# coding: utf-8

# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------

"""
FILE: sample_analyze_layout.py

DESCRIPTION:
    This sample demonstrates how to extract text, selection marks, and layout information from a document
    given through a file.

    Note that selection marks returned from begin_analyze_document(model_id="prebuilt-layout") do not return the text
    associated with the checkbox. For the API to return this information, build a custom model to analyze the
    checkbox and its text. See sample_build_model.py for more information.

USAGE:
    python sample_analyze_layout.py

    Set the environment variables with your own values before running the sample:
    1) AZURE_FORM_RECOGNIZER_ENDPOINT - the endpoint to your Form Recognizer resource.
    2) AZURE_FORM_RECOGNIZER_KEY - your Form Recognizer API key
"""

import os


def format_polygon(polygon):
    if not polygon:
        return "N/A"
    return ", ".join(["[{}, {}]".format(p.x, p.y) for p in polygon])


def analyze_layout():
    path_to_sample_documents = os.path.abspath(
        os.path.join(
            os.path.abspath(__file__),
            "..",
            "..",
            "./sample_forms/forms/form_selection_mark.png",
        )
    )

    from azure.core.credentials import AzureKeyCredential
    from azure.ai.formrecognizer import DocumentAnalysisClient

    endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"]
    key = os.environ["AZURE_FORM_RECOGNIZER_KEY"]

    document_analysis_client = DocumentAnalysisClient(
        endpoint=endpoint, credential=AzureKeyCredential(key)
    )
    with open(path_to_sample_documents, "rb") as f:
        poller = document_analysis_client.begin_analyze_document(
            "prebuilt-layout", document=f
        )
    result = poller.result()

    for idx, style in enumerate(result.styles):
        print(
            "Document contains {} content".format(
                "handwritten" if style.is_handwritten else "no handwritten"
            )
        )

    for page in result.pages:
        print("----Analyzing layout from page #{}----".format(page.page_number))
        print(
            "Page has width: {} and height: {}, measured with unit: {}".format(
                page.width, page.height, page.unit
            )
        )

        for line_idx, line in enumerate(page.lines):
            words = line.get_words()
            print(
                "...Line # {} has word count {} and text '{}' within bounding polygon '{}'".format(
                    line_idx,
                    len(words),
                    line.content,
                    format_polygon(line.polygon),
                )
            )

            for word in words:
                print(
                    "......Word '{}' has a confidence of {}".format(
                        word.content, word.confidence
                    )
                )

        for selection_mark in page.selection_marks:
            print(
                "...Selection mark is '{}' within bounding polygon '{}' and has a confidence of {}".format(
                    selection_mark.state,
                    format_polygon(selection_mark.polygon),
                    selection_mark.confidence,
                )
            )

    for table_idx, table in enumerate(result.tables):
        print(
            "Table # {} has {} rows and {} columns".format(
                table_idx, table.row_count, table.column_count
            )
        )
        for region in table.bounding_regions:
            print(
                "Table # {} location on page: {} is {}".format(
                    table_idx,
                    region.page_number,
                    format_polygon(region.polygon),
                )
            )
        for cell in table.cells:
            print(
                "...Cell[{}][{}] has content '{}'".format(
                    cell.row_index,
                    cell.column_index,
                    cell.content,
                )
            )
            for region in cell.bounding_regions:
                print(
                    "...content on page {} is within bounding polygon '{}'".format(
                        region.page_number,
                        format_polygon(region.polygon),
                    )
                )

    print("----------------------------------------")


if __name__ == "__main__":
    analyze_layout()
