrediction().getY5().value
);

y6

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

System.out.println(
  result.getDocument().getInference().getPrediction().getY6().value
);

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