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Unity Perception Package Documentation (com.unity.perception)

Preview package

This package is available as a preview, so it is not ready for production use. The features and documentation in this package might change before it is verified for release.

Visit the pages below for in-depth documentation on inidividual components of the package.

Feature Description
Labeling A component that marks a GameObject and its descendants with a set of labels
LabelConfig An asset that defines a taxonomy of labels for ground truth generation
Perception Camera Captures RGB images and ground truth from a Camera.
DatasetCapture Ensures sensors are triggered at proper rates and accepts data for the JSON dataset.
Randomization (Experimental) The Randomization tool set lets you integrate domain randomization principles into your simulation.

Known issues

  • The Linux Editor 2019.4.7f1 and 2019.4.8f1 might hang when importing HDRP-based Perception projects. For Linux Editor support, use 2019.4.6f1 or 2020.1

Other Resources

Quick Installation Instructions
Get your local Perception workspace up and running quickly. Recommended for users with prior Unity experience.

Perception Tutorial
Detailed instructions covering all the important steps from installing Unity Editor, to creating your first Perception project, building a randomized Scene, and generating large-scale synthetic datasets by leveraging the power of Unity Simulation. No prior Unity experience required.

Example projects using Perception

SynthDet

SynthDet is an end-to-end solution for training a 2D object detection model using synthetic data.

Unity Simulation Smart Camera example

The Unity Simulation Smart Camera Example illustrates how Perception could be used in a smart city or autonomous vehicle simulation. You can generate datasets locally or at scale in Unity Simulation.