Merge remote-tracking branch 'origin/aisv647_visualizations' into aisv647_visualizations

.yamato/publish.yml

 {% metadata_file .yamato/environments.yml %}
 
 ---
-{% for variant in package_variants %}
+
-  name: Publish {{ variant.name }} package to internal registry
+  name: Publish Perception package to internal registry
   agent:
     type: Unity::VM
     image: package-ci/win10:stable
   triggers:
     tags:
       only:
-        - "/^(r|R)(c|C)-+(-preview(+)?)?$/"
+        - /^(r|R)(c|C)-\d+\.\d+\.\d+(-preview(\.\d+)?)?$/
-    - .yamato/upm-ci-full.yml#pack_{{ variant.name }}
-    {% for editor in test_editors %}
-    {% for platform in test_platforms %}
-    - .yamato/upm-ci-full.yml#pkg_test_{{variant.name}}_{{platform.name}}_{{editor.version}}
+    - .yamato/upm-ci-full.yml#pack_Perception
+    {% for editor in publish_editors %}
+    {% for platform in publish_platforms %}
+    {% for suite in suites %}
+    {% for project in projects %}
+    - .yamato/upm-ci-full.yml#pkg_test_Perception_{{platform.name}}_{{editor.version}}
+    - .yamato/upm-ci-testprojects.yml#{{project.name}}_windows_{{suite.name}}_{{editor.version}}
+    {% endfor %}
+    {% endfor %}
-{% endfor %}
+

.yamato/promote.yml

     {% for platform in publish_platforms %}
     {% for suite in suites %}
     {% for project in projects %}
-    {% for variant in package_variants %}
-    - .yamato/upm-ci-full.yml#pkg_test_{{variant.name}}_{{platform.name}}_{{editor.version}}
+    - .yamato/upm-ci-full.yml#pkg_test_Perception_{{platform.name}}_{{editor.version}}
-    {% endfor %}
     {% endfor %}
     {% endfor %}
     {% endfor %}

TestProjects/PerceptionHDRP/Assets/IdLabelConfig.asset

   m_Name: IdLabelConfig
   m_EditorClassIdentifier: Unity.Perception.Runtime:UnityEngine.Perception.GroundTruth:IdLabelConfig
   m_LabelEntries:
-  - label: Box
+  - label: Crate
-  - label: Crate
+  - label: Box
     id: 3
   autoAssignIds: 1
   startingLabelId: 1

TestProjects/PerceptionHDRP/Assets/Scenes/SampleScene.unity

         asm: Unity.Perception.Runtime}
       data:
         enabled: 1
-        foldout: 0
-        labelingConfiguration: {fileID: 11400000, guid: be3971a848968144e8d07d9136a5bf49,
+        idLabelConfig: {fileID: 11400000, guid: 034ffd4e09ffb7348b2fe6634259058a,
           type: 2}
     00000001:
       type: {class: SemanticSegmentationLabeler, ns: UnityEngine.Perception.GroundTruth,
-        foldout: 0
+        m_TargetTextureOverride: {fileID: 0}
-        foldout: 0
-        m_LabelingConfiguration: {fileID: 11400000, guid: be3971a848968144e8d07d9136a5bf49,
+        m_LabelConfig: {fileID: 11400000, guid: 034ffd4e09ffb7348b2fe6634259058a,
           type: 2}
     00000003:
       type: {class: RenderedObjectInfoLabeler, ns: UnityEngine.Perception.GroundTruth,
-        foldout: 0
-        labelingConfiguration: {fileID: 11400000, guid: be3971a848968144e8d07d9136a5bf49,
+        idLabelConfig: {fileID: 11400000, guid: 034ffd4e09ffb7348b2fe6634259058a,
           type: 2}
 --- !u!1 &1640252278
 GameObject:

TestProjects/PerceptionURP/Assets/ExampleScripts/CustomAnnotationAndMetricReporter.cs

 [RequireComponent(typeof(PerceptionCamera))]
 public class CustomAnnotationAndMetricReporter : MonoBehaviour
 {
-    public GameObject light;
+    public GameObject targetLight;
     public GameObject target;
 
