Merge pull request #242 from Unity-Technologies/Tutorial_patches_0.8.0

Tutorial patches for 0.8.0

Author: mkamalza

com.unity.perception/Documentation~/HPTutorial/TUTORIAL.md

@@ -2,7 +2,7 @@
 
 In this tutorial, we will walk through the production of keypoint and pose datasets for computer vision tasks such as human pose estimation and gesture recognition.
 
-We strongly recommend you finish [Phase 1 of the Perception Tutorial](../Tutorial/Phase1.md) before continuing with this one, especially if you do not have prior experience with Unity Editor. This tutorial requires at least version **0.7.0-preview.2** of the Perception package.
+We strongly recommend you finish [Phase 1 of the Perception Tutorial](../Tutorial/Phase1.md) before continuing with this one, especially if you do not have prior experience with Unity Editor. This tutorial requires at least version **0.8.0-preview.1** of the Perception package.
 
 In this tutorial, **":green_circle: Action:"** mark all of the actions needed to progress through the tutorial. If you are in a hurry, just follow the actions!
 
@@ -37,15 +37,15 @@ Your Scenario should now look like this:
 We now need to import the sample files required for this tutorial.  
 
 * **:green_circle: Action**: Open _**Package Manager**_ and select the Perception package, which should already be present in the navigation pane to the left side. 
-* **:green_circle: Action**: From the list of ***Samples*** for the Perception package, click on the ***Import into Project*** button for the sample bundle named _**Human Pose Estimation**_.
+* **:green_circle: Action**: From the list of ***Samples*** for the Perception package, click on the ***Import*** button for the sample bundle named _**Human Pose Labeling and Randomization**_.
 
 Once the sample files are imported, they will be placed inside the `Assets/Samples/Perception` folder in your Unity project, as seen in the image below:
 
 <p align="center">
 <img src="Images/project_folders_samples.png" width="600"/>
 </p>
 
-* **:green_circle: Action**: Select all of the assets inside the `Assets/Samples/Perception/<perception-package-version>/Human Pose Estimation/Models and Animations`.
+* **:green_circle: Action**: Select all of the assets inside the `Assets/Samples/Perception/<perception-package-version>/Human Pose Labeling and Randomization/Models and Animations`.
 * **:green_circle: Action**: In the _**Inspector**_ tab, navigate to the _**Rig**_ section. 
 
 Note how `Animation Type` is set to `Humanoid` for all selected assets. This is a requirement and makes sure all animations included in the sample `.fbx` files are ready to be used on a rigged humanoid model.

com.unity.perception/Documentation~/SetupSteps.md

@@ -5,7 +5,7 @@
 This page provides brief instructions on installing the Perception package. Head over to the [Perception Tutorial](Tutorial/TUTORIAL.md) for more detailed instructions and steps for building a sample project.
 
 
-1. Install the latest version of 2019.4.x or 2020.1.x Unity Editor from [here](https://unity3d.com/get-unity/download/archive). (Perception has not been tested on Unity versions newer than 2020.1)
+1. Install the latest version of **2020.2.x** Unity Editor from [here](https://unity3d.com/get-unity/download/archive). (The Perception package has not been fully tested on newer Unity versions)
 1. Create a new HDRP or URP project, or open an existing project.
 1. Open `Window` ->  `Package Manager`
 	1. In the Package Manager window find and click the ***+*** button in the upper lefthand corner of the window
@@ -14,6 +14,6 @@ This page provides brief instructions on installing the Perception package. Head
 
 Note that although the Perception package is compatible with both URP and HDRP, Unity Simulation currently only supports URP projects, therefore a URP project is recommended. 
 
-If you want a specific version of the package, append the version to the end of the "git URL". Ex. `com.unity.perception@0.1.0-preview.4`
+If you want a specific version of the package, append the version to the end of the "git URL". Ex. `com.unity.perception@0.8.0-preview.1`
 
 To install from a local clone of the repository, see [installing a local package](https://docs.unity3d.com/Manual/upm-ui-local.html) in the Unity manual.

com.unity.perception/Documentation~/Tutorial/Images/build_uploaded.png

@@ -20,30 +20,32 @@ In order to use Unity Simulation, you need to first create a Unity account or lo
 <img src="Images/cloud_icon.png" width="400"/>
 </p>
 
-If you have not logged in yet, the _**Services**_ tab will display a message noting that you are offline:
+* **:green_circle: Action** Click the ***General settings***.
+
+This will open the ***Services*** tab of the ***Project Settings*** window. If you have not logged in yet, you will see a message noting that you are signed out:
 
 <p align="center">
-<img src="Images/signin.png" width="400"/>
+<img src="Images/signin.png" width="600"/>
 </p>
 
-* **:green_circle: Action**: Click _**Sign in...**_ and follow the steps in the window that opens to sign in or create an account.
+* **:green_circle: Action**: Click _**Sign in...**_ and follow the steps in the window that opens to sign in or create a Unity account.
 * **:green_circle: Action**: Sign up for a free trial of Unity Simulation [here](https://unity.com/products/unity-simulation).
 
 Unity Simulation is a cloud-based service that makes it possible for you to run hundreds of instances of Unity builds in order to generate massive amounts of data. The Unity Simulation service is billed on a per-usage basis, and the free trial offers up to $100 of free credit per month. In order to access the free trial, you will need to provide credit card information. **This information will be used to charge your account if you exceed the $100 monthly credit.** A list of hourly and daily rates for various computational resources is available in the page where you first register for Unity Simulation.
 
