Metadata-Version: 2.1
Name: azure-ai-formrecognizer
Version: 1.0.0b3
Summary: Microsoft Azure Form Recognizer Client Library for Python
Home-page: https://github.com/Azure/azure-sdk-for-python
Author: Microsoft Corporation
Author-email: azpysdkhelp@microsoft.com
License: MIT License
Description: # Azure Form Recognizer client library for Python
        
        Azure Cognitive Services Form Recognizer is a cloud service that uses machine learning to recognize text and table data
        from form documents. It includes the following main functionalities:
        
        * Custom models - Recognize field values and table data from forms. These models are trained with your own data, so they're tailored to your forms. You can then take these custom models and recognize forms. You can also manage the custom models you've created and see how close you are to the limit of custom models your account can hold.
        * Content API - Recognize text and table structures, along with their bounding box coordinates, from documents. Corresponds to the REST service's Layout API.
        * Prebuilt receipt model - Recognize data from USA sales receipts using a prebuilt model.
        
        [Source code][python-fr-src] | [Package (PyPI)][python-fr-pypi] | [API reference documentation][python-fr-ref-docs]| [Product documentation][python-fr-product-docs] | [Samples][python-fr-samples]
        
        ## Getting started
        
        ### Prerequisites
        * Python 2.7, or 3.5 or later is required to use this package.
        * You must have an [Azure subscription][azure_subscription] and a
        [Cognitive Services or Form Recognizer resource][FR_or_CS_resource] to use this package.
        
        ### Install the package
        Install the Azure Form Recognizer client library for Python with [pip][pip]:
        
        ```bash
        pip install azure-ai-formrecognizer
        ```
        
        > Note: This version of the client library supports the v2.0-preview version of the Form Recognizer service
        
        #### Create a Form Recognizer resource
        Form Recognizer supports both [multi-service and single-service access][multi_and_single_service].
        Create a Cognitive Services resource if you plan to access multiple cognitive services under a single endpoint/key. For Form Recognizer access only, create a Form Recognizer resource.
        
        You can create the resource using
        
        **Option 1:** [Azure Portal][azure_portal_create_FR_resource]
        
        **Option 2:** [Azure CLI][azure_cli_create_FR_resource].
        Below is an example of how you can create a Form Recognizer resource using the CLI:
        
        ```bash
        # Create a new resource group to hold the form recognizer resource -
        # if using an existing resource group, skip this step
        az group create --name my-resource-group --location westus2
        ```
        
        ```bash
        # Create form recognizer
        az cognitiveservices account create \
            --name form-recognizer-resource \
            --resource-group my-resource-group \
            --kind FormRecognizer \
            --sku F0 \
            --location westus2 \
            --yes
        ```
        
        ### Authenticate the client
        
        #### Looking up the endpoint
        You can find the endpoint for your form recognizer resource using the
        [Azure Portal][azure_portal_get_endpoint]
        or [Azure CLI][azure_cli_endpoint_lookup]:
        
        ```bash
        # Get the endpoint for the form recognizer resource
        az cognitiveservices account show --name "resource-name" --resource-group "resource-group-name" --query "endpoint"
        ```
        
        #### Types of credentials
        The `credential` parameter may be provided as a [AzureKeyCredential][azure-key-credential] from [azure.core][azure_core],
        or as a credential type from Azure Active Directory.
        See the full details regarding [authentication][cognitive_authentication] of cognitive services.
        
        1.  To use an [API key][cognitive_authentication_api_key],
            pass the key as a string into an instance of `AzureKeyCredential("<api_key>")`.
            The API key can be found in the Azure Portal or by running the following Azure CLI command:
        
            ```az cognitiveservices account keys list --name "resource-name" --resource-group "resource-group-name"```
        
            Use the key as the credential parameter to authenticate the client:
            ```python
            from azure.ai.formrecognizer import FormRecognizerClient
            from azure.core.credentials import AzureKeyCredential
        
            endpoint = "https://<region>.api.cognitive.microsoft.com/"
            credential = AzureKeyCredential("<api_key>")
            form_recognizer_client = FormRecognizerClient(endpoint, credential)
            ```
        
        2. To use an [Azure Active Directory (AAD) token credential][cognitive_authentication_aad],
           provide an instance of the desired credential type obtained from the
           [azure-identity][azure_identity_credentials] library.
           Note that regional endpoints do not support AAD authentication. Create a [custom subdomain][custom_subdomain]
           name for your resource in order to use this type of authentication.
        
