Multi Receipts Detector

The Python SDK supports the Mindee V1 Multi Receipts Detector API.

Product Specifications

Specification	Details
Endpoint Name	multi_receipts_detector
Recommended Version	v1.1
Supports Polling/Webhooks	❌ No
Support Synchronous HTTP Calls	✔️ Yes
Geography	🌐 Global

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.MultiReceiptsDetectorV1,
    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: d7c5b25f-e0d3-4491-af54-6183afa1aaab
:Filename: default_sample.jpg

Inference
#########
:Product: mindee/multi_receipts_detector v1.0
:Rotation applied: Yes

Prediction
==========
:List of Receipts: Polygon with 4 points.
                   Polygon with 4 points.
                   Polygon with 4 points.
                   Polygon with 4 points.
                   Polygon with 4 points.
                   Polygon with 4 points.

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

Page 0
------
:List of Receipts: Polygon with 4 points.
                   Polygon with 4 points.
                   Polygon with 4 points.
                   Polygon with 4 points.
                   Polygon with 4 points.
                   Polygon with 4 points.

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.

PositionField

The position field PositionField does not implement all the basic BaseField attributes, only bounding_box, polygon and page_id. On top of these, it has access to:

• rectangle ([Point, Point, Point, Point]): a Polygon with four points that may be oriented (even beyond canvas).

• quadrangle ([Point, Point, Point, Point]): a free polygon made up of four points.

Attributes

The following fields are extracted for Multi Receipts Detector V1:

List of Receipts

receipts (List[PositionField]): Positions of the receipts on the document.

for receipts_elem in result.document.inference.prediction.receipts:
    print(receipts_elem.polygon)