Merge pull request #246844 from laujan/jp-release-ga-doc-intel-v3-1

add jp updates

Author: American-Dipper

articles/ai-services/document-intelligence/concept-add-on-capabilities.md

@@ -37,6 +37,20 @@ Document Intelligence now supports more sophisticated analysis capabilities. The
 
 The task of recognizing small text from large-size documents, like engineering drawings, is a challenge. Often the text is mixed with other graphical elements and has varying fonts, sizes and orientations. Moreover, the text may be broken into separate parts or connected with other symbols. Document Intelligence now supports extracting content from these types of documents with the `ocr.highResolution` capability. You get improved quality of content extraction from A1/A2/A3 documents by enabling this add-on capability.
 
+## Barcode extraction
+
+The Read OCR model extracts all identified barcodes in the `barcodes` collection as a top level object under `content`. Inside the `content`, detected barcodes are represented as `:barcode:`. Each entry in this collection represents a barcode and includes the barcode type as `kind` and the embedded barcode content as `value` along with its `polygon` coordinates. Initially, barcodes appear at the end of each page. Here, the `confidence` is hard-coded for the public preview (`2023-02-28`) release.
+
+### Supported barcode types
+
+| **Barcode Type**   | **Example**   |
+| --- | --- |
+| QR Code |:::image type="content" source="media/barcodes/qr-code.png" alt-text="Screenshot of the QR Code.":::|
+| Code 39 |:::image type="content" source="media/barcodes/code-39.png" alt-text="Screenshot of the Code 39.":::|
+| Code 128 |:::image type="content" source="media/barcodes/code-128.png" alt-text="Screenshot of the Code 128.":::|
+| UPC (UPC-A & UPC-E) |:::image type="content" source="media/barcodes/upc.png" alt-text="Screenshot of the UPC.":::|
+| PDF417 |:::image type="content" source="media/barcodes/pdf-417.png" alt-text="Screenshot of the PDF417.":::|
+
 ## Formula extraction
 
 The `ocr.formula` capability extracts all identified formulas, such as mathematical equations, in the `formulas` collection as a top level object under `content`. Inside `content`, detected formulas are represented as `:formula:`. Each entry in this collection represents a formula that includes the formula type as `inline` or `display`, and its LaTeX representation as `value` along with its `polygon` coordinates. Initially, formulas appear at the end of each page.

articles/ai-services/document-intelligence/concept-document-intelligence-studio.md

@@ -19,23 +19,28 @@ monikerRange: '>=doc-intel-3.0.0'
 
 [Document Intelligence Studio](https://formrecognizer.appliedai.azure.com/) is an online tool for visually exploring, understanding, and integrating features from the Document Intelligence service into your applications. Use the [Document Intelligence Studio quickstart](quickstarts/try-document-intelligence-studio.md) to get started analyzing documents with pretrained models. Build custom template models and reference the models in your applications using the [Python SDK v3.0](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true) and other quickstarts.
 
-The following image shows the Invoice prebuilt model feature at work.
+The following image shows the landing page for Document Intelligence Studio.
 
-:::image border="true" type="content" source="media/quickstarts/prebuilt-get-started-v2.gif" alt-text="Document Intelligence Prebuilt example":::
+:::image border="true" type="content" source="media/studio/welcome-to-studio.png" alt-text="Document Intelligence Studio Homepage":::
 
 ## Document Intelligence Studio features
 
 The following Document Intelligence service features are available in the Studio.
 
 * **Read**: Try out Document Intelligence's Read feature to extract text lines, words, detected languages, and handwritten style if detected. Start with the [Studio Read feature](https://formrecognizer.appliedai.azure.com/studio/read). Explore with sample documents and your documents. Use the interactive visualization and JSON output to understand how the feature works. See the [Read overview](concept-read.md) to learn more and get started with the [Python SDK quickstart for Layout](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true).
 
