Receipt OCR Python
The Python OCR SDK supports the Receipt API.
Using the sample below, we are going to illustrate how to extract the data that we want using the OCR SDK.
Quick-Start
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.ReceiptV5, input_doc)
# Print a summary of the API result
print(result.document)
# Print the document-level summary
# print(result.document.inference.prediction)
Output (RST):
########
Document
########
:Mindee ID: d96fb043-8fb8-4adc-820c-387aae83376d
:Filename: default_sample.jpg
Inference
#########
:Product: mindee/expense_receipts v5.3
:Rotation applied: Yes
Prediction
==========
:Expense Locale: en-GB; en; GB; GBP;
:Purchase Category: food
:Purchase Subcategory: restaurant
:Document Type: EXPENSE RECEIPT
:Purchase Date: 2016-02-26
:Purchase Time: 15:20
:Total Amount: 10.20
:Total Net: 8.50
:Total Tax: 1.70
:Tip and Gratuity:
:Taxes:
+---------------+--------+----------+---------------+
| Base | Code | Rate (%) | Amount |
+===============+========+==========+===============+
| 8.50 | VAT | 20.00 | 1.70 |
+---------------+--------+----------+---------------+
:Supplier Name: clachan
:Supplier Company Registrations: Type: VAT NUMBER, Value: 232153895
Type: VAT NUMBER, Value: 232153895
:Supplier Address: 34 Kingley Street W1B 50H
:Supplier Phone Number: 02074940834
:Receipt Number: 54/7500
:Line Items:
+--------------------------------------+----------+--------------+------------+
| Description | Quantity | Total Amount | Unit Price |
+======================================+==========+==============+============+
| Meantime Pale | 2.00 | 10.20 | |
+--------------------------------------+----------+--------------+------------+
Page Predictions
================
Page 0
------
:Expense Locale: en-GB; en; GB; GBP;
:Purchase Category: food
:Purchase Subcategory: restaurant
:Document Type: EXPENSE RECEIPT
:Purchase Date: 2016-02-26
:Purchase Time: 15:20
:Total Amount: 10.20
:Total Net: 8.50
:Total Tax: 1.70
:Tip and Gratuity:
:Taxes:
+---------------+--------+----------+---------------+
| Base | Code | Rate (%) | Amount |
+===============+========+==========+===============+
| 8.50 | VAT | 20.00 | 1.70 |
+---------------+--------+----------+---------------+
:Supplier Name: clachan
:Supplier Company Registrations: Type: VAT NUMBER, Value: 232153895
Type: VAT NUMBER, Value: 232153895
:Supplier Address: 34 Kingley Street W1B 50H
:Supplier Phone Number: 02074940834
:Receipt Number: 54/7500
:Line Items:
+--------------------------------------+----------+--------------+------------+
| Description | Quantity | Total Amount | Unit Price |
+======================================+==========+==============+============+
| Meantime Pale | 2.00 | 10.20 | |
+--------------------------------------+----------+--------------+------------+
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:
- value (
Union[float, str]
): corresponds to the field value. Can beNone
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, alwaysNone
when at document-level. - reconstructed (
bool
): indicates whether an object was reconstructed (not extracted as the API gave it).
Note: 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.
AmountField
The amount field AmountField
only has one constraint: its value is an Optional[float]
.
ClassificationField
The classification field ClassificationField
does not implement all the basic BaseField
attributes. It only implements value, confidence and page_id.
Note: a classification field's
value is always a
str`.
CompanyRegistrationField
Aside from the basic BaseField
attributes, the company registration field CompanyRegistrationField
also implements the following:
- type (
str
): the type of company.
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 beNone
.
LocaleField
The locale field LocaleField
only implements the value, confidence and page_id base BaseField
attributes, but it comes with its own:
- language (
str
): ISO 639-1 language code (e.g.:en
for English). Can beNone
. - country (
str
): ISO 3166-1 alpha-2 or ISO 3166-1 alpha-3 code for countries (e.g.:GRB
orGB
for "Great Britain"). Can beNone
. - currency (
str
): ISO 4217 code for currencies (e.g.:USD
for "US Dollars"). Can beNone
.
