---
# System prepended metadata

title: 'Generate Synthetic Data of Dynamic Environments With a Custom Isaac Sim-Based Framework [S51570]'
tags: [GTC2023]

---

---
title: Generate Synthetic Data of Dynamic Environments With a Custom Isaac Sim-Based Framework [S51570]
tags: GTC2023
description: Nvidia 2023 GTC session
---

# Generate Synthetic Data of Dynamic Environments With a Custom Isaac Sim-Based Framework [S51570]

# Nvidia issac sim
## Grade
 GRADE is a system I developed to seamlessly manage the Isaac Sim simulation software to Generate Realistic Animated Dynamic Environments for Robotics Research.
 
![image](https://github.com/shaung08/GTC2023/raw/main/Generate%20Synthetic%20Data%20of%20Dynamic%20Environments%20With%20a%20Custom%20Isaac%20Sim-Based%20Framework%20%5BS51570%5D/img/img01.png)


### grade main componets
1. Readlistic Environmnets
2. Animaton Assets
3. Custom robots
4. A Customizable pipeline
5. Additional processing tools

### grade software pipeline
1. create environment
* Blender
* Unreal Engine
* Digital twin
2. Convert to USD format
3. Load it into Isaac Sim
4. Using sdk to set environment and camera to generate dataset

#### Verify
yolo people detection:
1. Train on synthetic data -> fine tune on S-coco dataset and full coco dataset
2. Train on S-coco dataset and full coco dataset

**Result: 1. is more accurate than 2.**

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## 參考
*  [https://github.com/eliabntt/GRADE-RR](https://github.com/eliabntt/GRADE-RR)

## Thank you! :dash:
You can find me on
- GitHub: https://github.com/shaung08
- Email: a2369875@gmail.com