     MetricDefinition lightMetricDefinition;
     public void Update()
     {
         //Report the light's position by manually creating the json array string.
-        var lightPos = light.transform.position;
+        var lightPos = targetLight.transform.position;
         DatasetCapture.ReportMetric(lightMetricDefinition,
             $@"[{{ ""x"": {lightPos.x}, ""y"": {lightPos.y}, ""z"": {lightPos.z} }}]");
         //compute the location of the object in the camera's local space

com.unity.perception/CHANGELOG.md

 ### Removed
 
 ### Fixed
+Fixed compilation warnings with latest com.unity.simulation.core package.
 
 ### Security
 

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

 
 [Setting up your first perception scene](GettingStarted.md)
 
+## Example projects using Perception
+
+### SynthDet
+
+<img src="images/synthdet.png"/>
+
+[SynthDet](https://github.com/Unity-Technologies/SynthDet) is an end-to-end solution for training a 2d object detection model using synthetic data.
+
+### Unity Simulation Smart Camera Example
+<img src="images/smartcamera.png"/>
+
+The [Unity Simulation Smart Camera Example](https://github.com/Unity-Technologies/Unity-Simulation-Smart-Camera-Outdoor) illustrates how Perception could be used in a smart city or autonomous vehicle simulation. Datasets can be generated locally or at scale in [Unity Simulation](https://unity.com/products/unity-simulation).
+
 ## Package contents
 
 |Feature|Description

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

 1. Select your project's `ScriptableRenderer` asset and open the inspector window. In most projects it is located at `Assets/Settings/ForwardRenderer.asset`.
 2. Click `Add Renderer Feature` and select `Ground Truth Renderer Feature`
 
-<img src="images/ScriptableRendererStep.PNG" align="middle"/>
+<img src="images/ScriptableRendererStep.png" align="middle"/>
 
 ## Step 3: Create a new scene and camera
 
    1. In the inspector panel of the main camera select Add Component
    2. Add a **Perception Camera** component
 
-<img src="images/MainCameraConfig.PNG" align="middle"/>
+<img src="images/PerceptionCameraFinished.png" align="middle"/>
 
 ## Step 4: Create labeled objects
 
 
 <img src="images/CompletedScene.PNG" align="middle"/>
 
-1. On each cube, from the inspector panel add a **Labeling** component
-   1. Click the **+**
-   2. In the text field add the name of the object i.e Crate. This will be the label used in the semantic segmentation images
-      <img src="images/LabeledObject.PNG" align="middle"/>
-2. In the Project panel right click -> Perception -> Labeling Configuration
-3. Select the new **Labeling Configuration**
-   1. Click the **+**
-   2. In the label text field add the same text that the Label script contains on the objects created in the scene (i.e Cube, Box, Crate)
-   3. Add a numerical value to the value field
+5. On each cube, from the inspector panel add a **Labeling** component 
+	1. Click the **+**
+	2. In the text field add the name of the object i.e Crate. This will be the label used in the semantic segmentation images 
-      Make sure the labels all have different values, for this example use increments of 10,000 to ensure they show up as very distinct colors in the segmentation images
+<img src="images/LabeledObject.PNG" align="middle"/>
-<img src="images/LabelingConfigurationFinished.PNG" align="middle"/>
+6. In the Project panel right click -> Perception -> Labeling Configuration
+7. Select the new **ID Label Config**
+	1. Click the **+**
+	2. In the label text field add the same text that the Label script contains on the objects created in the scene (i.e Cube, Box, Crate)
+		
+<img src="images/IDLabelingConfigurationFinished.PNG" align="middle"/>
-1. Select the Main Camera in the Hierarchy panel
-2. In the Perception Camera attach the Labeling Configuration created in previous step
+8. Select the Main Camera in the Hierarchy panel 
+9. In the Perception Camera attach the ID Label Config created in previous step for each ID Label config 
-<img src="images/MainCameraConfig.PNG" align="middle"/>
+<img src="images/MainCameraLabelConfig.PNG" align="middle"/>
 
 ## Step 5: Run simulation and generate dataset
 

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

 [RequireComponent(typeof(PerceptionCamera))]
 public class CustomAnnotationAndMetricReporter : MonoBehaviour
 {
-    public GameObject light;
+    public GameObject targetLight;
     public GameObject target;
 