-* **Layout**: Try out Document Intelligence's Layout feature to extract text, tables, selection marks, and structure information. Start with the [Studio Layout feature](https://formrecognizer.appliedai.azure.com/studio/layout). Explore with sample documents and your documents. Use the interactive visualization and JSON output to understand how the feature works. See the [Layout overview](concept-layout.md) to learn more and get started with the [Python SDK quickstart for Layout](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true).
+* **Layout**: Try out Document Intelligence's Layout feature to extract text, tables, selection marks, and structure information. Start with the [Studio Layout feature](https://formrecognizer.appliedai.azure.com/studio/layout). Explore with sample documents and your documents. Use the interactive visualization and JSON output to understand how the feature works. See the [Layout overview](concept-layout.md) to learn more and get started with the [Python SDK quickstart for Layout](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true#layout-model).
 
-* **General Documents**: Try out Document Intelligence's General Documents feature to extract key-value pairs. Start with the [Studio General Documents feature](https://formrecognizer.appliedai.azure.com/studio/document). Explore with sample documents and your documents. Use the interactive visualization and JSON output to understand how the feature works. See the [General Documents overview](concept-general-document.md) to learn more and get started with the [Python SDK quickstart for Layout](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true).
+* **General Documents**: Try out Document Intelligence's General Documents feature to extract key-value pairs. Start with the [Studio General Documents feature](https://formrecognizer.appliedai.azure.com/studio/document). Explore with sample documents and your documents. Use the interactive visualization and JSON output to understand how the feature works. See the [General Documents overview](concept-general-document.md) to learn more and get started with the [Python SDK quickstart for Layout](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true#general-document-model).
 
-* **Prebuilt models**: Document Intelligence's prebuilt models enable you to add intelligent document processing to your apps and flows without having to train and build your own models. As an example, start with the [Studio Invoice feature](https://formrecognizer.appliedai.azure.com/studio/prebuilt?formType=invoice). Explore with sample documents and your documents. Use the interactive visualization, extracted fields list, and JSON output to understand how the feature works. See the [Models overview](concept-model-overview.md) to learn more and get started with the [Python SDK quickstart for Prebuilt Invoice](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true).
+* **Prebuilt models**: Document Intelligence's prebuilt models enable you to add intelligent document processing to your apps and flows without having to train and build your own models. As an example, start with the [Studio Invoice feature](https://formrecognizer.appliedai.azure.com/studio/prebuilt?formType=invoice). Explore with sample documents and your documents. Use the interactive visualization, extracted fields list, and JSON output to understand how the feature works. See the [Models overview](concept-model-overview.md) to learn more and get started with the [Python SDK quickstart for Prebuilt Invoice](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true#prebuilt-model).
+
+* **Custom extraction models**: Document Intelligence's custom models enable you to extract fields and values from models trained with your data, tailored to your forms and documents. Create standalone custom models or combine two or more custom models to create a composed model to extract data from multiple form types. Start with the [Studio Custom models feature](https://formrecognizer.appliedai.azure.com/studio/custommodel/projects).  Use the help wizard, labeling interface, training step, and visualizations to understand how the feature works. Test the custom model with your sample documents and iterate to improve the model. See the [Custom models overview](concept-custom.md) to learn more.
+
+* **Custom classification models**: Document classification is a new scenario supported by Document Intelligence. the document classifier API supports classification and splitting scenarios. Train a classification model to identify the different types of documents your application supports. The input file for the classification model can contain multiple documents and classifies each document within an associated page range. See [custom classification models](concept-custom-classifier.md) to learn more.
+
+* **Add-on Capabilities**: Document Intelligence now supports more sophisticated analysis capabilities. These optional capabilities can be enabled and disabled in the studio using the `Analze Options` button in each model page. There are four add-on capabilities available: highResolution, formula, font, and barcode extraction capabilities. See [Add-on capabilities](concept-add-on-capabilities.md) to learn more.
 