-Once you have registered for a free trial, you will be taken to your Unity Simulation dashboard, where you will be able to observe your usage and billing invoices.
+Once you have registered for a free trial, you will be taken to your Unity Simulation dashboard, where you will be able to observe your usage and billing information.
 
 It is now time to connect your local Unity project to a cloud project.
 
-* **:green_circle: Action**: Return to Unity Editor. In the _**Services**_ tab click _**Select Organization**_ and choose the only available option (which typically has the same name as your Unity username).
+* **:green_circle: Action**: Return to Unity Editor. Click _**Select Organization**_ and choose the only available option (which typically has the same name as your Unity username).
 
-If you have used Unity before, you might have set-up multiple organizations for your account. In that case, choose whichever you would like to associate with this project.
+If you have used Unity before, you might have set up multiple organizations for your account. In that case, choose whichever you would like to associate with this project.
 
 <p align="center">
-<img src="Images/create_proj.png" width="400"/>
+<img src="Images/create_proj.png" width="600"/>
 </p>
 
-* **:green_circle: Action**: Click _**Create**_ to create a new cloud project and connect your local project to it.
+* **:green_circle: Action**: Click _**Create Project ID**_ to create a new cloud project and connect your local project to it.
 
 ### <a name="step-2">Step 2: Run Project on Unity Simulation</a> 
 
@@ -75,22 +77,21 @@ In order to make sure our builds are compatible with Unity Simulation, we need t
 <img src="Images/runinusim.png" width="600"/>
 </p>
 
-* **:green_circle: Action**: Choose `TutorialScene` (which is the Scene we have been working in) as your _**Main Scene**_ and the `SimulationScenario` object as your _**Scenario**_.
-
-Here, you can also specify a name for the run, the number of Iterations the Scenario will execute for, and the number of _**Instances**_ (number of nodes the work will be distributed across) for the run. 
+Here, you can also specify a name for the run, the number of Iterations the Scenario will execute for, and the number of _**Instances**_ (number of nodes the work will be distributed across) for the run. This window automatically picks the currently active Scene and Scenario to run in Unity Simulation.
 
 * **:green_circle: Action**: Name your run `FirstRun`, set the number of Iterations to `1000`, and Instances to `20`. 
 * **:green_circle: Action**: Click _**Build and Run**_.
 
-Your project will now be built and then uploaded to Unity Simulation. This may take a few minutes to complete, during which the editor may become frozen; this is normal behaviour.
+> :information_source: You can ignore the ***Optional Configuration*** section for now. This is useful if you plan to specify a configuration for your Scenario (including the Randomizers) that will override the values set in the Scenario UI, in Unity Simulation. To generate a configuration, you can click on the ***Generate JSON Config*** button provided in the ***Inspector*** view of Scenario components.
+
+Your project will now be built and then uploaded to Unity Simulation and run. This may take a few minutes to complete, during which the editor may become frozen; this is normal behaviour.
 
-* **:green_circle: Action**: Once the operation is complete, you can find the **Build ID**, **Run Definition ID**, and **Execution ID** of this Unity Simulation run in the _**Console**_ tab:
+* **:green_circle: Action**: Once the operation is complete, you can find the **Execution ID** of this Unity Simulation run in the **Console** tab and the ***Run in Unity Simulation** Window: 
 
 <p align="center">
-<img src="Images/build_uploaded.png"/>
+<img src="Images/build_uploaded.png" width="600"/>
 </p>
 
-
 ### <a name="step-3">Step 3: Keep Track of Your Runs Using the Unity Simulation Command-Line Interface</a> 
 
 To keep track of the progress of your Unity Simulation run, you will need to use Unity Simulation's command-line interface (CLI). Detailed instructions for this CLI are provided [here](https://github.com/Unity-Technologies/Unity-Simulation-Docs/blob/master/doc/quickstart.md#download-unity-simulation-quickstart-materials). For the purposes of this tutorial, we will only go through the most essential commands, which will help us know when our Unity Simulation run is complete and where to find the produced dataset.
@@ -322,4 +323,6 @@ The next couple of code blocks (under "Load dataset metadata") analyze the downl
 
 Follow the rest of the steps inside the notebook to generate a variety of plots and stats. Keep in mind that this notebook is provided just as an example, and you can modify and extend it according to your own needs using the tools provided by the [Dataset Insights framework](https://datasetinsights.readthedocs.io/en/latest/).
 
-This concludes the Perception Tutorial. The next step in this workflow would be to train an object-detection model using a dataset generated on Unity Simulation. It is important to note that the 1000 large dataset we generated here is probably not sufficiently large for training most models. We chose this number here so that the run would complete in a fairly short period of time, allowing us to move on to learning how to analyze the statistics of the dataset. In order to generate data for training, we recommend a dataset of about 400,000 captures. 
+The next step in this workflow, which is out of the scope of this tutorial, is to train an object-detection model using our synthetic dataset. It is important to note that the 1000 large dataset we generated here is probably not sufficiently large for training most models. We chose this number here so that the Unity Simulation run would finish quickly, allowing us to move on to learning how to analyze the statistics of the dataset. In order to generate data for training, we recommend a minimum dataset size of around 50,000 captures with a large degree of randomization. 
+
+This concludes the Perception Tutorial. In case of any issues or questions, please feel free to open a GitHub issue on the `com.unity.perception` repository so that the Unity Computer Vision team can get back to you as soon as possible.