License Plate V1

Sample Code:

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.
# The endpoint name must be specified since it cannot be determined from the class.
result: PredictResponse = mindee_client.parse(product.eu.LicensePlateV1, input_doc)

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

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

class LicensePlateV1(raw_prediction)

License Plate API version 1 inference prediction.

static get_endpoint_info(klass)

Retrives the endpoint information for an Inference.

Should never retrieve info for CustomV1, as a custom endpoint should be created to use CustomV1.

Parameters:

klass (Type[Inference]) – product subclass to access endpoint information.

Return type:

Dict[str, str]

endpoint_name: Optional[str] = 'license_plates'

Name of the endpoint.

endpoint_version: Optional[str] = '1'

Version of the endpoint.

is_rotation_applied: Optional[bool]

Whether the document has had any rotation applied to it.

page_id: Optional[int]

Optional page id for page-level predictions.

pages: List[Page[LicensePlateV1Document]]

Page-level prediction(s).

prediction: LicensePlateV1Document

Document-level prediction.

product: Product

Name and version of a given product, as sent back by the API.

class LicensePlateV1Document(raw_prediction, page_id=None)

License Plate API version 1.1 document data.

Parameters:

• raw_prediction (Dict[str, Any]) –

• page_id (Optional[int]) –

license_plates: List[StringField]

List of all license plates found in the image.