           Authentication with AAD requires some initial setup:
           * [Install azure-identity][install_azure_identity]
           * [Register a new AAD application][register_aad_app]
           * [Grant access][grant_role_access] to Form Recognizer by assigning the `"Cognitive Services User"` role to your service principal.
        
           After setup, you can choose which type of [credential][azure_identity_credentials] from azure.identity to use.
           As an example, [DefaultAzureCredential][default_azure_credential]
           can be used to authenticate the client:
        
           Set the values of the client ID, tenant ID, and client secret of the AAD application as environment variables:
           AZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET
        
           Use the returned token credential to authenticate the client:
            ```python
            from azure.identity import DefaultAzureCredential
            from azure.ai.formrecognizer import FormRecognizerClient
            token_credential = DefaultAzureCredential()
        
            form_recognizer_client = FormRecognizerClient(
                endpoint="https://<my-custom-subdomain>.cognitiveservices.azure.com/",
                credential=token_credential
            )
            ```
        
        ## Key concepts
        
        ### FormRecognizerClient
        `FormRecognizerClient` provides operations for:
        
         - Recognizing form fields and content using custom models trained to recognize your custom forms. These values are returned in a collection of `RecognizedForm` objects.
         - Recognizing form content, including tables, lines and words, without the need to train a model. Form content is returned in a collection of `FormPage` objects.
         - Recognizing common fields from US receipts, using a pre-trained receipt model on the Form Recognizer service. These fields and meta-data are returned in a collection of `RecognizedReceipt` objects.
        
        ### FormTrainingClient
        `FormTrainingClient` provides operations for:
        
        - Training custom models to recognize all fields and values found in your custom forms. A `CustomFormModel` is returned indicating the form types the model will recognize, and the fields it will extract for each form type. See the [service's documents][fr-train-without-labels] for a more detailed explanation.
        - Training custom models to recognize specific fields and values you specify by labeling your custom forms. A `CustomFormModel` is returned indicating the fields the model will extract, as well as the estimated accuracy for each field. See the [service's documents][fr-train-with-labels] for a more detailed explanation.
        - Managing models created in your account.
        - Copying a custom model from one Form Recognizer resource to another.
        
        Please note that models can also be trained using a graphical user interface such as the [Form Recognizer Labeling Tool][fr-labeling-tool].
        
        ### Long-Running Operations
        Long-running operations are operations which consist of an initial request sent to the service to start an operation,
        followed by polling the service at intervals to determine whether the operation has completed or failed, and if it has
        succeeded, to get the result.
        
        Methods that train models, recognize values from forms, or copy models are modeled as long-running operations. 
        The client exposes a `begin_<method-name>` method that returns an `LROPoller` or `AsyncLROPoller`. Callers should wait 
        for the operation to complete by calling `result()` on the operation returned from the `begin_<method-name>` method. 
        Sample code snippets are provided to illustrate using long-running operations [below](#examples "Examples").
        
        
        ## Examples
        
        The following section provides several code snippets covering some of the most common Form Recognizer tasks, including:
        
        * [Recognize Forms Using a Custom Model](#recognize-forms-using-a-custom-model "Recognize Forms Using a Custom Model")
        * [Recognize Content](#recognize-content "Recognize Content")
        * [Recognize Receipts](#recognize-receipts "Recognize receipts")
        * [Train a Model](#train-a-model "Train a model")
        * [Manage Your Models](#manage-your-models "Manage Your Models")
        
        ### Recognize Forms Using a Custom Model
        Recognize name/value pairs and table data from forms. These models are trained with your own data, so they're tailored to your forms. You should only recognize forms of the same form type that the custom model was trained on.
        
