Omniverse sample scripts - A guide for developing with Python scripts on NVIDIA Ominverse

Overview

Omniverse sample scripts

ここでは、NVIDIA Omniverse ( https://www.nvidia.com/ja-jp/omniverse/ ) のスクリプトのサンプルを貯めていってます。
Omniverseは、データ構造としてUSDを使用してます。
3Dモデルやシーンのファイルへの保存、読み込みでUSDが使用されるだけでなく、
Omniverse CreateやOmniverse ViewなどのOmniverseアプリのビュー上の制御もUSDを介して行われます(形状の表示/非表示の切り替えや移動など)。

ここでは、OmniverseアプリであるOmniverse CreateのScript Editorで試せるスクリプトのサンプルを用途別に列挙します。
Omniverse Create 2021.3.8で確認しました。

開発の参考サイト

Omniverseの情報は、Omniverse Launcherがポータルになっています。
ここのLEARNにチュートリアル動画やドキュメントなどが列挙されています。

NVIDIA Omniverse Developer Resource Center

https://developer.nvidia.com/nvidia-omniverse-developer-resource-center

Omniverse開発の入口となるサイトです。
全体的に何ができて何が重要か、というのは俯瞰して見ることができます。

はじめに

Omniverse Createで、メインメニューの [Window] - [Script Editor]を選択して、Script Editorを起動します。

omniverse_script_editor_01.png

この中でPythonを使用してプログラムを書きます。
左下のRunボタンを押すか、[Ctrl] +[Enter]キーを押すことで実行します。

以下、Pythonの初歩的な説明です。

コメント

1行のコメントの場合、"#"から行の末尾までがコメントになります。

# comment.

複数行の場合は、""" から """ までがコメントになります。

"""
comment.
line2.
"""

print

デバッグ用のメッセージはprintで記載します。

print('Hello Omniverse !')

学習のための知識

機能説明用のサンプル

サンプル 説明
Camera カメラ操作
Geometry ジオメトリの作成
Material マテリアルの割り当て
Math ベクトル/行列計算関連
Operation Ominverseの操作情報を取得/イベント処理
Physics Physics(物理)処理
pip_archive Pythonのよく使われるモジュールの使用
Prim USDのPrim(ノード)の操作
Rendering レンダリング画像の取得
Scene シーン情報の取得
Settings 設定の取得
System システム関連情報の取得
UI UI操作

ツール的なサンプル

サンプル 説明
Samples サンプルスクリプト

Extension

サンプル 説明
Extensions サンプルExtension
Owner
ft-lab (Yutaka Yoshisaka)
ft-lab (Yutaka Yoshisaka)
Code for 1st place solution in Sleep AI Challenge SNU Hospital

Sleep AI Challenge SNU Hospital 2021 Code for 1st place solution for Sleep AI Challenge (Note that the code is not fully organized) Refer to the notio

Saewon Yang 13 Jan 03, 2022
Applications using the GTN library and code to reproduce experiments in "Differentiable Weighted Finite-State Transducers"

gtn_applications An applications library using GTN. Current examples include: Offline handwriting recognition Automatic speech recognition Installing

Facebook Research 68 Dec 29, 2022
Aircraft design optimization made fast through modern automatic differentiation

Aircraft design optimization made fast through modern automatic differentiation. Plug-and-play analysis tools for aerodynamics, propulsion, structures, trajectory design, and much more.

Peter Sharpe 394 Dec 23, 2022
An NLP library with Awesome pre-trained Transformer models and easy-to-use interface, supporting wide-range of NLP tasks from research to industrial applications.

简体中文 | English News [2021-10-12] PaddleNLP 2.1版本已发布!新增开箱即用的NLP任务能力、Prompt Tuning应用示例与生成任务的高性能推理! 🎉 更多详细升级信息请查看Release Note。 [2021-08-22]《千言:面向事实一致性的生

6.9k Jan 01, 2023
OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network

Stock Price Prediction of Apple Inc. Using Recurrent Neural Network OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network Dataset:

Nouroz Rahman 410 Jan 05, 2023
✂️ EyeLipCropper is a Python tool to crop eyes and mouth ROIs of the given video.

