diff --git a/sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.1/async_samples/sample_convert_to_and_from_dict_async.py b/sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.1/async_samples/sample_convert_to_and_from_dict_async.py new file mode 100644 index 000000000000..bfa32d8867e6 --- /dev/null +++ b/sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.1/async_samples/sample_convert_to_and_from_dict_async.py @@ -0,0 +1,91 @@ +# 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_convert_to_and_from_dict_async.py + +DESCRIPTION: + This sample demonstrates how to convert models returned from a recognize operation + to and from a dictionary. The dictionary in this sample is then converted to a + JSON file, then the same dictionary is converted back to its original model. + +USAGE: + python sample_convert_to_and_from_dict_async.py + + Set the environment variables with your own values before running the sample: + 1) AZURE_FORM_RECOGNIZER_ENDPOINT - the endpoint to your Cognitive Services resource. + 2) AZURE_FORM_RECOGNIZER_KEY - your Form Recognizer API key +""" + +import os +import json +import asyncio + +async def convert_to_and_from_dict_async(): + path_to_sample_forms = os.path.abspath( + os.path.join( + os.path.abspath(__file__), + "..", + "..", + "..", + "./sample_forms/id_documents/license.jpg", + ) + ) + + from azure.core.serialization import AzureJSONEncoder + from azure.core.credentials import AzureKeyCredential + from azure.ai.formrecognizer.aio import FormRecognizerClient + from azure.ai.formrecognizer import RecognizedForm + + endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"] + key = os.environ["AZURE_FORM_RECOGNIZER_KEY"] + + form_recognizer_client = FormRecognizerClient( + endpoint=endpoint, credential=AzureKeyCredential(key) + ) + async with form_recognizer_client: + with open(path_to_sample_forms, "rb") as f: + poller = await form_recognizer_client.begin_recognize_identity_documents(identity_document=f) + + id_documents = await poller.result() + + # convert the received model to a dictionary + recognized_form_dict = [doc.to_dict() for doc in id_documents] + + # save the dictionary as JSON content in a JSON file, use the AzureJSONEncoder + # to help make types, such as dates, JSON serializable + # NOTE: AzureJSONEncoder is only available with azure.core>=1.18.0. + with open('data.json', 'w') as f: + json.dump(recognized_form_dict, f, cls=AzureJSONEncoder) + + # convert the dictionary back to the original model + model = [RecognizedForm.from_dict(doc) for doc in recognized_form_dict] + + # use the model as normal + for idx, id_document in enumerate(model): + print("--------Recognizing converted ID document #{}--------".format(idx+1)) + first_name = id_document.fields.get("FirstName") + if first_name: + print("First Name: {} has confidence: {}".format(first_name.value, first_name.confidence)) + last_name = id_document.fields.get("LastName") + if last_name: + print("Last Name: {} has confidence: {}".format(last_name.value, last_name.confidence)) + document_number = id_document.fields.get("DocumentNumber") + if document_number: + print("Document Number: {} has confidence: {}".format(document_number.value, document_number.confidence)) + + print("----------------------------------------") + + +async def main(): + await convert_to_and_from_dict_async() + + +if __name__ == '__main__': + loop = asyncio.get_event_loop() + loop.run_until_complete(main()) diff --git a/sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.1/sample_convert_to_and_from_dict.py b/sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.1/sample_convert_to_and_from_dict.py new file mode 100644 index 000000000000..b0822db84ebe --- /dev/null +++ b/sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.1/sample_convert_to_and_from_dict.py @@ -0,0 +1,82 @@ +# 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_convert_to_and_from_dict.py + +DESCRIPTION: + This sample demonstrates how to convert models returned from an analyze operation + to and from a dictionary. The dictionary in this sample is then converted to a + JSON file, then the same dictionary is converted back to its original model. + +USAGE: + python sample_convert_to_and_from_dict.py + + Set the environment variables with your own values before running the sample: + 1) AZURE_FORM_RECOGNIZER_ENDPOINT - the endpoint to your Cognitive Services resource. + 2) AZURE_FORM_RECOGNIZER_KEY - your Form Recognizer API key +""" + +import os +import json + +def convert_to_and_from_dict(): + path_to_sample_forms = os.path.abspath( + os.path.join( + os.path.abspath(__file__), + "..", + "..", + "./sample_forms/id_documents/license.jpg", + ) + ) + + from azure.core.serialization import AzureJSONEncoder + from azure.core.credentials import AzureKeyCredential + from azure.ai.formrecognizer import FormRecognizerClient, RecognizedForm + + endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"] + key = os.environ["AZURE_FORM_RECOGNIZER_KEY"] + + form_recognizer_client = FormRecognizerClient( + endpoint=endpoint, credential=AzureKeyCredential(key) + ) + with open(path_to_sample_forms, "rb") as f: + poller = form_recognizer_client.begin_recognize_identity_documents(identity_document=f) + + id_documents = poller.result() + + # convert the received model to a dictionary + recognized_form_dict = [doc.to_dict() for doc in id_documents] + + # save the dictionary as JSON content in a JSON file, use the AzureJSONEncoder + # to help make types, such as dates, JSON serializable + # NOTE: AzureJSONEncoder is only available with azure.core>=1.18.0. + with open('data.json', 'w') as f: + json.dump(recognized_form_dict, f, cls=AzureJSONEncoder) + + # convert the dictionary back to the original model + model = [RecognizedForm.from_dict(doc) for doc in recognized_form_dict] + + # use the model as normal + for idx, id_document in enumerate(model): + print("--------Recognizing converted ID document #{}--------".format(idx+1)) + first_name = id_document.fields.get("FirstName") + if