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Copy file name to clipboardExpand all lines: articles/ai-services/computer-vision/concept-ocr.md
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> [!NOTE]
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> If you want to extract text from PDFs, Office files, or HTML documents and document images, use the [Document Intelligence Read OCR model](../../ai-services/document-intelligence/concept-read.md). It's optimized for text-heavy digital and scanned documents and uses an asynchronous API that makes it easy to power your intelligent document processing scenarios.
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> If you want to extract text from PDFs, Office files, or HTML documents and document images, use the [Document Intelligence Read OCR model](../document-intelligence/prebuilt/read.md). It's optimized for text-heavy digital and scanned documents and uses an asynchronous API that makes it easy to power your intelligent document processing scenarios.
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OCR is a machine-learning-based technique for extracting text from in-the-wild and non-document images like product labels, user-generated images, screenshots, street signs, and posters. The Azure AI Vision OCR service provides a fast, synchronous API for lightweight scenarios where images aren't text-heavy. This allows OCR to be embedded in near real-time user experiences to enrich content understanding and follow-up user actions with fast turn-around times.
> | **Images**: General, in-the-wild images | labels, street signs, and posters | [OCR for images (version 4.0)](../concept-ocr.md) | Optimized for general, non-document images with a performance-enhanced synchronous API that makes it easier to embed OCR in your user experience scenarios.
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> | **Documents**: Digital and scanned, including images | books, articles, and reports | [Document Intelligence read model](../../../ai-services/document-intelligence/concept-read.md) | Optimized for text-heavy scanned and digital documents with an asynchronous API to help automate intelligent document processing at scale.
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> | **Documents**: Digital and scanned, including images | books, articles, and reports | [Document Intelligence read model](../../document-intelligence/prebuilt/read.md) | Optimized for text-heavy scanned and digital documents with an asynchronous API to help automate intelligent document processing at scale.
Copy file name to clipboardExpand all lines: articles/ai-services/computer-vision/overview-ocr.md
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## How is OCR related to Intelligent Document Processing (IDP)?
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Intelligent Document Processing (IDP) uses OCR as its foundational technology to additionally extract structure, relationships, key-values, entities, and other document-centric insights with an advanced machine-learning based AI service like [Document Intelligence](../../ai-services/document-intelligence/overview.md). Document Intelligence includes a document-optimized version of **Read** as its OCR engine while delegating to other models for higher-end insights. If you are extracting text from scanned and digital documents, use [Document Intelligence Read OCR](../../ai-services/document-intelligence/concept-read.md).
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Intelligent Document Processing (IDP) uses OCR as its foundational technology to additionally extract structure, relationships, key-values, entities, and other document-centric insights with an advanced machine-learning based AI service like [Document Intelligence](../../ai-services/document-intelligence/overview.md). Document Intelligence includes a document-optimized version of **Read** as its OCR engine while delegating to other models for higher-end insights. If you are extracting text from scanned and digital documents, use [Document Intelligence Read OCR](../document-intelligence/prebuilt/read.md).
Copy file name to clipboardExpand all lines: articles/ai-services/document-intelligence/authentication/create-sas-tokens.md
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# Create SAS tokens for storage containers
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::: moniker range="<=doc-intel-4.0.0"
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[!INCLUDE [applies to v4.0 v3.1 v3.0 v2.1](includes/applies-to-v40-v31-v30-v21.md)]
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[!INCLUDE [applies to v4.0 v3.1 v3.0 v2.1](../includes/applies-to-v40-v31-v30-v21.md)]
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::: moniker-end
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In this article, learn how to create user delegation, shared access signature (SAS) tokens, using the Azure portal or Azure Storage Explorer. User delegation SAS tokens are secured with Microsoft Entra credentials. SAS tokens provide secure, delegated access to resources in your Azure storage account.
