Receipt V5

Sample Code:

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

from mindee.v1 import Client, product, AsyncPredictResponse
from mindee import PathInput

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

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

# Load a file from disk and enqueue it.
result: AsyncPredictResponse = mindee_client.enqueue_and_parse(
    product.ReceiptV5,
    input_doc,
)

# Print a brief summary of the parsed data
print(result.document)

class ReceiptV5(raw_prediction)

Receipt API version 5 inference prediction.

Parameters:

raw_prediction (dict[str, Any])

static get_endpoint_info(klass)

Retrieves 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: str | None = 'expense_receipts'

Name of the endpoint.

endpoint_version: str | None = '5'

Version of the endpoint.

extras: Extras | None = None

Potential Extras fields sent back along with the prediction.

is_rotation_applied: bool | None

Whether the document has had any rotation applied to it.

page_id: int | None

Optional page id for page-level predictions.

pages: list[Page[ReceiptV5Document]]

Page-level prediction(s).

prediction: ReceiptV5Document

Document-level prediction.

product: Product

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

class ReceiptV5Document(raw_prediction, page_id=None)

Receipt API version 5.4 document data.

Parameters:

• raw_prediction (dict[str, Any])

• page_id (int | None)

category: ClassificationField

The purchase category of the receipt.

date: DateField

The date the purchase was made.

document_type: ClassificationField

The type of receipt: EXPENSE RECEIPT or CREDIT CARD RECEIPT.

line_items: list[ReceiptV5LineItem]

List of all line items on the receipt.

locale: LocaleField

The locale of the document.

receipt_number: StringField

The receipt number or identifier.

subcategory: ClassificationField

The purchase subcategory of the receipt for transport and food.

supplier_address: StringField

The address of the supplier or merchant.

supplier_company_registrations: list[CompanyRegistrationField]

List of company registration numbers associated to the supplier.

supplier_name: StringField

The name of the supplier or merchant.

supplier_phone_number: StringField

The phone number of the supplier or merchant.

taxes: Taxes

The list of taxes present on the receipt.

time: StringField

The time the purchase was made.

tip: AmountField

The total amount of tip and gratuity.

total_amount: AmountField

The total amount paid: includes taxes, discounts, fees, tips, and gratuity.

total_net: AmountField

The net amount paid: does not include taxes, fees, and discounts.

total_tax: AmountField

The sum of all taxes.

class ReceiptV5LineItem(raw_prediction, page_id=None)

List of all line items on the receipt.

Parameters:

• raw_prediction (dict[str, Any])

• page_id (int | None)

to_table_line()

Output in a format suitable for inclusion in an rST table.

Return type:

str

bounding_box: Quadrilateral | None

A right rectangle containing the word in the document.

confidence: float

The confidence score.

description: str | None

The item description.

page_n: int

The document page on which the information was found.

polygon: Polygon

A polygon containing the word in the document.

quantity: float | None

The item quantity.

total_amount: float | None

The item total amount.

unit_price: float | None

The item unit price.