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Unity-Technologies / Com.unity.perception

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Perception toolkit for sim2real training and validation

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com.unity.perception is in active development. Its features and API are subject to significant change as development progresses.

Perception Package (Unity Computer Vision)

The Perception package provides a toolkit for generating large-scale datasets for computer vision training and validation. It is focused on a handful of camera-based use cases for now and will ultimately expand to other forms of sensors and machine learning tasks.

Visit the Unity Computer Vision page for more information on our tools and offerings!

Getting Started

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 computer vision data generation project, building a randomized Scene, and generating large-scale synthetic datasets by leveraging the power of Unity Simulation. No prior Unity experience required.

Human Pose Labeling and Randomization Tutorial
Step by step instructions for using the keypoint, pose, and animation randomization tools included in the Perception package. It is recommended that you finish Phase 1 of the Perception Tutorial above before starting this tutorial.


In-depth documentation on individual components of the package.

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

Example Projects


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 the Perception package could be used in a smart city or autonomous vehicle simulation. You can generate datasets locally or at scale in Unity Simulation.

Local development

The repository includes two projects for local development in TestProjects folder, one set up for HDRP and the other for URP.

Suggested IDE Setup

For closest standards conformity and best experience overall, JetBrains Rider or Visual Studio w/ JetBrains Resharper are suggested. For optimal experience, perform the following additional steps:

  • To allow navigating to code in all packages included in your project, in your Unity Editor, navigate to Edit -> Preferences... -> External Tools and check Generate all .csproj files.

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



For general questions or concerns please contact the Computer Vision team at [email protected].

For feedback, bugs, or other issues please file a GitHub issue and the Computer Vision team will investigate the issue as soon as possible.


If you find this package useful, consider citing it using:

    title={Unity {P}erception Package},
    author={{Unity Technologies}},
Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].