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from azure.core.credentials import AzureKeyCredential
from azure.ai.formrecognizer import DocumentAnalysisClient
from io import BytesIO
from helpers import format_polygon, Logger
import logging
import os
import sys
logging.basicConfig(filename='app.log', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
sys.stdout = Logger("output.log")
endpoint = os.environ['AZURE_API_ENDPOINT']
key = os.environ['AZURE_API_KEY']
def detect_document(content):
document_analysis_client = DocumentAnalysisClient(
endpoint=endpoint, credential=AzureKeyCredential(key)
)
with open(content.name, "rb") as f:
poller = document_analysis_client.begin_analyze_document(
"prebuilt-document", document=f
)
result = poller.result()
text_content = result.content
logging.info(result.content)
print(text_content)
pair_content = "----Key-value pairs found in document----\n"
for kv_pair in result.key_value_pairs:
if kv_pair.key and kv_pair.value:
pair_content += "Key '{}' with Value '{}' \n".format(
kv_pair.key.content,
kv_pair.value.content
)
logging.info(pair_content)
print(pair_content)
document_content = "----Lines found in document----\n"
for page in result.pages:
for line_idx, line in enumerate(page.lines):
document_content += "...Line # {} text '{}' within bounding polygon '{}' \n".format(
line_idx,
line.content,
format_polygon(line.polygon),
)
logging.info(document_content)
print(document_content)
table_content = "----Tables found in document----\n"
for table_idx, table in enumerate(result.tables):
table_content += "Table # {} has {} rows and {} columns\n".format(
table_idx, table.row_count, table.column_count
)
for cell in table.cells:
table_content += "...Cell[{}][{}] has content '{}'\n".format(
cell.row_index,
cell.column_index,
cell.content,
)
logging.info(table_content)
print(table_content)
name = content.name.split('\\')[-1]
name = name.split("/")[-1]
name = name.split('.')[0]
return (text_content, pair_content, document_content, table_content, name)
def detect_image(content):
document_analysis_client = DocumentAnalysisClient(
endpoint=endpoint, credential=AzureKeyCredential(key)
)
byte_stream = BytesIO()
content.save(byte_stream, format='PNG') # or 'JPEG', 'BMP', etc. depending on your image
byte_stream.seek(0) # reset pointer back to the start of the stream
poller = document_analysis_client.begin_analyze_document(
"prebuilt-read", document=byte_stream
)
result = poller.result()
logging.info(result.content)
print(result.content)
return(result.content)
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