        ```python
        from azure.ai.formrecognizer import FormRecognizerClient
        from azure.core.credentials import AzureKeyCredential
        
        endpoint = "https://<region>.api.cognitive.microsoft.com/"
        credential = AzureKeyCredential("<api_key>")
        
        form_recognizer_client = FormRecognizerClient(endpoint, credential)
        model_id = "<your custom model id>"
        
        # Make sure the form type is one of the types of forms your custom model can recognize
        with open("<path to your form>", "rb") as fd:
            form = fd.read()
        
        poller = form_recognizer_client.begin_recognize_custom_forms(model_id=model_id, form=form)
        result = poller.result()
        
        for recognized_form in result:
            print("Form type ID: {}".format(recognized_form.form_type))
            for label, field in recognized_form.fields.items():
                print("Field '{}' has value '{}' with a confidence score of {}".format(
                    label, field.value, field.confidence
                ))
        ```
        
        ### Recognize Content
        Recognize text and table structures, along with their bounding box coordinates, from documents.
        
        ```python
        from azure.ai.formrecognizer import FormRecognizerClient
        from azure.core.credentials import AzureKeyCredential
        
        endpoint = "https://<region>.api.cognitive.microsoft.com/"
        credential = AzureKeyCredential("<api_key>")
        
        form_recognizer_client = FormRecognizerClient(endpoint, credential)
        
        with open("<path to your form>", "rb") as fd:
            form = fd.read()
        
        poller = form_recognizer_client.begin_recognize_content(form)
        page = poller.result()
        
        table = page[0].tables[0] # page 1, table 1
        for cell in table.cells:
            print(cell.text)
            print(cell.bounding_box)
            print(cell.confidence)
        ```
        
        ### Recognize Receipts
        Recognize data from USA sales receipts using a prebuilt model. [Here][service_recognize_receipt] are the fields the service returns for a recognized receipt.
        
        ```python
        from azure.ai.formrecognizer import FormRecognizerClient
        from azure.core.credentials import AzureKeyCredential
        
        endpoint = "https://<region>.api.cognitive.microsoft.com/"
        credential = AzureKeyCredential("<api_key>")
        
        form_recognizer_client = FormRecognizerClient(endpoint, credential)
        
        with open("<path to your receipt>", "rb") as fd:
            receipt = fd.read()
        
        poller = form_recognizer_client.begin_recognize_receipts(receipt)
        result = poller.result()
        
        for receipt in result:
            for name, field in receipt.fields.items():
                if name == "Items":
                    print("Receipt Items:")
                    for idx, items in enumerate(field.value):
                        print("...Item #{}".format(idx))
                        for item_name, item in items.value.items():
                            print("......{}: {} has confidence {}".format(item_name, item.value, item.confidence))
                else:
                    print("{}: {} has confidence {}".format(name, field.value, field.confidence))
        ```
        
        ### Train a model
        Train a machine-learned model on your own form type. The resulting model will be able to recognize values from the types of forms it was trained on.
        Provide a container SAS url to your Azure Storage Blob container where you're storing the training documents. See details on setting this up
        in the [service quickstart documentation][quickstart_training].
        
        ```python
        from azure.ai.formrecognizer import FormTrainingClient
        from azure.core.credentials import AzureKeyCredential
        
        endpoint = "https://<region>.api.cognitive.microsoft.com/"
        credential = AzureKeyCredential("<api_key>")
        
        form_training_client = FormTrainingClient(endpoint, credential)
        
        container_sas_url = "xxx"  # training documents uploaded to blob storage
        poller = form_training_client.begin_training(container_sas_url)
        model = poller.result()
        
        # Custom model information
        print("Model ID: {}".format(model.model_id))
        print("Status: {}".format(model.status))
        print("Requested on: {}".format(model.requested_on))
        print("Completed on: {}".format(model.completed_on))
        
        print("Recognized fields:")
        # looping through the submodels, which contains the fields they were trained on
        for submodel in model.submodels:
            print("The submodel with form type '{}' has recognized the following fields: {}".format(
                submodel.form_type,
                ", ".join([label for label in submodel.fields])
            ))
        
