Merge pull request #224138 from laujan/patch-190

Update form-recognizer-container-install-run.md

Author: prmerger-automator[bot]

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

@@ -11,7 +11,7 @@ ms.date: 11/14/2022
 ms.author: lajanuar
 recommendations: false
 ---
-<!-- markdownlint-disable MD033 -->
+<!-- markdownlint-disable MD033 -->
 
 # Azure Form Recognizer receipt model
 

articles/applied-ai-services/form-recognizer/containers/form-recognizer-container-install-run.md

@@ -116,7 +116,7 @@ The following host machine requirements are applicable to **train and analyze**
 
 ### [Layout](#tab/layout)
 
-Below is a self-contained `docker compose`  example to run the Form Recognizer Layout container.  With `docker compose`, you use a YAML file to configure your application's services. Then, with `docker-compose up` command, you create and start all the services from your configuration. Enter {FORM_RECOGNIZER_ENDPOINT_URI} and {{FORM_RECOGNIZER_KEY} values for your Layout container instance.
+The following code sample is a self-contained `docker compose`  example to run the Form Recognizer Layout container.  With `docker compose`, you use a YAML file to configure your application's services. Then, with `docker-compose up` command, you create and start all the services from your configuration. Enter {FORM_RECOGNIZER_ENDPOINT_URI} and {{FORM_RECOGNIZER_KEY} values for your Layout container instance.
 
 ```yml
 version: "3.9"
@@ -146,7 +146,7 @@ docker-compose up
 
 ### [Business Card](#tab/business-card)
 
-Below is a self-contained `docker compose` example to run Form Recognizer Business Card and Read containers together. With `docker compose`, you use a YAML file to configure your application's services. Then, with `docker-compose up` command, you create and start all the services from your configuration. Enter {FORM_RECOGNIZER_ENDPOINT_URI} and {FORM_RECOGNIZER_KEY} values for your Business Card container instance. Enter {COMPUTER_VISION_ENDPOINT_URI} and {COMPUTER_VISION_KEY} for your Computer Vision Read container.
+The following code sample is a self-contained `docker compose` example to run Form Recognizer Business Card and Read containers together. With `docker compose`, you use a YAML file to configure your application's services. Then, with `docker-compose up` command, you create and start all the services from your configuration. Enter {FORM_RECOGNIZER_ENDPOINT_URI} and {FORM_RECOGNIZER_KEY} values for your Business Card container instance. Enter {COMPUTER_VISION_ENDPOINT_URI} and {COMPUTER_VISION_KEY} for your Computer Vision Read container.
 
 ```yml
 version: "3.9"
@@ -186,7 +186,7 @@ docker-compose up
 
 ### [ID Document](#tab/id-document)
 
-Below is a self-contained `docker compose` example to run Form Recognizer ID Document and Read containers together. With `docker compose`, you use a YAML file to configure your application's services. Then, with `docker-compose up` command, you create and start all the services from your configuration. Enter {FORM_RECOGNIZER_ENDPOINT_URI} and {FORM_RECOGNIZER_KEY} values for your ID document container. Enter {COMPUTER_VISION_ENDPOINT_URI} and {COMPUTER_VISION_KEY} values for your Computer Vision Read container.
+The following code sample is a self-contained `docker compose` example to run Form Recognizer ID Document and Read containers together. With `docker compose`, you use a YAML file to configure your application's services. Then, with `docker-compose up` command, you create and start all the services from your configuration. Enter {FORM_RECOGNIZER_ENDPOINT_URI} and {FORM_RECOGNIZER_KEY} values for your ID document container. Enter {COMPUTER_VISION_ENDPOINT_URI} and {COMPUTER_VISION_KEY} values for your Computer Vision Read container.
 
 ```yml
 version: "3.9"
@@ -226,7 +226,7 @@ docker-compose up
 
 ### [Invoice](#tab/invoice)
 
-Below is a self-contained `docker compose` example to run Form Recognizer Invoice and Layout containers together. With `docker compose`, you use a YAML file to configure your application's services. Then, with `docker-compose up` command, you create and start all the services from your configuration.  Enter {FORM_RECOGNIZER_ENDPOINT_URI} and {FORM_RECOGNIZER_KEY} values for your Invoice and Layout containers.
+The following code sample is a self-contained `docker compose` example to run Form Recognizer Invoice and Layout containers together. With `docker compose`, you use a YAML file to configure your application's services. Then, with `docker-compose up` command, you create and start all the services from your configuration.  Enter {FORM_RECOGNIZER_ENDPOINT_URI} and {FORM_RECOGNIZER_KEY} values for your Invoice and Layout containers.
 
 ```yml
 version: "3.9"
@@ -265,8 +265,7 @@ docker-compose up
 ```
 
 ### [Receipt](#tab/receipt)
-
-Below is a self-contained `docker compose` example to run Form Recognizer Receipt and Read containers together. With `docker compose`, you use a YAML file to configure your application's services. Then, with `docker-compose up` command, you create and start all the services from your configuration. Enter {FORM_RECOGNIZER_ENDPOINT_URI} and {FORM_RECOGNIZER_KEY} values for your Receipt container. Enter {COMPUTER_VISION_ENDPOINT_URI} and {COMPUTER_VISION_KEY} values for your Computer Vision Read container.
+The following code sample is a self-contained `docker compose` example to run Form Recognizer Receipt and Read containers together. With `docker compose`, you use a YAML file to configure your application's services. Then, with `docker-compose up` command, you create and start all the services from your configuration. Enter {FORM_RECOGNIZER_ENDPOINT_URI} and {FORM_RECOGNIZER_KEY} values for your Receipt container. Enter {COMPUTER_VISION_ENDPOINT_URI} and {COMPUTER_VISION_KEY} values for your Computer Vision Read container.
 