-* **Custom models**: Document Intelligence's custom models enable you to extract fields and values from models trained with your data, tailored to your forms and documents. Create standalone custom models or combine two or more custom models to create a composed model to extract data from multiple form types. Start with the [Studio Custom models feature](https://formrecognizer.appliedai.azure.com/studio/custommodel/projects).  Use the online wizard, labeling interface, training step, and visualizations to understand how the feature works. Test the custom model with your sample documents and iterate to improve the model. See the [Custom models overview](concept-custom.md) to learn more and use the [Document Intelligence v3.0 migration guide](v3-migration-guide.md) to start integrating the new models with your applications.
 
 ## Next steps
 

articles/ai-services/document-intelligence/concept-model-overview.md

@@ -54,6 +54,14 @@ monikerRange: '<=doc-intel-3.1.0'
 | [Custom classification model](#custom-classifier)| The **Custom classification model** can classify each page in an input file to identify the document(s) within and can also identify multiple documents or multiple instances of a single document within an input file.
 | [Composed models](#composed-models) | Combine several custom models into a single model to automate processing of diverse document types with a single composed model.
 
+For all of the models above except Business card model, Document Intelligence now supports add-on capabilities to allow for more sophisticated analysis. These optional capabilities can be enabled and disabled depending on the scenario of the document extraction. There are four add-on capabilities available for the `2023-07-31` (GA) API version:
+
+* [`ocr.highResolution`](concept-add-on-capabilities.md#high-resolution-extraction)
+* [`ocr.formula`](concept-add-on-capabilities.md#formula-extraction)
+* [`ocr.font`](concept-add-on-capabilities.md#font-property-extraction)
+* [`ocr.barcode`](concept-add-on-capabilities.md#barcode-extraction)
+
+
 ### Read OCR
 
 :::image type="icon" source="media/studio/read-card.png" :::

articles/ai-services/document-intelligence/media/managed-identities/rbac-flow.png

@@ -55,21 +55,6 @@ Prebuilt models help you add Document Intelligence features to your apps without
 * [**Custom extraction models**](https://formrecognizer.appliedai.azure.com/studio): extract information from forms and documents with custom extraction models. Quickly train a model by labeling as few as five sample documents.
 * [**Custom classification model**](https://formrecognizer.appliedai.azure.com/studio): train a custom classifier to distinguish between the different document types within your applications. Quickly train a model with as few as two classes and five samples per class.
 
-#### Gated preview models
-
-> [!NOTE]
-> To request access for gated preview models in Document Intelligence Studio, complete and submit the [**Document Intelligence private preview request form**](https://aka.ms/form-recognizer/preview/survey).
-
-* [**General document with query fields**](https://formrecognizer.appliedai.azure.com/studio): extract labels, values such as names, dates, and amounts from documents.
-* [**Contract**](https://formrecognizer.appliedai.azure.com/studio): extract the title and signatory party information (including names, references, and addresses) from contracts.
-* [**Vaccination card**](https://formrecognizer.appliedai.azure.com/studio): extract card holder name, health provider, and vaccination records from US COVID-19 vaccination cards.
-* [**US 1098 tax form**](https://formrecognizer.appliedai.azure.com/studio): extract mortgage interest information from US 1098 tax forms.
-* [**US 1098-E tax form**](https://formrecognizer.appliedai.azure.com/studio): extract student loan information from US 1098-E tax forms.
-* [**US 1098-T tax form**](https://formrecognizer.appliedai.azure.com/studio): extract tuition information from US 1098-T forms.
-
-> [!NOTE]
-> To request access for gated preview models in Document Intelligence Studio, complete and submit the [**Document Intelligence private preview request form**](https://aka.ms/form-recognizer/preview/survey).
-
 After you've completed the prerequisites, navigate to [Document Intelligence Studio General Documents](https://formrecognizer.appliedai.azure.com/studio/document).
 
