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invoice_splitter_v1.md

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100 lines (76 loc) · 3.92 KB
title Invoice Splitter OCR Python
category 622b805aaec68102ea7fcbc2
slug python-invoice-splitter-ocr
parentDoc 609808f773b0b90051d839de

The Python OCR SDK supports the Invoice Splitter API.

Using the sample below, we are going to illustrate how to extract the data that we want using the OCR SDK. Invoice Splitter sample

Quick-Start

from mindee import Client, product, AsyncPredictResponse

# 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 enqueue it.
result: AsyncPredictResponse = mindee_client.enqueue_and_parse(
    product.InvoiceSplitterV1,
    input_doc,
)

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

Output (RST):

########
Document
########
:Mindee ID: 15ad7a19-7b75-43d0-b0c6-9a641a12b49b
:Filename: default_sample.pdf

Inference
#########
:Product: mindee/invoice_splitter v1.2
:Rotation applied: No

Prediction
==========
:Invoice Page Groups:
  +--------------------------------------------------------------------------+
  | Page Indexes                                                             |
  +==========================================================================+
  | 0                                                                        |
  +--------------------------------------------------------------------------+
  | 1                                                                        |
  +--------------------------------------------------------------------------+

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 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).

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.

Specific Fields

Fields which are specific to this product; they are not used in any other product.

Invoice Page Groups Field

List of page groups. Each group represents a single invoice within a multi-invoice document.

A InvoiceSplitterV1InvoicePageGroup implements the following attributes:

  • page_indexes (List[int]): List of page indexes that belong to the same invoice (group).

Attributes

The following fields are extracted for Invoice Splitter V1:

Invoice Page Groups

invoice_page_groups (List[InvoiceSplitterV1InvoicePageGroup]): List of page groups. Each group represents a single invoice within a multi-invoice document.

for invoice_page_groups_elem in result.document.inference.prediction.invoice_page_groups:
    print(invoice_page_groups_elem.value)

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