update

Author: laujan

articles/applied-ai-services/form-recognizer/concept-business-card.md

@@ -15,8 +15,6 @@ recommendations: false
 
 # Form Recognizer Business Card model
 
-The business card model combines powerful Optical Character Recognition (OCR) capabilities with deep learning models to analyze and extract key information from business card images. The API analyzes printed business cards; extracts key information such as first name, last name, company name, email address, and phone number;  and returns a structured JSON data representation.
-
 ::: moniker range="form-recog-3.0.0"
 [!INCLUDE [applies to v3.0](includes/applies-to-v3-0.md)]
 ::: moniker-end
@@ -25,9 +23,11 @@ The business card model combines powerful Optical Character Recognition (OCR) ca
 [!INCLUDE [applies to v2.1](includes/applies-to-v2-1.md)]
 ::: moniker-end
 
-## Business card data extraction works
+The business card model combines powerful Optical Character Recognition (OCR) capabilities with deep learning models to analyze and extract key information from business card images. The API analyzes printed business cards; extracts key information such as first name, last name, company name, email address, and phone number;  and returns a structured JSON data representation.
+
+## Business card data extraction
 
-Business cards are a great way of representing a business or a professional. The company logo, fonts and background images found in business cards help the company branding and differentiate it from others. Applying OCR and machine-learning based techniques to automate scanning of business cards is a common image processing scenario. Enterprise systems used by sales and marketing teams typically have business card data extraction capability integrated into them for the benefit of their users.
+Business cards are a great way to represent a business or a professional. The company logo, fonts and background images found in business cards help promote the company branding and differentiate it from others. Applying OCR and machine-learning based techniques to automate scanning of business cards is a common image processing scenario. Enterprise systems used by sales and marketing teams typically have business card data extraction capability integration into for the benefit of their users.
 
 ::: moniker range="form-recog-3.0.0"
 ***Sample business card processed with [Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio/prebuilt?formType=businessCard)***
@@ -68,7 +68,7 @@ The following tools are supported by Form Recognizer v2.1:
 
 ### Try business card data extraction
 
-See how data, including name, job title, address, email, and company name, is extracted from business cards using the Form Recognizer Studio or our Sample Labeling tool. You'll need the following resources:
+See how data, including name, job title, address, email, and company name, is extracted from business cards. You'll need the following resources:
 
 * An Azure subscription—you can [create one for free](https://azure.microsoft.com/free/cognitive-services/)
 
@@ -102,11 +102,11 @@ See how data, including name, job title, address, email, and company name, is ex
 
 1. Navigate to the [Form Recognizer Sample Tool](https://fott-2-1.azurewebsites.net/).
 
-1. On the sample tool home page, select **Use prebuilt model to get data**.
+1. On the sample tool home page, select the **Use prebuilt model to get data** tile.
 
     :::image type="content" source="media/label-tool/prebuilt-1.jpg" alt-text="Analyze results of Form Recognizer Layout":::
 
-1. Select the **Form Type**  to analyze from the dropdown window.
+1. Select the **Form Type**  to analyze from the dropdown menu.
 
 1. Choose a URL for the file you would like to analyze from the below options:
 
@@ -129,7 +129,7 @@ See how data, including name, job title, address, email, and company name, is ex
 
 1. View the results - see the key-value pairs extracted, line items, highlighted text extracted and tables detected.
 
-    :::image type="content" source="media/invoice-example-new.jpg" alt-text="Analyze Results of Form Recognizer invoice model":::
+    :::image type="content" source="media/business-card-results.png" alt-text="Screenshot of the analyze Results for business card model":::
 
 > [!NOTE]
 > The [Sample Labeling tool](https://fott-2-1.azurewebsites.net/) does not support the BMP file format. This is a limitation of the tool not the Form Recognizer Service.
@@ -138,8 +138,20 @@ See how data, including name, job title, address, email, and company name, is ex
 
 ## Input requirements
 
+::: moniker range="form-recog-3.0.0"
+
 [!INCLUDE [input requirements](./includes/input-requirements.md)]
 
+::: moniker-end
+
+::: moniker range="form-recog-2.1.0"
+
+* Supported file formats: JPEG, PNG, PDF, and TIFF
+* For PDF and TIFF, up to 2000 pages are processed. For free tier subscribers, only the first two pages are processed.
+* The file size must be less than 50 MB and dimensions at least 50 x 50 pixels and at most 10,000 x 10,000 pixels.
+
+::: moniker-end
+
 ::: moniker range="form-recog-3.0.0"
 
 ## Supported languages and locales

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

@@ -162,6 +162,9 @@ The [Sample Labeling tool](https://fott-2-1.azurewebsites.net/) doesn't support
 
 ## Supported languages and locales
 
+>[!NOTE]
+ > It's not necessary to specify a locale. This is an optional parameter. The Form Recognizer deep-learning technology will auto-detect the language of the text in your image.
+
  The Form Recognizer v3.0 version introduces more language support for custom models. For a list of supported handwritten and printed text, see [Language support](language-support.md).
 
