Merge pull request #110852 from sdgilley/sdg-datalabeling-rbac

Remove teams and management of labelers

Author: GitHubber17

articles/machine-learning/how-to-create-labeling-projects.md

@@ -6,7 +6,7 @@ author: sdgilley
 ms.author: sgilley
 ms.service: machine-learning
 ms.topic: tutorial
-ms.date: 03/01/2020
+ms.date: 04/09/2020
 
 ---
 
@@ -164,24 +164,12 @@ Once a machine learning model has been trained on your manually labeled data, th
 
 After the labeling project is initialized, some aspects of the  project are immutable. You can't change the task type or dataset. You *can* modify labels and the URL for the task description. Carefully review the settings before you create the project. After you submit the project, you're returned to the **Data Labeling** homepage, which will show the project as **Initializing**. This page doesn't automatically refresh. So, after a pause,  manually refresh the page to see the project's status as **Created**.
 
-## Manage teams and people
-
-By default, each labeling project that you create gets a new team with you as a member. But teams can also be shared between projects. And projects can have more than one team. To create a team, select **Add team** on the **Teams** page. 
-
-You manage people on the **Labelers** page. Add and remove people by email address. Each labeler has to authenticate through your Microsoft account or Azure Active Directory, if you use it.  
-
-After you add a person, you can assign that person to one or more teams: Go to the **Teams** page, select the team, and then select **Assign people** or **Remove people**.
-
-To send an email to the team, select the team to view the **Team details** page. On this page, select **Email team** to open an email draft with the addresses of everyone on the team.
-
 ## Run and monitor the project
 
 After you initialize the project, Azure will begin running it. Select the project on the main **Data Labeling** page to go to **Project details**. The **Dashboard** tab shows the progress of the labeling task.
 
 On the **Data** tab, you can see your dataset and review labeled data. If you see incorrectly labeled data, select it and choose **Reject**, which will remove the labels and put the data back into the unlabeled queue.
 
-Use the **Team** tab to assign or unassign teams to the project.
-
 To pause or restart the project, select the **Pause**/**Start** button. You can only label data when the project is running.
 
 You can label data directly from the **Project details** page by selecting **Label data**.

articles/machine-learning/how-to-label-images.md

@@ -6,7 +6,7 @@ author: lobrien
 ms.author: laobri
 ms.service: machine-learning
 ms.topic: tutorial
-ms.date: 11/04/2019
+ms.date: 04/09/2020
 
 ---
 
@@ -21,21 +21,24 @@ After your project administrator [creates a labeling project](https://docs.micro
 
 ## Prerequisites
 
-* The labeling portal URL for a running data labeling project
 * A [Microsoft account](https://account.microsoft.com/account) or an Azure Active Directory account for the organization and project
+* Contributor level access to the workspace that contains the labeling project.
 
-> [!NOTE]
-> The project administrator can find the labeling portal URL on the **Details** tab of the **Project details** page.
+## Sign in to the workspace
 
-## Sign in to the project's labeling portal
+1. Sign in to [Azure Machine Learning studio](https://ml.azure.com).
 
-Go to the labeling portal URL that's provided by the project administrator. Sign in by using the email account that the administrator used to add you to the team. For most users, it will be your Microsoft account. If the labeling project uses Azure Active Directory, that's how you'll sign in.
+1. Select the subscription and the workspace that contains the labeling project.  Get this information from your project administrator.
+
+1. Select **Data labeling** on the left-hand side to find the project.  
+
+1. Select the project name in the list.
 
 ## Understand the labeling task
 
-After you sign in, you'll see the project's overview page.
+Once you've selected the project, at the top of the page, select **Label data**.
 
-Go to **View detailed instructions**. These instructions are specific to your project. They explain the type of data that you're facing, how you should make your decisions, and other relevant information. After you read this information, return to the project page and select **Start labeling**.
+You see instructions that are specific to your project. They explain the type of data that you're facing, how you should make your decisions, and other relevant information. After you read this information, at the top of the page select **Tasks**.  Or at the bottom of the page, select **Start labeling**.
 
 ## Common features of the labeling task
 

articles/machine-learning/tutorial-labeling.md

@@ -9,7 +9,7 @@ ms.topic: tutorial
 ms.author: sgilley
 author: sdgilley
 ms.reviewer: ranku
-ms.date: 04/02/2020
+ms.date: 04/09/2020
 
 # Customer intent: As a project administrator, I want to manage the process of labeling images so they can be used in machine learning models.
 # THIS ARTICLE SHOWS A SAS TOKEN THAT EXPIRES IN 2025
@@ -73,18 +73,6 @@ Azure Machine Learning datastores are used to store connection information, like
 
 1. Select **Create** to create the datastore.
 
-### Add labelers to workspace
-
-Set up your workspace to include all the people who will label data for any of your projects.  Later you'll add these labelers to your specific labeling project.
-
-1. On the left side, select **Data labeling**.
-
-1. At the top of the page, select **Labelers**.
-
-1. Select **Add labeler** to add the email address of a labeler.
-
-1. Continue to add more labelers until you're done.
-
 ### Create a labeling project
 
 Now that you have your list of labelers and access to the data you want to have labeled, create your labeling project.
@@ -140,51 +128,21 @@ Now that you have your list of labelers and access to the data you want to have
 
 This page doesn't automatically refresh. After a pause, manually refresh the page until the project's status changes to **Created**.
 
-### Add labelers to your project
-
-Add some or all of your labelers to this project.
-
-1. Select the project name to open the project.  
-
-1. At the top of the page, select **Teams**.
-
-1. Select the **labeling_tutorial Default Team** link.
-
-1. Now use **Assign labelers** to add the labelers you want to participate in this project. 
-
-1. Select from the list of labelers you created earlier.  Once you've selected all the labelers you wish to use, select **Assign labelers** to add them to your default project team.
-
 ## Start labeling
 
 You have now set up your Azure resources, and configured a data labeling project. It's time to add labels to your data.
 
-### Notify labelers
+### Tag the images
 
-If you have lots of images to label, hopefully you also have lots of labelers to complete the task.  You'll now want to send them instructions so they can access the data and start labeling.
+In this part of the tutorial, you'll switch roles from the *project administrator* to that of a *labeler*.  Anyone who has contributor access to your workspace can become a labeler.
 
 1. In [Machine Learning studio](https://ml.azure.com), select **Data labeling** on the left-hand side to find your project.  
 
-1. Select the project name link.
-
-1. At the top of the page, select **Details**.  You see a summary of your project.
-
-    ![Project details](media/tutorial-labeling/project-details.png)
-
-1. Copy the **Labeling portal URL** link to send to your labelers.
-
-1. Now select **Team** at the top to find your labeling team.  
-
-1. Select the team name link.
-
-1. At the top of the page, select **Email team** to start your email.  Paste in the labeling portal URL you just copied.  
-
-Each time a labeler goes to the portal URL, they'll be presented with more images to label, until the queue is empty.  
-
-### Tag the images
+1. Select the project name in the list.
 
-In this part of the tutorial, you'll switch roles from the *project administrator* to that of a *labeler*.  Use the URL you sent to the team.  This URL brings you to the labeling portal for your project.  If you had added instructions, you'd see them here when you arrive on the page.
+1. Below the project name, select **Label data**.
 
-1. At the top of the page, select **Tasks** to start labeling.
+1. Read the instructions, then select **Tasks**.
 
 1. Select a thumbnail image on the right to display the number of images you wish to label in one go. You must label all these images before you can move on. Only switch layouts when you have a fresh page of unlabeled data. Switching layouts clears the page's in-progress tagging work.