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# 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_addon_fonts.py
DESCRIPTION:
This sample demonstrates how to extract font information using the add-on
'STYLE_FONT' capability.
This sample uses Layout model to demonstrate.
Add-on capabilities accept a list of strings containing values from the `DocumentAnalysisFeature`
enum class. For more information, see:
https://aka.ms/azsdk/python/documentintelligence/analysisfeature.
The following capabilities are free:
- BARCODES
- LANGUAGES
The following capabilities will incur additional charges:
- FORMULAS
- OCR_HIGH_RESOLUTION
- STYLE_FONT
- QUERY_FIELDS
See pricing: https://azure.microsoft.com/pricing/details/ai-document-intelligence/.
USAGE:
python sample_analyze_addon_fonts.py
Set the environment variables with your own values before running the sample:
1) DOCUMENTINTELLIGENCE_ENDPOINT - the endpoint to your Document Intelligence resource.
2) DOCUMENTINTELLIGENCE_API_KEY - your Document Intelligence API key.
"""
import os
from collections import defaultdict
def analyze_fonts():
path_to_sample_documents = os.path.abspath(
os.path.join(
os.path.abspath(__file__),
"..",
"sample_forms/add_ons/fonts_and_languages.png",
)
)
# [START analyze_fonts]
from azure.core.credentials import AzureKeyCredential
from azure.ai.documentintelligence import DocumentIntelligenceClient
from azure.ai.documentintelligence.models import DocumentAnalysisFeature, AnalyzeResult
def _get_styled_text(styles, content):
# Iterate over the styles and merge the spans from each style.
spans = [span for style in styles for span in style.spans]
spans.sort(key=lambda span: span.offset)
return ",".join([content[span.offset : span.offset + span.length] for span in spans])
endpoint = os.environ["DOCUMENTINTELLIGENCE_ENDPOINT"]
key = os.environ["DOCUMENTINTELLIGENCE_API_KEY"]
document_intelligence_client = DocumentIntelligenceClient(endpoint=endpoint, credential=AzureKeyCredential(key))
# Specify which add-on capabilities to enable.
with open(path_to_sample_documents, "rb") as f:
poller = document_intelligence_client.begin_analyze_document(
"prebuilt-layout",
body=f,
features=[DocumentAnalysisFeature.STYLE_FONT],
)
result: AnalyzeResult = poller.result()
# DocumentStyle has the following font related attributes:
similar_font_families = defaultdict(list) # e.g., 'Arial, sans-serif
font_styles = defaultdict(list) # e.g, 'italic'
font_weights = defaultdict(list) # e.g., 'bold'
font_colors = defaultdict(list) # in '#rrggbb' hexadecimal format
font_background_colors = defaultdict(list) # in '#rrggbb' hexadecimal format
if result.styles and any([style.is_handwritten for style in result.styles]):
print("Document contains handwritten content")
else:
print("Document does not contain handwritten content")
return
print("\n----Fonts styles detected in the document----")
# Iterate over the styles and group them by their font attributes.
for style in result.styles:
if style.similar_font_family:
similar_font_families[style.similar_font_family].append(style)
if style.font_style:
font_styles[style.font_style].append(style)
if style.font_weight:
font_weights[style.font_weight].append(style)
if style.color:
font_colors[style.color].append(style)
if style.background_color:
font_background_colors[style.background_color].append(style)
print(f"Detected {len(similar_font_families)} font families:")
for font_family, styles in similar_font_families.items():
print(f"- Font family: '{font_family}'")
print(f" Text: '{_get_styled_text(styles, result.content)}'")
print(f"\nDetected {len(font_styles)} font styles:")
for font_style, styles in font_styles.items():
print(f"- Font style: '{font_style}'")
print(f" Text: '{_get_styled_text(styles, result.content)}'")
print(f"\nDetected {len(font_weights)} font weights:")
for font_weight, styles in font_weights.items():
print(f"- Font weight: '{font_weight}'")
print(f" Text: '{_get_styled_text(styles, result.content)}'")
print(f"\nDetected {len(font_colors)} font colors:")
for font_color, styles in font_colors.items():
print(f"- Font color: '{font_color}'")
print(f" Text: '{_get_styled_text(styles, result.content)}'")
print(f"\nDetected {len(font_background_colors)} font background colors:")
for font_background_color, styles in font_background_colors.items():
print(f"- Font background color: '{font_background_color}'")
print(f" Text: '{_get_styled_text(styles, result.content)}'")
print("----------------------------------------")
# [END analyze_fonts]
if __name__ == "__main__":
from azure.core.exceptions import HttpResponseError
from dotenv import find_dotenv, load_dotenv
try:
load_dotenv(find_dotenv())
analyze_fonts()
except HttpResponseError as error:
# Examples of how to check an HttpResponseError
# Check by error code:
if error.error is not None:
if error.error.code == "InvalidImage":
print(f"Received an invalid image error: {error.error}")
if error.error.code == "InvalidRequest":
print(f"Received an invalid request error: {error.error}")
# Raise the error again after printing it
raise
# If the inner error is None and then it is possible to check the message to get more information:
if "Invalid request".casefold() in error.message.casefold():
print(f"Uh-oh! Seems there was an invalid request: {error}")
# Raise the error again
raise
|