 ```yml
 version: "3.9"
@@ -306,7 +305,7 @@ docker-compose up
 
 ### [Custom](#tab/custom)
 
-In addition to the [prerequisites](#prerequisites) mentioned above, you'll need to do the following to process a custom document:
+In addition to the [prerequisites](#prerequisites), you'll need to do the following to process a custom document:
 
 ####  • Create a folder to store the following files:
 
@@ -318,13 +317,13 @@ In addition to the [prerequisites](#prerequisites) mentioned above, you'll need
 
   1. Name this folder **shared**.
   1. We'll reference the file path for this folder as  **{SHARED_MOUNT_PATH}**.
-  1. Copy the file path in a convenient location, such as *Microsoft Notepad*. You'll need to add it to your **.env** file, below.
+  1. Copy the file path in a convenient location, such as *Microsoft Notepad*. You'll need to add it to your **.env** file.
 
 #### • Create a folder to store the logs  written by the Form Recognizer service on your local machine.
 
   1. Name this folder **output**.
   1. We'll reference the file path for this folder as **{OUTPUT_MOUNT_PATH}**.
-  1. Copy the file path in a convenient location, such as *Microsoft Notepad*. You'll need to add it to your **.env** file, below.
+  1. Copy the file path in a convenient location, such as *Microsoft Notepad*. You'll need to add it to your **.env** file.
 
 #### • Create an environment file
 
@@ -407,7 +406,7 @@ http {
 }
 ```
 
-* Gather a set of at least six forms of the same type. You'll use this data to train the model and test a form. You can use a [sample data set](https://go.microsoft.com/fwlink/?linkid=2090451) (download and extract *sample_data.zip*). Download the training files to the **shared** folder you created above.
+* Gather a set of at least six forms of the same type. You'll use this data to train the model and test a form. You can use a [sample data set](https://go.microsoft.com/fwlink/?linkid=2090451) (download and extract *sample_data.zip*). Download the training files to the **shared** folder you created.
 
 * If you want to label your data, download the [Form Recognizer Sample Labeling tool for Windows](https://github.com/microsoft/OCR-Form-Tools/releases). The download will import the labeling tool .exe file that you'll use to label the data present on your local file system. You can ignore any warnings that occur during the download process.
 
@@ -426,7 +425,7 @@ http {
 
 1. Name this file **docker-compose.yml**
 
-2. Below is a self-contained `docker compose` example to run Form Recognizer Layout, Label Tool, Custom API, and Custom Supervised containers together. With `docker compose`, you use a YAML file to configure your application's services. Then, with `docker-compose up` command, you create and start all the services from your configuration.
+2. The following code sample is a self-contained `docker compose` example to run Form Recognizer Layout, Label Tool, Custom API, and Custom Supervised containers together. With `docker compose`, you use a YAML file to configure your application's services. Then, with `docker-compose up` command, you create and start all the services from your configuration.
 
   ```yml
   version: '3.3'
@@ -545,13 +544,17 @@ $docker-compose up
 
 ---
 
+## The Sample Labeling tool and Azure Container Instances (ACI)
+
+To learn how to use the Sample Labeling tool with an Azure Container Instance, *see*, [Deploy the Sample Labeling tool](../deploy-label-tool.md#deploy-with-azure-container-instances-aci).
+
 ## Validate that the service is running
 
 There are several ways to validate that the container is running:
 
 * The container provides a homepage at `\` as a visual validation that the container is running.
 
-* You can open your favorite web browser and navigate to the external IP address and exposed port of the container in question. Use the various request URLs below to validate the container is running. The example request URLs listed below are `http://localhost:5000`, but your specific container may vary. Keep in mind that you're  navigating to your container's **External IP address** and exposed port.
+* You can open your favorite web browser and navigate to the external IP address and exposed port of the container in question. Use the listed request URLs to validate the container is running. The listed example request URLs are `http://localhost:5000`, but your specific container may vary. Keep in mind that you're  navigating to your container's **External IP address** and exposed port.
 
   Request URL    | Purpose
   ----------- | --------
@@ -577,7 +580,7 @@ The Form Recognizer containers send billing information to Azure by using a Form
 
 Queries to the container are billed at the pricing tier of the Azure resource that's used for the `Key`. You'll be billed for each container instance used to process your documents and images. Thus, If you use the business card feature, you'll be billed for the Form Recognizer `BusinessCard` and `Computer Vision Read` container instances. For the invoice feature, you'll be billed for the Form Recognizer `Invoice` and `Layout` container instances. *See*, [Form Recognizer](https://azure.microsoft.com/pricing/details/form-recognizer/) and Computer Vision [Read feature](https://azure.microsoft.com/pricing/details/cognitive-services/computer-vision/) container pricing.
 
-Azure Cognitive Services containers aren't licensed to run without being connected to the metering / billing endpoint. Containers must be enabled to communicate billing information with the billing endpoint at all times. Cognitive Services containers don't send customer data, such as the image or text that's being analyzed, to Microsoft.
+Azure Cognitive Services containers aren't licensed to run without being connected to the metering / billing endpoint. Containers must be enabled to always communicate billing information with the billing endpoint. Cognitive Services containers don't send customer data, such as the image or text that's being analyzed, to Microsoft.
 
 ### Connect to Azure
 

articles/applied-ai-services/form-recognizer/language-support.md

@@ -540,4 +540,4 @@ This technology is currently available for US driver licenses and the biographic
 ::: moniker range="form-recog-2.1.0"
 > [!div class="nextstepaction"]
 > [Try Form Recognizer Sample Labeling tool](https://aka.ms/fott-2.1-ga)
-::: moniker-end
+::: moniker-end