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articles/applied-ai-services/form-recognizer/concept-layout.md

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ms.service: applied-ai-services
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ms.subservice: forms-recognizer
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ms.topic: conceptual
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ms.date: 05/23/2023
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ms.date: 06/23/2023
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ms.author: lajanuar
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---
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The JSON output has two parts:
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* `readResults` node contains all of the recognized text and selection mark. The text presentation hierarchy is page, then line, then individual words.
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* `pageResults` node contains the tables and cells extracted with their bounding boxes, confidence, and a reference to the lines and words in "readResults".
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* `pageResults` node contains the tables and cells extracted with their bounding boxes, confidence, and a reference to the lines and words in "readResults" field.
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## Example Output
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articles/applied-ai-services/form-recognizer/faq.yml

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ms.service: applied-ai-services
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ms.date: 03/03/2023
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monikerRange: '>=form-recog-2.1.0'
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Models have the same lifecycle as the API version used to train the model. Custom models trained with a generally available (GA) version of the API have the same lifecycle as the API version. When the API version is deprecated, the model is no longer available for inference. Models trained with a preview version of the API also have the same lifecycle as the preview API.
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Expect that preview APIs will be deprecated within three months of an updated preview API version or newer generally available API version.
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Expect preview API deprecation within three months of an updated preview API version or newer generally available API version.
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What is the accuracy score and how is it calculated?
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- [C#/.NET](https://www.nuget.org/packages/Azure.AI.FormRecognizer/4.0.0)
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- [Java](https://oss.sonatype.org/#nexus-search;quick-azure-ai-formrecognizer)
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- [Java](https://oss.sonatype.org/#nexus-search; quick-azure-ai-formrecognizer)
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- [JavaScript/TypeScript](https://www.npmjs.com/package/@azure/ai-form-recognizer/v/4.0.0-beta.4)
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| JavaScript | [4.0.0](https://azuresdkdocs.blob.core.windows.net/$web/javascript/azure-ai-form-recognizer/4.0.0/index.html)|[**v3.0**](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-2022-08-31/operations/AnalyzeDocument)</br> [**v2.1**](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v2-1/operations/AnalyzeBusinessCardAsync)</br>[**v2.0**](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v2/operations/AnalyzeLayoutAsync) |
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| Python | [3.2.0](https://azuresdkdocs.blob.core.windows.net/$web/python/azure-ai-formrecognizer/3.2.0/index.html) |[**v3.0**](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-2022-08-31/operations/AnalyzeDocument)</br> [**v2.1**](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v2-1/operations/AnalyzeBusinessCardAsync)</br>[**v2.0**](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v2/operations/AnalyzeLayoutAsync) |
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For more information, *see* [**Supported clients**](sdk-overview.md#supported-clients)
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For more information, *see* [Supported clients](sdk-overview.md#supported-clients)
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Form Recognizer connected containers send billing information to Azure by using a Form Recognizer resource on your Azure account. Connected containers don't send customer data, such as the image or text that's being analyzed, to Microsoft. See the [Cognitive Services container FAQ](../../cognitive-services/containers/disconnected-container-faq.yml#how-does-billing-work) for an example of the information sent to Microsoft for billing.
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I received an "OutOfQuota" error message: "Container isn't in a valid state. Subscription validation failed with status 'OutOfQuota'. API key is out of quota".
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I received an "OutOfQuota" error message: *Container isn't in a valid state. Subscription validation failed with status 'OutOfQuota' API key is out of quota*.
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Form Recognizer connected containers send billing information to Azure by using a Form Recognizer resource on your Azure account. You could get this message if the containers can't communicate with the billing endpoint.

articles/applied-ai-services/form-recognizer/how-to-guides/compose-custom-models.md

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### [Client libraries](#tab/sdks)
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Training with labels leads to better performance in some scenarios. To train with labels, you need to have special label information files (*\<filename\>.pdf.labels.json*) in your blob storage container alongside the training documents. Once you've them, you can call the training method with the *useTrainingLabels* parameter set to `true`.
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Training with labels leads to better performance in some scenarios. To train with labels, you need to have special label information files (*\<filename\>.pdf.labels.json*) in your blob storage container alongside the training documents. Once you have them, you can call the training method with the *useTrainingLabels* parameter set to `true`.
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articles/applied-ai-services/form-recognizer/service-limits.md

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* Go to [Azure portal](https://portal.azure.com/)
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* Select the Form Recognizer Resource for which you would like to increase the TPS limit
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* Select *New support request* (*Support + troubleshooting* group)
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* A new window appears with auto-populated information about your Azure Subscription and Azure Resource
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* A new window appears with autopopulated information about your Azure Subscription and Azure Resource
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* Enter *Summary* (like "Increase Form Recognizer TPS limit")
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* In Problem type,* select "Quota or usage validation"
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* Select *Next: Solutions*
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## Example of a workload pattern best practice
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This example presents the approach we recommend following to mitigate possible request throttling due to [Autoscaling being in progress](#detailed-description-quota-adjustment-and-best-practices). It isn't an "exact recipe", but merely a template we invite to follow and adjust as necessary.
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This example presents the approach we recommend following to mitigate possible request throttling due to [Autoscaling being in progress](#detailed-description-quota-adjustment-and-best-practices). It isn't an *exact recipe*, but merely a template we invite to follow and adjust as necessary.
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Let us suppose that a Form Recognizer resource has the default limit set. Start the workload to submit your analyze requests. If you find that you're seeing frequent throttling with response code 429, start by implementing an exponential backoff on the GET analyze response request. By using a progressively longer wait time between retries for consecutive error responses, for example a 2-5-13-34 pattern of delays between requests. In general, it's recommended to not call the get analyze response more than once every 2 seconds for a corresponding POST request.
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