xrfeitoria 0.6.3

Description:

xrfeitoria 0.6.3

Introduction
XRFeitoria is a rendering toolbox for generating synthetic data photorealistic with ground-truth annotations.
It is a part of the OpenXRLab project.
https://github.com/openxrlab/xrfeitoria/assets/35397764/1e83bcd4-ae00-4c20-8188-3fe73f7c9c01
Major Features

Support rendering photorealistic images with ground-truth annotations.
Support multiple engine backends, including Unreal Engine and Blender.
Support assets/camera management, including import, place, export, and delete.
Support a CLI tool to render images from a mesh file.

Installation
pip install xrfeitoria

Requirements

Python >= 3.8
(optional) Unreal Engine >= 5.1

Windows
Linux
MacOS


(optional) Blender >= 3.0

Windows
Linux
MacOS



Get-Started
CLI
xf-render --help

# render a mesh file
xf-render {mesh_file}

# for example
wget https://graphics.stanford.edu/~mdfisher/Data/Meshes/bunny.obj
xf-render bunny.obj

https://github.com/openxrlab/xrfeitoria/assets/35397764/430a7264-9337-4327-838d-08e9a354c277
https://github.com/openxrlab/xrfeitoria/assets/35397764/9c029eb7-a8be-4d11-890e-b2499ff22caa
Documentation
The reference documentation is available on readthedocs.
Tutorials
There are several tutorials.
You can read them here.
Sample codes
There are several samples.
Please follow the instructions here.
Use plugins under development
Details can be found here.
If you want to publish plugins of your own, you can use the following command:
# install xrfeitoria first
cd xrfeitoria
pip install .

# build plugins for UE 5.1, UE 5.2, and UE 5.3 on Windows
python -m xrfeitoria.utils.publish_plugins build-unreal `
-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"

# build plugins for Blender
python -m xrfeitoria.utils.publish_plugins build-blender

Frequently Asked Questions
Please refer to FAQ.
:rocket: Amazing Projects Using XRFeitoria



Project
Teaser
Engine




SynBody: Synthetic Dataset with Layered Human Models for 3D Human Perception and Modeling

Unreal Engine / Blender


Zolly: Zoom Focal Length Correctly for Perspective-Distorted Human Mesh Reconstruction

Blender


SHERF: Generalizable Human NeRF from a Single Image

Blender


MatrixCity: A Large-scale City Dataset for City-scale Neural Rendering and Beyond

Unreal Engine


HumanLiff: Layer-wise 3D Human Generation with Diffusion Model

Blender


PrimDiffusion: Volumetric Primitives Diffusion for 3D Human Generation

Blender


WHAC: World-grounded Humans and Cameras

Unreal Engine



License
The 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 to LICENSE to view the full license.
Citation
If 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 OpenXRLab

XRPrimer: 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.