Steven Leal eff6628f | 4 年前 | |
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.github | 4 年前 | |
.yamato | 4 年前 | |
TestProjects | 4 年前 | |
com.unity.perception | 4 年前 | |
.editorconfig | 5 年前 | |
.gitattributes | 5 年前 | |
.gitignore | 4 年前 | |
.npmignore | 5 年前 | |
CONTRIBUTING.md | 5 年前 | |
LICENSE.md | 4 年前 | |
README.md | 4 年前 | |
com.unity.perception.meta | 4 年前 |
README.md
Perception
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.
com.unity.perception is in active development. Its features and API are subject to significant change as development progresses.
Documentation
Setting up your first perception scene
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 checkGenerate all .csproj files.
- To get automatic feedback and fixups on formatting and naming convention violations, set up Rider/JetBrains with our Unity standard .dotsettings file by following these instructions.
- If you use VS Code, install the Editorconfig extension to get automatic code formatting according to our convention
License
Citation
If you find this package useful, consider citing it using:
@misc{com.unity.perception2020,
title={Unity {P}erception Package},
author={{Unity Technologies}},
howpublished={\url{https://github.com/Unity-Technologies/com.unity.perception}},
year={2020}
}