Merge pull request #113584 from PatrickFarley/minor-updates

[cog serv] Minor updates

Author: PRMerger13

articles/cognitive-services/Computer-vision/QuickStarts/python-analyze.md

@@ -9,7 +9,7 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: computer-vision
 ms.topic: quickstart
-ms.date: 04/14/2020
+ms.date: 05/01/2020
 ms.author: pafarley
 ms.custom: seodec18
 ---

articles/cognitive-services/Computer-vision/concept-recognizing-text.md

@@ -22,10 +22,10 @@ Computer Vision provides a number of services that detect and extract printed or
 
 The Read API detects text content in an image using our latest recognition models and converts the identified text into a machine-readable character stream. It's optimized for text-heavy images (such as documents that have been digitally scanned) and for images with a lot of visual noise. It will determine which recognition model to use for each line of text, supporting images with both printed and handwritten text. The Read API executes asynchronously because larger documents can take several minutes to return a result.
 
-The Read operation maintains the original line groupings of recognized words in its output. Each line comes with bounding box coordinates, and each word within the line also has its own coordinates. If a word was recognized with low confidence, that information is conveyed as well. See the [Read API reference docs](https://westus.dev.cognitive.microsoft.com/docs/services/5adf991815e1060e6355ad44/operations/2afb498089f74080d7ef85eb) and [Read API Preview reference docs](https://go.microsoft.com/fwlink/?linkid=2118322) to learn more.
+The Read operation maintains the original line groupings of recognized words in its output. Each line comes with bounding box coordinates, and each word within the line also has its own coordinates. If a word was recognized with low confidence, that information is conveyed as well. See the [Read API v2.0 reference docs](https://westus.dev.cognitive.microsoft.com/docs/services/5adf991815e1060e6355ad44/operations/2afb498089f74080d7ef85eb) or [Read API v3.0 preview reference docs](https://go.microsoft.com/fwlink/?linkid=2118322) to learn more.
 
 > [!NOTE]
-> This feature is only available for English and Spanish (preview) text.
+> This feature is only available for English and Spanish (v3.0 preview) text.
 
 ### Image requirements
 

articles/cognitive-services/form-recognizer/quickstarts/label-tool.md

@@ -33,7 +33,7 @@ To complete this quickstart, you must have:
 You'll use the Docker engine to run the sample labeling tool. Follow these steps to set up the Docker container. For a primer on Docker and container basics, see the [Docker overview](https://docs.docker.com/engine/docker-overview/).
 
 > [!TIP]
-> The OCR Form Labeling Tool is also available as an open source project on GitHub. The tool is a web application built using React + Redux, and is written in TypeScript. To learn more or contribute, see [OCR Form Labeling Tool](https://github.com/microsoft/OCR-Form-Tools/blob/master/README.md#run-as-web-application).
+> The OCR Form Labeling Tool is also available as an open source project on GitHub. The tool is a TypeScript web application built using React + Redux. To learn more or contribute, see the [OCR Form Labeling Tool](https://github.com/microsoft/OCR-Form-Tools/blob/master/README.md#run-as-web-application) repo. To try out the tool online, go to the [FOTT website](https://fott.azurewebsites.net/).   
 
 1. First, install Docker on a host computer. This guide will show you how to use local computer as a host. If you want to use a Docker hosting service in Azure, see the [Deploy the sample labeling tool](../deploy-label-tool.md) how-to guide.