     MetricDefinition lightMetricDefinition;
     public void Update()
     {
         //Report the light's position by manually creating the json array string.
-        var lightPos = light.transform.position;
+        var lightPos = targetLight.transform.position;
         DatasetCapture.ReportMetric(lightMetricDefinition,
             $@"[{{ ""x"": {lightPos.x}, ""y"": {lightPos.y}, ""z"": {lightPos.z} }}]");
         //compute the location of the object in the camera's local space

com.unity.perception/Runtime/GroundTruth/Labelers/SemanticSegmentationLabeler.cs

                 height = targetTexture.height,
                 path = localPath
             };
-            asyncRequest.Start((r) =>
+            asyncRequest.Enqueue((r) =>
             {
                 Profiler.BeginSample("Encode");
                 var pngBytes = ImageConversion.EncodeArrayToPNG(r.data.data.ToArray(), GraphicsFormat.R8G8B8A8_UNorm, (uint)r.data.width, (uint)r.data.height);
                 r.data.data.Dispose();
                 return AsyncRequest.Result.Completed;
             });
+            asyncRequest.Execute();
         }
 
         /// <inheritdoc/>

com.unity.perception/Runtime/GroundTruth/PerceptionCamera.cs

 
         bool m_CapturedLastFrame;
         Ego m_EgoMarker;
+
+#pragma warning disable 414
+#pragma warning restore 414
 
         static PerceptionCamera s_VisualizedPerceptionCamera;
         static GameObject s_VisualizationCamera;

com.unity.perception/Runtime/GroundTruth/SimulationState_Json.cs

                     PendingCaptures = pendingCapturesToWrite,
                     SimulationState = this
                 };
-                req.Start(r =>
+                req.Enqueue(r =>
+                req.Execute(AsyncRequest.ExecutionContext.JobSystem);
             }
 
             m_SerializeCapturesSampler.End();
                     MetricFileIndex = m_MetricsFileIndex,
                     PendingMetrics = pendingMetricsToWrite
                 };
-                req.Start(r =>
+                req.Enqueue(r =>
+                req.Execute();
             }
 
             m_MetricsFileIndex++;

com.unity.perception/Tests/Editor/DatasetCaptureEditorTests.cs

 using NUnit.Framework;
 using UnityEngine.Perception.GroundTruth;
 
-namespace GroundTruth
+namespace GroundTruthTests
 {
     public class DatasetCaptureEditorTests
     {

com.unity.perception/Tests/Runtime/GroundTruthTests/SegmentationGroundTruthTests.cs

 using NUnit.Framework;
 using Unity.Collections;
 using UnityEngine;
-using UnityEngine.Experimental.Rendering;
-using UnityEngine.Rendering.HighDefinition;
-using UnityEngine.Experimental.Rendering;
-using UnityEngine.UIElements;
 using Object = UnityEngine.Object;
 
 namespace GroundTruthTests
         [UnityTest]
         public IEnumerator SemanticSegmentationPass_WithTextureOverride_RendersToOverride()
         {
-            int timesSegmentationImageReceived = 0;
             var expectedPixelValue = new Color32(0, 0, 255, 255);
             var targetTextureOverride = new RenderTexture(2, 2, 1, RenderTextureFormat.R8);
 

com.unity.perception/package.json

     "displayName": "Perception", 
     "name": "com.unity.perception", 
     "unity": "2019.3", 
-    "version": "0.1.0-preview.4"
+    "version": "0.3.0-preview.1"
 }

TestProjects/PerceptionHDRP/Assets/csc.rsp

+-warnaserror+

TestProjects/PerceptionHDRP/Assets/csc.rsp.meta

+fileFormatVersion: 2
+guid: b590f0b421136b44098ad7e92fc45f3e
+DefaultImporter:
+  externalObjects: {}
+  userData: 
+  assetBundleName: 
+  assetBundleVariant: 

TestProjects/PerceptionURP/Assets/csc.rsp

+-warnaserror+

TestProjects/PerceptionURP/Assets/csc.rsp.meta

+fileFormatVersion: 2
+guid: 1800f44b598c0b647bf3fad2f5c9b957
+DefaultImporter:
+  externalObjects: {}
+  userData: 
+  assetBundleName: 
+  assetBundleVariant: 

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

+* [Installation Instructions](SetupSteps.md)
+* [Getting Started](GettingStarted.md)
+* [Labeling](GroundTruth-Labeling.md)
+* [Perception Camera](PerceptionCamera.md)
+* [Dataset Capture](DatasetCapture.md)

com.unity.perception/Documentation~/filter.yml

+apiRules:
+  - exclude:
+      uidRegex: Tests$
+      type: Namespace
+  - exclude:
+      uidRegex: Tests
+      type: Type