first_name: + print("First Name: {} has confidence: {}".format(first_name.value, first_name.confidence)) + last_name = id_document.fields.get("LastName") + if last_name: + print("Last Name: {} has confidence: {}".format(last_name.value, last_name.confidence)) + document_number = id_document.fields.get("DocumentNumber") + if document_number: + print("Document Number: {} has confidence: {}".format(document_number.value, document_number.confidence)) + + print("----------------------------------------") + + +if __name__ == "__main__": + convert_to_and_from_dict() diff --git a/sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.2-beta/async_samples/sample_convert_to_and_from_dict_async.py b/sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.2-beta/async_samples/sample_convert_to_and_from_dict_async.py new file mode 100644 index 000000000000..700963ee8a9b --- /dev/null +++ b/sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.2-beta/async_samples/sample_convert_to_and_from_dict_async.py @@ -0,0 +1,85 @@ +# 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_convert_to_and_from_dict_async.py + +DESCRIPTION: + This sample demonstrates how to convert models returned from an analyze operation + to and from a dictionary. The dictionary in this sample is then converted to a + JSON file, then the same dictionary is converted back to its original model. + +USAGE: + python sample_convert_to_and_from_dict_async.py + + Set the environment variables with your own values before running the sample: + 1) AZURE_FORM_RECOGNIZER_ENDPOINT - the endpoint to your Cognitive Services resource. + 2) AZURE_FORM_RECOGNIZER_KEY - your Form Recognizer API key +""" + +import os +import json +import asyncio + +async def convert_to_and_from_dict_async(): + path_to_sample_documents = os.path.abspath( + os.path.join( + os.path.abspath(__file__), + "..", + "..", + "..", + "./sample_forms/forms/Form_1.jpg", + ) + ) + + from azure.core.serialization import AzureJSONEncoder + from azure.core.credentials import AzureKeyCredential + from azure.ai.formrecognizer.aio import DocumentAnalysisClient + from azure.ai.formrecognizer import AnalyzeResult + + endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"] + key = os.environ["AZURE_FORM_RECOGNIZER_KEY"] + + document_analysis_client = DocumentAnalysisClient( + endpoint=endpoint, credential=AzureKeyCredential(key) + ) + async with document_analysis_client: + with open(path_to_sample_documents, "rb") as f: + poller = await document_analysis_client.begin_analyze_document( + "prebuilt-document", document=f + ) + result = await poller.result() + + # convert the received model to a dictionary + analyze_result_dict = result.to_dict() + + # save the dictionary as JSON content in a JSON file, use the AzureJSONEncoder + # to help make types, such as dates, JSON serializable + # NOTE: AzureJSONEncoder is only available with azure.core>=1.18.0. + with open('data.json', 'w') as f: + json.dump(analyze_result_dict, f, cls=AzureJSONEncoder) + + # convert the dictionary back to the original model + model = AnalyzeResult.from_dict(analyze_result_dict) + + # use the model as normal + print("----Converted from dictionary AnalyzeResult----") + print("Model ID: '{}'".format(model.model_id)) + print("Number of pages analyzed {}".format(len(model.pages))) + print("API version used: {}".format(model.api_version)) + + print("----------------------------------------") + + +async def main(): + await convert_to_and_from_dict_async() + + +if __name__ == '__main__': + loop = asyncio.get_event_loop() + loop.run_until_complete(main()) diff --git a/sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.2-beta/sample_convert_to_and_from_dict.py b/sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.2-beta/sample_convert_to_and_from_dict.py new file mode 100644 index 000000000000..b80ea63b79c5 --- /dev/null +++ b/sdk/formrecognizer/azure-ai-formrecognizer/samples/v3.2-beta/sample_convert_to_and_from_dict.py @@ -0,0 +1,76 @@ +# 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_convert_to_and_from_dict.py + +DESCRIPTION: + This sample demonstrates how to convert models returned from an analyze operation + to and from a dictionary. The dictionary in this sample is then converted to a + JSON file, then the same dictionary is converted back to its original model. + +USAGE: + python sample_convert_to_and_from_dict.py + + Set the environment variables with your own values before running the sample: + 1) AZURE_FORM_RECOGNIZER_ENDPOINT - the endpoint to your Cognitive Services resource. + 2) AZURE_FORM_RECOGNIZER_KEY - your Form Recognizer API key +""" + +import os +import json + +def convert_to_and_from_dict(): + path_to_sample_documents = os.path.abspath( + os.path.join( + os.path.abspath(__file__), + "..", + "..", + "./sample_forms/forms/Form_1.jpg", + ) + ) + + from azure.core.serialization import AzureJSONEncoder + from azure.core.credentials import AzureKeyCredential + from azure.ai.formrecognizer import DocumentAnalysisClient, AnalyzeResult + + 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-document", document=f + ) + result = poller.result() + + # convert the received model to a dictionary + analyze_result_dict = result.to_dict() + + # save the dictionary as JSON content in a JSON file, use the AzureJSONEncoder + # to help make types, such as dates, JSON serializable + # NOTE: AzureJSONEncoder is only available with azure.core>=1.18.0. + with open('data.json', 'w') as f: + json.dump(analyze_result_dict, f, cls=AzureJSONEncoder) + + # convert the dictionary back to the original model + model = AnalyzeResult.from_dict(analyze_result_dict) + + # use the model as normal + print("----Converted from dictionary AnalyzeResult----") + print("Model ID: '{}'".format(model.model_id)) + print("Number of pages analyzed {}".format(len(model.pages))) + print("API version used: {}".format(model.api_version)) + + print("----------------------------------------") + + +if __name__ == "__main__": + convert_to_and_from_dict()