In this tutorial, we will generate synthetic data intended for detecting 10 everyday grocery items. These grocery items were imported into your project when you imported the tutorial files from the _**Package Manager**_, and are located in the folder `Assets/Samples/Perception/0.6.0-preview.1/Tutorial Files/Foreground Objects/Phase 1/Prefabs`.
The label configuration we have created (`TutorialIdLabelConfig`) is of type `IdLabelConfig`, and is compatible with three of the four labelers we have attached to our `Perception Camera`. This type of label configuration carries a unique numerical ID for each label. However, `SemanticSegmentationLabeler` requires a different kind of label configuration which includes unique colors for each label instead of numerical IDs. This is because the output of this labeler are images in which each visible foreground object is painted in a unique color.
The label configuration we have created (`TutorialIdLabelConfig`) is of type `IdLabelConfig`, and is compatible with three of the four labelers we have attached to our `Perception Camera`. This type of label configuration carries a unique numerical ID for each label. However, `SemanticSegmentationLabeler` requires a different kind of label configuration which includes unique colors for each label instead of numerical IDs. This is because the output of this labeler is a set of images in which each visible foreground object is painted in a unique color.
* **Action**: In the _**Project**_ tab, right-click the `Assets` folder, then click _**Create -> Perception -> Semantic Segmentation Label Config**_. Name this asset `TutorialSemanticSegmentationLabelConfig`.
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