        # Training result information
        for doc in model.training_documents:
            print("Document name: {}".format(doc.document_name))
            print("Document status: {}".format(doc.status))
            print("Document page count: {}".format(doc.page_count))
            print("Document errors: {}".format(doc.errors))
        ```
        
        ### Manage Your Models
        Manage the custom models attached to your account.
        
        ```python
        from azure.ai.formrecognizer import FormTrainingClient
        from azure.core.credentials import AzureKeyCredential
        from azure.core.exceptions import ResourceNotFoundError
        
        endpoint = "https://<region>.api.cognitive.microsoft.com/"
        credential = AzureKeyCredential("<api_key>")
        
        form_training_client = FormTrainingClient(endpoint, credential)
        
        account_properties = form_training_client.get_account_properties()
        print("Our account has {} custom models, and we can have at most {} custom models".format(
            account_properties.custom_model_count, account_properties.custom_model_limit
        ))
        
        # Here we get a paged list of all of our custom models
        custom_models = form_training_client.list_custom_models()
        print("We have models with the following ids: {}".format(
            ", ".join([m.model_id for m in custom_models])
        ))
        
        # Now we get the custom model from the "Train a model" sample
        model_id = "<model id from the Train a Model sample>"
        
        custom_model = form_training_client.get_custom_model(model_id=model_id)
        print("Model ID: {}".format(custom_model.model_id))
        print("Status: {}".format(custom_model.status))
        print("Requested on: {}".format(custom_model.requested_on))
        print("Completed on: {}".format(custom_model.completed_on))
        
        # Finally, we will delete this model by ID
        form_training_client.delete_model(model_id=custom_model.model_id)
        
        try:
            form_training_client.get_custom_model(model_id=custom_model.model_id)
        except ResourceNotFoundError:
            print("Successfully deleted model with id {}".format(custom_model.model_id))
        ```
        
        ## Optional Configuration
        
        Optional keyword arguments can be passed in at the client and per-operation level.
        The azure-core [reference documentation][azure_core_ref_docs]
        describes available configurations for retries, logging, transport protocols, and more.
        
        ## Troubleshooting
        
        ### General
        Form Recognizer client library will raise exceptions defined in [Azure Core][azure_core_ref_docs].
        
        ### Logging
        This library uses the standard
        [logging][python_logging] library for logging.
        Basic information about HTTP sessions (URLs, headers, etc.) is logged at INFO
        level.
        
        Detailed DEBUG level logging, including request/response bodies and unredacted
        headers, can be enabled on a client with the `logging_enable` keyword argument:
        ```python
        import sys
        import logging
        from azure.ai.formrecognizer import FormRecognizerClient
        from azure.core.credentials import AzureKeyCredential
        
        # Create a logger for the 'azure' SDK
        logger = logging.getLogger('azure')
        logger.setLevel(logging.DEBUG)
        
        # Configure a console output
        handler = logging.StreamHandler(stream=sys.stdout)
        logger.addHandler(handler)
        
        endpoint = "https://<my-custom-subdomain>.cognitiveservices.azure.com/"
        credential = AzureKeyCredential("<api_key>")
        
        # This client will log detailed information about its HTTP sessions, at DEBUG level
        form_recognizer_client = FormRecognizerClient(endpoint, credential, logging_enable=True)
        ```
        
        Similarly, `logging_enable` can enable detailed logging for a single operation,
        even when it isn't enabled for the client:
        ```python
        poller = form_recognizer_client.begin_recognize_receipts(receipt, logging_enable=True)
        ```
        
        ## Next steps
        
        The following section provides several code snippets illustrating common patterns used in the Form Recognizer Python API.
        
        ### More sample code
        
        These code samples show common scenario operations with the Azure Form Recognizer client library.
        The async versions of the samples (the python sample files appended with `_async`) show asynchronous operations
        with Form Recognizer and require Python 3.5 or later.
        
