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process_document_quality_sample.py
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process_document_quality_sample.py
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# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# [START documentai_process_quality_document]
from google.api_core.client_options import ClientOptions
from google.cloud import documentai
# TODO(developer): Uncomment these variables before running the sample.
# project_id = 'YOUR_PROJECT_ID'
# location = 'YOUR_PROCESSOR_LOCATION' # Format is 'us' or 'eu'
# processor_id = 'YOUR_PROCESSOR_ID' # Create processor before running sample
# file_path = '/path/to/local/pdf'
# mime_type = 'application/pdf' # Refer to https://cloud.google.com/document-ai/docs/file-types for supported file types
def process_document_quality_sample(
project_id: str, location: str, processor_id: str, file_path: str, mime_type: str
):
# Online processing request to Document AI
document = process_document(
project_id, location, processor_id, file_path, mime_type
)
# Read the quality-specific information from the output from the
# Intelligent Document Quality Processor:
# https://cloud.google.com/document-ai/docs/processors-list#processor_doc-quality-processor
# OCR and other data is also present in the quality processor's response.
# Please see the OCR and other samples for how to parse other data in the
# response.
for entity in document.entities:
conf_percent = f"{entity.confidence:.1%}"
page_num = str(int(entity.page_anchor.page_refs[0].page) + 1)
print(f"\nPage {page_num} has a quality score of {conf_percent}")
for prop in entity.properties:
conf_percent = f"{prop.confidence:.1%}"
print(f" * {prop.type_} score of {conf_percent}")
def process_document(
project_id: str, location: str, processor_id: str, file_path: str, mime_type: str
) -> documentai.Document:
# You must set the api_endpoint if you use a location other than 'us'.
opts = ClientOptions(api_endpoint=f"{location}-documentai.googleapis.com")
client = documentai.DocumentProcessorServiceClient(client_options=opts)
# The full resource name of the processor, e.g.:
# projects/project_id/locations/location/processor/processor_id
name = client.processor_path(project_id, location, processor_id)
# Read the file into memory
with open(file_path, "rb") as image:
image_content = image.read()
# Load Binary Data into Document AI RawDocument Object
raw_document = documentai.RawDocument(content=image_content, mime_type=mime_type)
# Configure the process request
request = documentai.ProcessRequest(name=name, raw_document=raw_document)
result = client.process_document(request=request)
return result.document
# [END documentai_process_quality_document]