EyeLipCropper EyeLipCropper is a Python tool to crop eyes and mouth ROIs of the given video. The whole process consists of three parts: frame extracti

Zi-Han Liu 9 Oct 25, 2022
LabelImg is a graphical image annotation tool.

LabelImgPlus LabelImg is a graphical image annotation tool. This project is not updated with new functions now. More functions are supported with Labe

lzx1413 200 Dec 20, 2022
(ICCV 2021) Official code of "Dressing in Order: Recurrent Person Image Generation for Pose Transfer, Virtual Try-on and Outfit Editing."

Dressing in Order (DiOr) 👚 [Paper] 👖 [Webpage] 👗 [Running this code] The official implementation of "Dressing in Order: Recurrent Person Image Gene

Aiyu Cui 277 Dec 28, 2022
Adaptable tools to make reinforcement learning and evolutionary computation algorithms.

Pearl The Parallel Evolutionary and Reinforcement Learning Library (Pearl) is a pytorch based package with the goal of being excellent for rapid proto

38 Jan 01, 2023
HTSeq is a Python library to facilitate processing and analysis of data from high-throughput sequencing (HTS) experiments.

HTSeq DEVS: https://github.com/htseq/htseq DOCS: https://htseq.readthedocs.io A Python library to facilitate programmatic analysis of data from high-t

HTSeq 57 Dec 20, 2022
SimDeblur is a simple framework for image and video deblurring, implemented by PyTorch

SimDeblur (Simple Deblurring) is an open source framework for image and video deblurring toolbox based on PyTorch, which contains most deep-learning based state-of-the-art deblurring algorithms. It i

220 Jan 07, 2023
AVD Quickstart Containerlab

AVD Quickstart Containerlab WARNING This repository is still under construction. It's fully functional, but has number of limitations. For example: RE

Carl Buchmann 3 Apr 10, 2022
Finetuning Pipeline

KLUE Baseline Korean(한국어) KLUE-baseline contains the baseline code for the Korean Language Understanding Evaluation (KLUE) benchmark. See our paper fo

74 Dec 13, 2022
Official NumPy Implementation of Deep Networks from the Principle of Rate Reduction (2021)

Deep Networks from the Principle of Rate Reduction This repository is the official NumPy implementation of the paper Deep Networks from the Principle

Ryan Chan 49 Dec 16, 2022
Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"

StrengthNet Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis" https://arxiv.org/abs/2110

RuiLiu 65 Dec 20, 2022
PyTorch implementation of Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets

Simple PyTorch Implementation of "Grokking" Implementation of Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets Usage Running

Teddy Koker 15 Sep 29, 2022
Model-based 3D Hand Reconstruction via Self-Supervised Learning, CVPR2021

S2HAND: Model-based 3D Hand Reconstruction via Self-Supervised Learning S2HAND presents a self-supervised 3D hand reconstruction network that can join

Yujin Chen 72 Dec 12, 2022
[PNAS2021] The neural architecture of language: Integrative modeling converges on predictive processing

The neural architecture of language: Integrative modeling converges on predictive processing Code accompanying the paper The neural architecture of la

Martin Schrimpf 36 Dec 01, 2022
CVPR 2021

Smoothing the Disentangled Latent Style Space for Unsupervised Image-to-image Translation [Paper] | [Poster] | [Codes] Yahui Liu1,3, Enver Sangineto1,

Yahui Liu 37 Sep 12, 2022
Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.

3D Infomax improves GNNs for Molecular Property Prediction Video | Paper We pre-train GNNs to understand the geometry of molecules given only their 2D

Hannes Stärk 95 Dec 30, 2022