        * Client authentication: [sample_authentication.py][sample_authentication] ([async_version][sample_authentication_async])
        * Recognize receipts: [sample_recognize_receipts.py][sample_recognize_receipts] ([async version][sample_recognize_receipts_async])
        * Recognize receipts from a URL: [sample_recognize_receipts_from_url.py][sample_recognize_receipts_from_url] ([async version][sample_recognize_receipts_from_url_async])
        * Recognize content: [sample_recognize_content.py][sample_recognize_content] ([async version][sample_recognize_content_async])
        * Recognize custom forms: [sample_recognize_custom_forms.py][sample_recognize_custom_forms] ([async version][sample_recognize_custom_forms_async])
        * Train a model without labels: [sample_train_model_without_labels.py][sample_train_model_without_labels] ([async version][sample_train_model_without_labels_async])
        * Train a model with labels: [sample_train_model_with_labels.py][sample_train_model_with_labels] ([async version][sample_train_model_with_labels_async])
        * Manage custom models: [sample_manage_custom_models.py][sample_manage_custom_models] ([async_version][sample_manage_custom_models_async])
        * Copy a model between Form Recognizer resources: [sample_copy_model.py][sample_copy_model] ([async_version][sample_copy_model_async])
        
        ### Additional documentation
        
        For more extensive documentation on Azure Cognitive Services Form Recognizer, see the [Form Recognizer documentation][python-fr-product-docs] on docs.microsoft.com.
        
        ## Contributing
        This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit [cla.microsoft.com][cla].
        
        When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
        
        This project has adopted the [Microsoft Open Source Code of Conduct][code_of_conduct]. For more information see the [Code of Conduct FAQ][coc_faq] or contact [opencode@microsoft.com][coc_contact] with any additional questions or comments.
        
        <!-- LINKS -->
        
        [python-fr-src]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/azure/ai/formrecognizer
        [python-fr-pypi]: https://pypi.org/project/azure-ai-formrecognizer/
        [python-fr-product-docs]: https://docs.microsoft.com/azure/cognitive-services/form-recognizer/overview
        [python-fr-ref-docs]: https://aka.ms/azsdk-python-formrecognizer-ref-docs
        [python-fr-samples]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples
        
        
        [quickstart_training]: https://docs.microsoft.com/azure/cognitive-services/form-recognizer/quickstarts/curl-train-extract#train-a-form-recognizer-model
        [azure_subscription]: https://azure.microsoft.com/free/
        [FR_or_CS_resource]: https://docs.microsoft.com/azure/cognitive-services/cognitive-services-apis-create-account?tabs=multiservice%2Cwindows
        [pip]: https://pypi.org/project/pip/
        [azure_portal_create_FR_resource]: https://ms.portal.azure.com/#create/Microsoft.CognitiveServicesFormRecognizer
        [azure_cli_create_FR_resource]: https://docs.microsoft.com/azure/cognitive-services/cognitive-services-apis-create-account-cli?tabs=windows
        [azure-key-credential]: https://aka.ms/azsdk-python-core-azurekeycredential
        [fr-labeling-tool]: https://docs.microsoft.com/azure/cognitive-services/form-recognizer/quickstarts/label-tool
        [fr-train-without-labels]: https://docs.microsoft.com/azure/cognitive-services/form-recognizer/overview#train-without-labels
        [fr-train-with-labels]: https://docs.microsoft.com/azure/cognitive-services/form-recognizer/overview#train-with-labels
        