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In this article, learn how to create user delegation, shared access signature (SAS) tokens, using the Azure portal or Azure Storage Explorer. User delegation SAS tokens are secured with Microsoft Entra credentials. SAS tokens provide secure, delegated access to resources in your Azure storage account.
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:::image type="content" source="media/sas-tokens/sas-url-token.png" alt-text="Screenshot of storage URI with SAS token appended.":::
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:::image type="content" source="../media/sas-tokens/sas-url-token.png" alt-text="Screenshot of storage URI with SAS token appended.":::
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At a high level, here's how SAS tokens work:
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1. Sign in to the [Azure portal](https://portal.azure.com).
:::image type="content" source="media/sas-tokens/data-storage-menu.png" alt-text="Screenshot that shows the Data storage menu in the Azure portal.":::
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:::image type="content" source="../media/sas-tokens/data-storage-menu.png" alt-text="Screenshot that shows the Data storage menu in the Azure portal.":::
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1. Select a container from the list.
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1. Select **Upload** from the menu at the top of the page.
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:::image type="content" source="media/sas-tokens/container-upload-button.png" alt-text="Screenshot that shows the container Upload button in the Azure portal.":::
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:::image type="content" source="../media/sas-tokens/container-upload-button.png" alt-text="Screenshot that shows the container Upload button in the Azure portal.":::
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1. The **Upload blob** window appears. Select your files to upload.
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:::image type="content" source="media/sas-tokens/upload-blob-window.png" alt-text="Screenshot that shows the Upload blob window in the Azure portal.":::
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:::image type="content" source="../media/sas-tokens/upload-blob-window.png" alt-text="Screenshot that shows the Upload blob window in the Azure portal.":::
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> [!NOTE]
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> By default, the REST API uses documents located at the root of your container. You can also use data organized in subfolders if specified in the API call. For more information, see [Organize your data in subfolders](how-to-guides/build-a-custom-model.md?view=doc-intel-2.1.0&preserve-view=true#organize-your-data-in-subfolders-optional).
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> By default, the REST API uses documents located at the root of your container. You can also use data organized in subfolders if specified in the API call. For more information, see [Organize your data in subfolders](../how-to-guides/build-a-custom-model.md?view=doc-intel-2.1.0&preserve-view=true#organize-your-data-in-subfolders-optional).
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## Use the Azure portal
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* Make sure the **Read**, **Write**, **Delete**, and **List** permissions are selected.
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:::image type="content" source="media/sas-tokens/sas-permissions.png" alt-text="Screenshot that shows the SAS permission fields in the Azure portal.":::
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:::image type="content" source="../media/sas-tokens/sas-permissions.png" alt-text="Screenshot that shows the SAS permission fields in the Azure portal.":::
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>[!IMPORTANT]
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> * If you receive a message similar to the following one, you'll also need to assign access to the blob data in your storage account:
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> :::image type="content" source="media/sas-tokens/need-permissions.png" alt-text="Screenshot that shows the lack of permissions warning.":::
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> :::image type="content" source="../media/sas-tokens/need-permissions.png" alt-text="Screenshot that shows the lack of permissions warning.":::
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> *[Azure role-based access control](/azure/role-based-access-control/overview) (Azure RBAC) is the authorization system used to manage access to Azure resources. Azure RBAC helps you manage access and permissions for your Azure resources.
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> *[Assign an Azure role for access to blob data](/azure/role-based-access-control/role-assignments-portal?tabs=current) to assign a role that allows for read, write, and delete permissions for your Azure storage container. *See*[Storage Blob Data Contributor](/azure/role-based-access-control/built-in-roles#storage-blob-data-contributor).
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## Next step
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> [!div class="nextstepaction"]
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> [Build a training data set](how-to-guides/build-a-custom-model.md?view=doc-intel-2.1.0&preserve-view=true)
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> [Build a training data set](../how-to-guides/build-a-custom-model.md?view=doc-intel-2.1.0&preserve-view=true)
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