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.gitignore

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/.download
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**/Build/**
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**/Builds/**
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/utr

.yamato/environments.yml

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# sticking to 2019.4.6f1 for testing for now because Linux Editor fails to open PerceptionHDRP on 2019.4.8f1
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# see https://fogbugz.unity3d.com/default.asp?1273518_d68j5lb6eucglb84
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coverage_editors:
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- version: 2019.4.6f1
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- version: 2019.4.18f1
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per_commit_editors:
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- version: 2019.4.6f1
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- version: 2019.4.18f1
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# - version: 2020.1.15f1
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performance_editors:
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- version: 2019.4.6f1
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- version: 2020.1.3f1
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- version: 2019.4.18f1
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# - version: 2020.1.3f1
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complete_editors:
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- version: 2019.4.6f1
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- version: 2019.4.18f1
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# - version: 2020.1.15f1
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# - version: 2020.2.0a21
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.yamato/upm-ci-performance.yml

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---
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{% for editor in complete_editors %}
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{% for editor in performance_editors %}
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{% for suite in performance_suites %}
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{% for project in projects %}
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{{project.name}}_linux_{{suite.name}}_{{editor.version}}:
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{% endfor %}
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{% endfor %}
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{% for editor in complete_editors %}
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{% for editor in performance_editors %}
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{% for suite in performance_suites %}
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{% for project in projects %}
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{{project.name}}_windows_{{suite.name}}_{{editor.version}}:
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name : {{project.name}} {{ suite.display_name }} performance tests ({{ editor.version }}, Windows)
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agent:
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type: Unity::VM::GPU
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model: rtx2080
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image: package-ci/win10:stable
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image: graphics-foundation/win10-dxr:stable
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flavor: b1.large
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commands:
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- git submodule update --init --recursive

LICENSE.md

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com.unity.perception copyright © 2020 Unity Technologies ApS
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com.unity.perception copyright © 2021 Unity Technologies ApS
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Apache License
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Version 2.0, January 2004

README.md

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<img src="com.unity.perception/Documentation~/images/banner2.PNG" align="middle"/>
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# Perception
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The Perception package provides a toolkit for generating large-scale datasets for perception-based machine learning 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.
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![ReleaseBadge](https://badge-proxy.cds.internal.unity3d.com/5ab9a162-9dd0-4ba1-ba41-cf25378a927a)
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[![license badge](https://img.shields.io/badge/license-Apache--2.0-green.svg)](LICENSE.md)
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> com.unity.perception is in active development. Its features and API are subject to significant change as development progresses.
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## Documentation
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# Perception Package (Unity Computer Vision)
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The Perception package provides a toolkit for generating large-scale datasets for perception-based machine learning 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.
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## Getting Started
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**[Quick Installation Instructions](com.unity.perception/Documentation~/SetupSteps.md)**
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Get your local Perception workspace up and running quickly. Recommended for users with prior Unity experience.
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**[Perception Tutorial](com.unity.perception/Documentation~/Tutorial/TUTORIAL.md)**
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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.
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## Documentation
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In-depth documentation on inidividual components of the package.
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[Quick Installation Instructions](com.unity.perception/Documentation~/SetupSteps.md)
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|Feature|Description|
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|---|---|
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|[Labeling](com.unity.perception/Documentation~/GroundTruthLabeling.md)|A component that marks a GameObject and its descendants with a set of labels|
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|[Label Config](com.unity.perception/Documentation~/GroundTruthLabeling.md#label-config)|An asset that defines a taxonomy of labels for ground truth generation|
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|[Perception Camera](com.unity.perception/Documentation~/PerceptionCamera.md)|Captures RGB images and ground truth from a [Camera](https://docs.unity3d.com/Manual/class-Camera.html).|
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|[Dataset Capture](com.unity.perception/Documentation~/DatasetCapture.md)|Ensures sensors are triggered at proper rates and accepts data for the JSON dataset.|
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|[Randomization (Experimental)](com.unity.perception/Documentation~/Randomization/Index.md)|The Randomization tool set lets you integrate domain randomization principles into your simulation.|
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[Perception Tutorial](com.unity.perception/Documentation~/Tutorial/TUTORIAL.md): 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.
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## Example Projects
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[Perception Manual](com.unity.perception/Documentation~/index.md): Sample projects and documentation of the SDK.
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### SynthDet
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<img src="com.unity.perception/Documentation~/images/synthdet.png"/>
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[SynthDet](https://github.com/Unity-Technologies/SynthDet) is an end-to-end solution for training a 2D object detection model using synthetic data.
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### Unity Simulation Smart Camera example
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<img src="com.unity.perception/Documentation~/images/smartcamera.png"/>
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The [Unity Simulation Smart Camera Example](https://github.com/Unity-Technologies/Unity-Simulation-Smart-Camera-Outdoor) illustrates how the Perception toolset could be used in a smart city or autonomous vehicle simulation. You can generate datasets locally or at scale in [Unity Simulation](https://unity.com/products/unity-simulation).
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## Local development
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The repository includes two projects for local development in `TestProjects` folder, one set up for HDRP and the other for URP.
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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:
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* 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.`
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## Known issues
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* 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
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## License
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* [License](com.unity.perception/LICENSE.md)
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## Support
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For general questions or concerns please contact the Computer Vision team at [email protected].
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For feedback, bugs, or other issues please file a GitHub issue and the Computer Vision team will investigate the issue as soon as possible.
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## Citation
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If you find this package useful, consider citing it using:
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```
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@misc{com.unity.perception2020,
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@misc{com.unity.perception2021,
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title={Unity {P}erception Package},
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author={{Unity Technologies}},
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howpublished={\url{https://github.com/Unity-Technologies/com.unity.perception}},
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TestProjects/PerceptionHDRP/Packages/manifest.json

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TestProjects/PerceptionHDRP/Packages/packages-lock.json

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"url": "https://packages.unity.com"
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"url": "https://packages.unity.com"
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"version": "1.0.5",
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"com.unity.mathematics": {
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"dependencies": {},
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"dependencies": {
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"com.unity.simulation.core": "0.0.10-preview.21"
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"com.unity.platforms": {
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"dependencies": {
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"com.unity.simulation.core": "0.0.10-preview.21"
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TestProjects/PerceptionHDRP/ProjectSettings/PackageManagerSettings.asset

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m_Script: {fileID: 13960, guid: 0000000000000000e000000000000000, type: 0}
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m_EditorClassIdentifier:
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m_EditorVersion: 2019.4.12f1
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m_EditorVersionWithRevision: 2019.4.12f1 (225e826a680e)
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m_EditorVersion: 2019.4.16f1
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m_EditorVersionWithRevision: 2019.4.16f1 (e05b6e02d63e)

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