        [azure_core]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/core/azure-core/README.md
        [azure_core_ref_docs]: https://aka.ms/azsdk-python-azure-core
        [python_logging]: https://docs.python.org/3/library/logging.html
        [multi_and_single_service]: https://docs.microsoft.com/azure/cognitive-services/cognitive-services-apis-create-account?tabs=multiservice%2Cwindows
        [azure_cli_endpoint_lookup]: https://docs.microsoft.com/cli/azure/cognitiveservices/account?view=azure-cli-latest#az-cognitiveservices-account-show
        [azure_portal_get_endpoint]: https://docs.microsoft.com/azure/cognitive-services/cognitive-services-apis-create-account?tabs=multiservice%2Cwindows#get-the-keys-for-your-resource
        [cognitive_authentication]: https://docs.microsoft.com/azure/cognitive-services/authentication
        [cognitive_authentication_api_key]: https://docs.microsoft.com/azure/cognitive-services/cognitive-services-apis-create-account?tabs=multiservice%2Cwindows#get-the-keys-for-your-resource
        [install_azure_identity]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/identity/azure-identity#install-the-package
        [register_aad_app]: https://docs.microsoft.com/azure/cognitive-services/authentication#assign-a-role-to-a-service-principal
        [grant_role_access]: https://docs.microsoft.com/azure/cognitive-services/authentication#assign-a-role-to-a-service-principal
        [cognitive_custom_subdomain]: https://docs.microsoft.com/azure/cognitive-services/cognitive-services-custom-subdomains
        [custom_subdomain]: https://docs.microsoft.com/azure/cognitive-services/authentication#create-a-resource-with-a-custom-subdomain
        [cognitive_authentication_aad]: https://docs.microsoft.com/azure/cognitive-services/authentication#authenticate-with-azure-active-directory
        [azure_identity_credentials]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/identity/azure-identity#credentials
        [default_azure_credential]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/identity/azure-identity#defaultazurecredential
        [service_recognize_receipt]: https://westus2.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v2-preview/operations/GetAnalyzeReceiptResult
        
        [cla]: https://cla.microsoft.com
        [code_of_conduct]: https://opensource.microsoft.com/codeofconduct/
        [coc_faq]: https://opensource.microsoft.com/codeofconduct/faq/
        [coc_contact]: mailto:opencode@microsoft.com
        
        [sample_authentication]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_authentication.py
        [sample_authentication_async]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/async_samples/sample_authentication_async.py
        [sample_manage_custom_models]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_manage_custom_models.py
        [sample_manage_custom_models_async]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/async_samples/sample_manage_custom_models_async.py
        [sample_recognize_content]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_recognize_content.py
        [sample_recognize_content_async]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/async_samples/sample_recognize_content_async.py
        [sample_recognize_custom_forms]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_recognize_custom_forms.py
        [sample_recognize_custom_forms_async]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/async_samples/sample_recognize_custom_forms_async.py
        [sample_recognize_receipts_from_url]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_recognize_receipts_from_url.py
        [sample_recognize_receipts_from_url_async]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/async_samples/sample_recognize_receipts_from_url_async.py
        [sample_recognize_receipts]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_recognize_receipts.py
        [sample_recognize_receipts_async]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/async_samples/sample_recognize_receipts_async.py
        [sample_train_model_with_labels]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_train_model_with_labels.py
        [sample_train_model_with_labels_async]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/async_samples/sample_train_model_with_labels_async.py
        [sample_train_model_without_labels]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_train_model_without_labels.py
        [sample_train_model_without_labels_async]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/async_samples/sample_train_model_without_labels_async.py
        [sample_copy_model]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_copy_model.py
        [sample_copy_model_async]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/formrecognizer/azure-ai-formrecognizer/samples/async_samples/sample_copy_model_async.py
        
