Package: xrfeitoria
IntroductionXRFeitoria is a rendering toolbox for generating synthetic data photorealistic with ground-truth annotations.
It is a part of theOpenXRLabproject.https://github.com/openxrlab/xrfeitoria/assets/35397764/1e83bcd4-ae00-4c20-8188-3fe73f7c9c01Major FeaturesSupport rendering photorealistic images with ground-truth annotations.Support multiple engine backends, includingUnreal EngineandBlender.Support assets/camera management, including import, place, export, and delete.Support a CLI tool to render images from a mesh file.InstallationpipinstallxrfeitoriaRequirementsPython >= 3.8(optional)Unreal Engine >= 5.1WindowsLinuxMacOS(optional)Blender >= 3.0WindowsLinuxMacOSGet-StartedCLIxf-render--help# render a mesh filexf-render{mesh_file}# for examplewgethttps://graphics.stanford.edu/~mdfisher/Data/Meshes/bunny.obj
xf-renderbunny.objhttps://github.com/openxrlab/xrfeitoria/assets/35397764/430a7264-9337-4327-838d-08e9a354c277https://github.com/openxrlab/xrfeitoria/assets/35397764/9c029eb7-a8be-4d11-890e-b2499ff22caaDocumentationThe reference documentation is available onreadthedocs.TutorialsThere are severaltutorials.
You can read themhere.Sample codesThere are severalsamples.
Please follow the instructionshere.Use plugins under developmentDetails can be foundhere.If you want to publish plugins of your own, you can use the following command:# install xrfeitoria firstcdxrfeitoriapipinstall.# for instance, build plugins for Blender, UE 5.1, UE 5.2, and UE 5.3 on Windows.# using powershell where backtick(`) is the line continuation character.python-mxrfeitoria.utils.publish_plugins`-u"C:/Program Files/Epic Games/UE_5.1/Engine/Binaries/Win64/UnrealEditor-Cmd.exe"`-u"C:/Program Files/Epic Games/UE_5.2/Engine/Binaries/Win64/UnrealEditor-Cmd.exe"`-u"C:/Program Files/Epic Games/UE_5.3/Engine/Binaries/Win64/UnrealEditor-Cmd.exe"Frequently Asked QuestionsPlease refer toFAQ.:rocket: Amazing Projects Using XRFeitoriaProjectTeaserEngineSynBody: Synthetic Dataset with Layered Human Models for 3D Human Perception and ModelingUnreal Engine / BlenderZolly: Zoom Focal Length Correctly for Perspective-Distorted Human Mesh ReconstructionBlenderSHERF: Generalizable Human NeRF from a Single ImageBlenderMatrixCity: A Large-scale City Dataset for City-scale Neural Rendering and BeyondUnreal EngineHumanLiff: Layer-wise 3D Human Generation with Diffusion ModelBlenderPrimDiffusion: Volumetric Primitives Diffusion for 3D Human GenerationBlenderLicenseThe license of our codebase is Apache-2.0. Note that this license only applies to code in our library, the dependencies of which are separate and individually licensed. We would like to pay tribute to open-source implementations to which we rely on. Please be aware that using the content of dependencies may affect the license of our codebase. Refer toLICENSEto view the full license.CitationIf you find this project useful in your research, please consider cite:@misc{xrfeitoria,title={OpenXRLab Synthetic Data Rendering Toolbox},author={XRFeitoria Contributors},howpublished={\url{https://github.com/openxrlab/xrfeitoria}},year={2023}}Projects in OpenXRLabXRPrimer: OpenXRLab foundational library for XR-related algorithms.XRSLAM: OpenXRLab Visual-inertial SLAM Toolbox and Benchmark.XRSfM: OpenXRLab Structure-from-Motion Toolbox and Benchmark.XRLocalization: OpenXRLab Visual Localization Toolbox and Server.XRMoCap: OpenXRLab Multi-view Motion Capture Toolbox and Benchmark.XRMoGen: OpenXRLab Human Motion Generation Toolbox and Benchmark.XRNeRF: OpenXRLab Neural Radiance Field (NeRF) Toolbox and Benchmark.XRFeitoria: OpenXRLab Synthetic Data Rendering Toolbox.