 ## Form Recognizer v3.0 

articles/applied-ai-services/form-recognizer/concept-general-document.md

@@ -97,6 +97,9 @@ Keys can also exist in isolation when the model detects that a key exists, with
 
 ## Supported languages and locales
 
+>[!NOTE]
+ > It's not necessary to specify a locale. This is an optional parameter. The Form Recognizer deep-learning technology will auto-detect the language of the text in your image.
+
 | Model | Language—Locale code | Default |
 |--------|:----------------------|:---------|
 |General document| <ul><li>English (United States)—en-US</li></ul>| English (United States)—en-US|

articles/applied-ai-services/form-recognizer/concept-id-document.md

@@ -77,8 +77,20 @@ The following tools are supported by Form Recognizer v2.1:
 
 ## Input requirements
 
+::: moniker range="form-recog-3.0.0"
+
 [!INCLUDE [input requirements](./includes/input-requirements.md)]
 
+::: moniker-end
+
+::: moniker range="form-recog-2.1.0"
+
+* Supported file formats: JPEG, PNG, PDF, and TIFF
+* For PDF and TIFF, up to 2000 pages are processed. For free tier subscribers, only the first two pages are processed.
+* The file size must be less than 50 MB and dimensions at least 50 x 50 pixels and at most 10,000 x 10,000 pixels.
+
+::: moniker-end
+
 ### Try Form Recognizer
 
 Extract data, including name, birth date, and expiration date, from ID documents. You'll need the following resources:
@@ -114,11 +126,11 @@ Extract data, including name, birth date, and expiration date, from ID documents
 
 1. Navigate to the [Form Recognizer Sample Tool](https://fott-2-1.azurewebsites.net/).
 
-1. On the sample tool home page, select **Use prebuilt model to get data**.
+1. On the sample tool home page, select the **Use prebuilt model to get data** tile.
 
     :::image type="content" source="media/label-tool/prebuilt-1.jpg" alt-text="Analyze results of Form Recognizer Layout":::
 
-1. Select the **Form Type**  to analyze from the dropdown window.
+1. Select the **Form Type**  to analyze from the dropdown menu.
 
 1. Choose a URL for the file you would like to analyze from the below options:
 
@@ -135,7 +147,7 @@ Extract data, including name, birth date, and expiration date, from ID documents
 
 1. In the **key** field, paste  the key you obtained from your Form Recognizer resource.
 
-    :::image type="content" source="media/fott-select-form-type.png" alt-text="Screenshot: select form type dropdown window.":::
+    :::image type="content" source="media/fott-select-form-type.png" alt-text="Screenshot: select form type dropdown menu.":::
 
 1. Select **Run analysis**. The Form Recognizer Sample Labeling tool will call the Analyze Prebuilt API and analyze the document.
 
@@ -155,6 +167,9 @@ Extract data, including name, birth date, and expiration date, from ID documents
 
 ## Supported languages and locales
 
+>[!NOTE]
+ > It's not necessary to specify a locale. This is an optional parameter. The Form Recognizer deep-learning technology will auto-detect the language of the text in your image.
+
 | Model | Language—Locale code | Default |
 |--------|:----------------------|:---------|
 |ID document| <ul><li>English (United States)—en-US (driver's license)</li><li>Biographical pages from international passports</br> (excluding visa and other travel documents)</li><li>English (United States)—en-US (state ID)</li><li>English (United States)—en-US (social security card)</li><li>English (United States)—en-US (permanent resident card)</li></ul></br>|English (United States)—en-US|

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

@@ -100,11 +100,11 @@ See how data, including customer information, vendor details, and line items, is
 
 1. Navigate to the [Form Recognizer Sample Tool](https://fott-2-1.azurewebsites.net/).
 
-1. On the sample tool home page, select **Use prebuilt model to get data**.
+1. On the sample tool home page, select the **Use prebuilt model to get data** tile.
 