        
        # Change Log azure-ai-formrecognizer
        
        ## 1.0.0b3 (2020-06-10)
        
        **Breaking Changes**
        
        - All asynchronous long running operation methods now return an instance of an `AsyncLROPoller` from `azure-core`
        - All asynchronous long running operation methods are renamed with the `begin_` prefix to indicate that an `AsyncLROPoller` is returned:
            - `train_model` is renamed to `begin_training`
            - `recognize_receipts` is renamed to `begin_recognize_receipts`
            - `recognize_receipts_from_url` is renamed to `begin_recognize_receipts_from_url`
            - `recognize_content` is renamed to `begin_recognize_content`
            - `recognize_content_from_url` is renamed to `begin_recognize_content_from_url`
            - `recognize_custom_forms` is renamed to `begin_recognize_custom_forms`
            - `recognize_custom_forms_from_url` is renamed to `begin_recognize_custom_forms_from_url`
        - Sync method `begin_train_model` renamed to `begin_training`
        - `training_files` parameter of `begin_training` is renamed to `training_files_url`
        - `use_labels` parameter of `begin_training` is renamed to `use_training_labels`
        - `list_model_infos` method has been renamed to `list_custom_models`
        - Removed `get_form_training_client` from `FormRecognizerClient`
        - Added `get_form_recognizer_client` to `FormTrainingClient`
        - A `HttpResponseError` is now raised if a model with `status=="invalid"` is returned from the `begin_training` methods
        - `PageRange` is renamed to `FormPageRange`
        - `first_page` and `last_page` renamed to `first_page_number` and `last_page_number`, respectively on `FormPageRange`
        - `FormField` does not have a page_number
        - `use_training_labels` is now a required positional param in the `begin_training` APIs
        - `stream` and `url` parameters found on methods for `FormRecognizerClient` have been renamed to `form` and `form_url`, respectively
        - For `begin_recognize_receipt` methods, parameters have been renamed to `receipt` and `receipt_url`
        - `created_on` and `last_modified` are renamed to `requested_on` and `completed_on` in the
        `CustomFormModel`  and `CustomFormModelInfo` models
        - `models` property of `CustomFormModel` is renamed to `submodels`
        - `CustomFormSubModel` is renamed to `CustomFormSubmodel`
        - `begin_recognize_receipts` APIs now return a list of `RecognizedReceipt` instead of `USReceipt`
        - Removed `USReceipt`. To see how to deal with the return value of `begin_recognize_receipts`, see the recognize receipt samples in the [samples directory](https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/formrecognizer/azure-ai-formrecognizer/samples) for details.
        - Removed `USReceiptItem`. To see how to access the individual items on a receipt, see the recognize receipt samples in the [samples directory](https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/formrecognizer/azure-ai-formrecognizer/samples) for details.
        - Removed `USReceiptType` and the `receipt_type` property from `RecognizedReceipt`. See the recognize receipt samples in the [samples directory](https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/formrecognizer/azure-ai-formrecognizer/samples) for details.
        
        **New features**
        
        - Support to copy a custom model from one Form Recognizer resource to another
        - Authentication using `azure-identity` credentials now supported
          - see the [Azure Identity documentation](https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/identity/azure-identity/README.md) for more information
        - `page_number` attribute has been added to `FormTable`
        - All long running operation methods now accept the keyword argument `continuation_token` to restart the poller from a saved state
        
        **Dependency updates**
        
        - Adopted [azure-core](https://pypi.org/project/azure-core/) version 1.6.0 or greater
        
        ## 1.0.0b2 (2020-05-06)
        
        **Fixes and improvements**
        
        - Bug fixed where `confidence` == `0.0` was erroneously getting set to `1.0`
        - `__repr__` has been added to all of the models
        
        
        ## 1.0.0b1 (2020-04-23)
        
        Version (1.0.0b1) is the first preview of our efforts to create a user-friendly and Pythonic client library for Azure Form Recognizer.
        This library replaces the package found here: https://pypi.org/project/azure-cognitiveservices-formrecognizer/
        
        For more information about this, and preview releases of other Azure SDK libraries, please visit
        https://azure.github.io/azure-sdk/releases/latest/python.html.
        
        **Breaking changes: New API design**
        
        - New namespace/package name:
          - The namespace/package name for the Form Recognizer client library has changed from
            `azure.cognitiveservices.formrecognizer` to `azure.ai.formrecognizer`
        - Two client design:
            - FormRecognizerClient to analyze fields/values on custom forms, receipts, and form content/layout
            - FormTrainingClient to train custom models (with/without labels), and manage the custom models on your account
        - Different analyze methods based on input type: file stream or URL.
            - URL input should use the method with suffix `from_url`
            - Stream methods will automatically detect content-type of the input file
        - Asynchronous APIs added under `azure.ai.formrecognizer.aio` namespace
        - Authentication with API key supported using `AzureKeyCredential("<api_key>")` from `azure.core.credentials`
        - New underlying REST pipeline implementation based on the azure-core library
        - Client and pipeline configuration is now available via keyword arguments at both the client level, and per-operation.
            See README for a link to optional configuration arguments
        - New error hierarchy:
            - All service errors will now use the base type: `azure.core.exceptions.HttpResponseError`
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: License :: OSI Approved :: MIT License
Description-Content-Type: text/markdown