StringField
The text field StringField
only has one constraint: its value is an Optional[str]
.
TaxesField
Tax
Aside from the basic BaseField
attributes, the tax field TaxField
also implements the following:
- rate (
float
): the tax rate applied to an item expressed as a percentage. Can beNone
. - code (
str
): tax code (or equivalent, depending on the origin of the document). Can beNone
. - base (
float
): base amount used for the tax. Can beNone
.
Note: currently
TaxField
is not used on its own, and is accessed through a parentTaxes
object, a list-like structure.
Taxes (Array)
The Taxes
field represents a list-like collection of TaxField
objects. As it is the representation of several objects, it has access to a custom __str__
method that can render a TaxField
object as a table line.
Specific Fields
Fields which are specific to this product; they are not used in any other product.
Line Items Field
List of line item details.
A ReceiptV5LineItem
implements the following attributes:
- description (
str
): The item description. - quantity (
float
): The item quantity. - total_amount (
float
): The item total amount. - unit_price (
float
): The item unit price.
Attributes
The following fields are extracted for Receipt V5:
Purchase Category
category (ClassificationField): The purchase category among predefined classes.
Possible values include:
- toll
- food
- parking
- transport
- accommodation
- gasoline
- telecom
- miscellaneous
print(result.document.inference.prediction.category.value)
Purchase Date
date (DateField): The date the purchase was made.
print(result.document.inference.prediction.date.value)
Document Type
document_type (ClassificationField): One of: 'CREDIT CARD RECEIPT', 'EXPENSE RECEIPT'.
Possible values include:
- expense_receipt
- credit_card_receipt
print(result.document.inference.prediction.document_type.value)
Line Items
line_items (List[ReceiptV5LineItem]): List of line item details.
for line_items_elem in result.document.inference.prediction.line_items:
print(line_items_elem)
Expense Locale
locale (LocaleField): The locale detected on the document.
print(result.document.inference.prediction.locale.value)
Receipt Number
receipt_number (StringField): The receipt number or identifier.
print(result.document.inference.prediction.receipt_number.value)
Purchase Subcategory
subcategory (ClassificationField): The purchase subcategory among predefined classes for transport and food.
Possible values include:
- plane
- taxi
- train
- restaurant
- shopping
print(result.document.inference.prediction.subcategory.value)
Supplier Address
supplier_address (StringField): The address of the supplier or merchant.
print(result.document.inference.prediction.supplier_address.value)
Supplier Company Registrations
supplier_company_registrations (List[CompanyRegistrationField]): List of company registrations associated to the supplier.
for supplier_company_registrations_elem in result.document.inference.prediction.supplier_company_registrations:
print(supplier_company_registrations_elem.value)
Supplier Name
supplier_name (StringField): The name of the supplier or merchant.
print(result.document.inference.prediction.supplier_name.value)
Supplier Phone Number
supplier_phone_number (StringField): The phone number of the supplier or merchant.
print(result.document.inference.prediction.supplier_phone_number.value)
Taxes
taxes (List[TaxField]): List of tax lines information.
for taxes_elem in result.document.inference.prediction.taxes:
print(taxes_elem.polygon)
Purchase Time
time (StringField): The time the purchase was made.
print(result.document.inference.prediction.time.value)
Tip and Gratuity
tip (AmountField): The total amount of tip and gratuity.
print(result.document.inference.prediction.tip.value)
Total Amount
total_amount (AmountField): The total amount paid: includes taxes, discounts, fees, tips, and gratuity.
print(result.document.inference.prediction.total_amount.value)
Total Net
total_net (AmountField): The net amount paid: does not include taxes, fees, and discounts.
print(result.document.inference.prediction.total_net.value)
Total Tax
total_tax (AmountField): The total amount of taxes.
print(result.document.inference.prediction.total_tax.value)
Questions?
Updated about 1 month ago