     :::image type="content" source="media/label-tool/prebuilt-1.jpg" alt-text="Analyze results of Form Recognizer Layout":::
 
-1. Select the **Form Type**  to analyze from the dropdown window.
+1. Select the **Form Type**  to analyze from the dropdown menu.
 
 1. Choose a URL for the file you would like to analyze from the below options:
 
@@ -136,12 +136,27 @@ See how data, including customer information, vendor details, and line items, is
 
 ## Input requirements
 
+::: moniker range="form-recog-3.0.0"
+
 [!INCLUDE [input requirements](./includes/input-requirements.md)]
 
+::: moniker-end
+
+::: moniker range="form-recog-2.1.0"
+
+* Supported file formats: JPEG, PNG, PDF, and TIFF
+* For PDF and TIFF, up to 2000 pages are processed. For free tier subscribers, only the first two pages are processed.
+* The file size must be less than 50 MB and dimensions at least 50 x 50 pixels and at most 10,000 x 10,000 pixels.
+
+::: moniker-end
+
 ::: moniker range="form-recog-3.0.0"
 
 ## Supported languages and locales
 
+>[!NOTE]
+ > It's not necessary to specify a locale. This is an optional parameter. The Form Recognizer deep-learning technology will auto-detect the language of the text in your image.
+
 | Model | Language—Locale code | Default |
 |--------|:----------------------|:---------|
 |Invoice| <ul><li>English (United States)—en-US</li></ul>| English (United States)—en-US|

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

@@ -12,7 +12,7 @@ ms.author: lajanuar
 recommendations: false
 ---
 
-# Form Recognizer layout model
+# Azure Form Recognizer layout model
 
 The Form Recognizer Layout is an advanced machine-learning based document layout analysis model available in the Form Recognizer cloud API. In the version v2.1, the document layout model extracted text lines, words, tables, and selection marks.
 
@@ -165,8 +165,20 @@ See how data, including text, tables, table headers, selection marks, and struct
 
 ## Input requirements
 
+::: moniker range="form-recog-3.0.0"
+
 [!INCLUDE [input requirements](./includes/input-requirements.md)]
 
+::: moniker-end
+
+::: moniker range="form-recog-2.1.0"
+
+* Supported file formats: JPEG, PNG, PDF, and TIFF
+* For PDF and TIFF, up to 2000 pages are processed. For free tier subscribers, only the first two pages are processed.
+* The file size must be less than 50 MB and dimensions at least 50 x 50 pixels and at most 10,000 x 10,000 pixels.
+
+::: moniker-end
+
 ## Supported languages and locales
 
 *See* [Language Support](language-support.md) for a complete list of supported handwritten and printed languages.
@@ -404,15 +416,15 @@ Layout API also extracts selection marks from documents. Extracted selection mar
 
 ::: moniker range="form-recog-3.0.0"
 
-* Try processing your own forms and documents with the [Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio)
+* [Learn how to process your own forms and documents](quickstarts/try-v3-form-recognizer-studio.md) with the [Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio)
 
 * Complete a [Form Recognizer quickstart](quickstarts/get-started-sdks-rest-api.md?view=form-recog-3.0.0&preserve-view=true) and get started creating a document processing app in the development language of your choice.
 
 ::: moniker-end
 
 ::: moniker range="form-recog-2.1.0"
 
-* Try processing your own forms and documents with the [Form Recognizer sample labeling tool](https://fott-2-1.azurewebsites.net/)
+* [Learn how to process your own forms and documents](quickstarts/try-sample-label-tool.md) with the [Form Recognizer sample labeling tool](https://fott-2-1.azurewebsites.net/)
 
 * Complete a [Form Recognizer quickstart](quickstarts/get-started-sdks-rest-api.md?view=form-recog-2.1.0&preserve-view=true) and get started creating a document processing app in the development language of your choice.
 

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

@@ -103,11 +103,11 @@ See how data, including time and date of transactions, merchant information, and
 
 1. Navigate to the [Form Recognizer Sample Tool](https://fott-2-1.azurewebsites.net/).
 
-1. On the sample tool home page, select **Use prebuilt model to get data**.
+1. On the sample tool home page, select the **Use prebuilt model to get data** tile.
 