 In the following example, we use the General Documents feature. The steps to use other pretrained features like [W2 tax form](https://formrecognizer.appliedai.azure.com/studio/prebuilt?formType=tax.us.w2), [Read](https://formrecognizer.appliedai.azure.com/studio/read), [Layout](https://formrecognizer.appliedai.azure.com/studio/layout), [Invoice](https://formrecognizer.appliedai.azure.com/studio/prebuilt?formType=invoice), [Receipt](https://formrecognizer.appliedai.azure.com/studio/prebuilt?formType=receipt), [Business card](https://formrecognizer.appliedai.azure.com/studio/prebuilt?formType=businessCard), and [ID documents](https://formrecognizer.appliedai.azure.com/studio/prebuilt?formType=idDocument) models are similar.
@@ -161,13 +146,15 @@ To create custom models, you start with configuring your project:
 
 1. Review and submit your settings to create the project.
 
-1. From the labeling view, define the labels and their types that you're interested in extracting.
+1. To quickstart the labeling process, use the auto label feature to label using already trained model or one of our prebuilt models.
+
+1. For manual labeling from scratch, define the labels and their types that you're interested in extracting.
 
 1. Select the text in the document and select the label from the drop-down list or the labels pane.
 
 1. Label four more documents to get at least five documents labeled.
 
-1. Select the Train command and enter model name, select whether you want the custom template (form) or custom neural (document) model to start training your custom model.
+1. Select the Train command and enter model name, select whether you want the neural (recommended) or template model to start training your custom model.
 
 1. Once the model is ready, use the Test command to validate it with your test documents and observe the results.
 

articles/ai-services/document-intelligence/media/studio/form-recognizer-studio-front.png

@@ -18,7 +18,7 @@ monikerRange: '>=doc-intel-3.0.0'
 
 [!INCLUDE [applies to v3.1 and v3.0](includes/applies-to-v3-1-v3-0.md)]
 
-Document Intelligence Studio is an online tool to visually explore, understand, train, and integrate features from the Document Intelligence service into your applications. The studio provides a platform for you to experiment with the different Document Intelligence models and sample their returned data in an interactive manner without the need to write code.
+Document Intelligence Studio is an online tool to visually explore, understand, train, and integrate features from the Document Intelligence service into your applications. The studio provides a platform for you to experiment with the different Document Intelligence models and sample returned data in an interactive manner without the need to write code.
 
 The studio supports Document Intelligence v3.0 models and v3.0 model training. Previously trained v2.1 models with labeled data are supported, but not v2.1 model training. Refer to the [REST API migration guide](v3-migration-guide.md) for detailed information about migrating from v2.1 to v3.0.
 
@@ -38,8 +38,6 @@ The studio supports Document Intelligence v3.0 models and v3.0 model training. P
       * Select an existing resource group within your subscription or create a new one.
       * Select your existing Document Intelligence or Azure AI services resource.
 
-      :::image type="content" source="media/studio/welcome-to-studio.png" alt-text="Screenshot of the configure service resource window.":::
-
     **b. Access by API endpoint and key**.
 
       * Retrieve your endpoint and key from the Azure portal.
@@ -50,7 +48,7 @@ The studio supports Document Intelligence v3.0 models and v3.0 model training. P
 
 1. Once you've completed configuring your resource, you're able to try the different models offered by Document Intelligence Studio. From the front page, select any Document Intelligence model to try using with a no-code approach.
 
-    :::image type="content" source="media/studio/form-recognizer-studio-front.png" alt-text="Screenshot of Document Intelligence Studio front page.":::
+    :::image type="content" source="media/studio/welcome-to-studio.png" alt-text="Screenshot of Document Intelligence Studio front page.":::
 
 1. After you've tried Document Intelligence Studio, use the [**C#**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true), [**Java**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true), [**JavaScript**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true) or [**Python**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true) client libraries or the [**REST API**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true) to get started incorporating Document Intelligence models into your own applications.