     :::image type="content" source="media/label-tool/prebuilt-1.jpg" alt-text="Analyze results of Form Recognizer Layout":::
 
-1. Select the **Form Type**  to analyze from the dropdown window.
+1. Select the **Form Type**  to analyze from the dropdown menu.
 
 1. Choose a URL for the file you would like to analyze from the below options:
 
@@ -139,8 +139,20 @@ See how data, including time and date of transactions, merchant information, and
 
 ## Input requirements
 
+::: moniker range="form-recog-3.0.0"
+
 [!INCLUDE [input requirements](./includes/input-requirements.md)]
 
+::: moniker-end
+
+::: moniker range="form-recog-2.1.0"
+
+* Supported file formats: JPEG, PNG, PDF, and TIFF
+* For PDF and TIFF, up to 2000 pages are processed. For free tier subscribers, only the first two pages are processed.
+* The file size must be less than 50 MB and dimensions at least 50 x 50 pixels and at most 10,000 x 10,000 pixels.
+
+::: moniker-end
+
 ::: moniker range="form-recog-3.0.0"
 
 ## Supported languages and locales v3.0

articles/applied-ai-services/form-recognizer/quickstarts/includes/get-started/csharp.md

@@ -66,7 +66,7 @@ In this quickstart, you'll use the following APIs to extract structured data fro
 
  1. Select the Browse tab and type Azure.AI.FormRecognizer.
 
-      :::image type="content" source="../../../media/quickstarts/azure-nuget-package.png" alt-text="Screenshot showing the select Form Recognizer package dropdown window.":::
+      :::image type="content" source="../../../media/quickstarts/azure-nuget-package.png" alt-text="Screenshot showing the select Form Recognizer package dropdown menu.":::
 
  1. Select version **3.1.1** from the dropdown menu and select **Install**.
 

articles/applied-ai-services/form-recognizer/quickstarts/try-sample-label-tool.md

@@ -65,11 +65,11 @@ Form Recognizer offers several prebuilt models to choose from. Each model has it
 
 1. Navigate to the [Form Recognizer Sample Tool](https://fott-2-1.azurewebsites.net/).
 
-1. On the sample tool home page, select **Use prebuilt model to get data**.
+1. On the sample tool home page, select the **Use prebuilt model to get data** tile.
 
     :::image type="content" source="../media/label-tool/prebuilt-1.jpg" alt-text="Analyze results of Form Recognizer Layout":::
 
-1. Select the **Form Type**  to analyze from the dropdown window.
+1. Select the **Form Type**  to analyze from the dropdown menu.
 
 1. Choose a URL for the file you would like to analyze from the below options:
 
@@ -86,7 +86,7 @@ Form Recognizer offers several prebuilt models to choose from. Each model has it
 
 1. In the **key** field, paste  the key you obtained from your Form Recognizer resource.
 
-    :::image type="content" source="../media/fott-select-form-type.png" alt-text="Screenshot: select form type dropdown window.":::
+    :::image type="content" source="../media/fott-select-form-type.png" alt-text="Screenshot: select form type dropdown menu.":::
 
 1. Select **Run analysis**. The Form Recognizer Sample Labeling tool will call the Analyze Prebuilt API and analyze the document.
 
@@ -119,7 +119,7 @@ Azure the Form Recognizer Layout API extracts text, tables, selection marks, and
 
 1. Select **Run Layout**. The Form Recognizer Sample Labeling tool will call the Analyze Layout API and analyze the document.
 
-    :::image type="content" source="../media/fott-layout.png" alt-text="Screenshot: Layout dropdown window.":::
+    :::image type="content" source="../media/fott-layout.png" alt-text="Screenshot: Layout dropdown menu.":::
 
 1. View the results - see the highlighted text extracted, selection marks detected and tables detected.
 

articles/applied-ai-services/form-recognizer/tutorial-azure-function.md

@@ -95,7 +95,7 @@ In this tutorial, you learn how to:
 
     * **Select subscription** → choose your Azure subscription with the storage account you created → select your storage account → then select the name of the storage input container (in this case, `input/{name}`). Press **Enter** to confirm.
 
-    * **Select how your would like to open your project** → choose **Open the project in the current window** from the dropdown window.
+    * **Select how your would like to open your project** → choose **Open the project in the current window** from the dropdown menu.
 
 1. Once you've completed these steps, VS Code will add a new Azure Function project with a *\_\_init\_\_.py* Python script. This script will be triggered when a file is uploaded to the **input** storage container: