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Update document, add a colab example for reading data, upgrade numpy dependency (#34)

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* Minor update to docs

* WIP

* adjust numpy requirement

* prepare example for reading data from SN dataset

* prepare example for reading data from SN dataset

* clean
This commit is contained in:
PENG Zhenghao
2023-10-18 14:32:01 -07:00
committed by GitHub
parent 5fa5c1070f
commit af9fe0a2aa
11 changed files with 3847 additions and 47 deletions
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README.md
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@@ -1,22 +1,34 @@
# ScenarioNet
**Open-Source Platform for Large-Scale Traffic Scenario Simulation and Modeling** [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/metadriverse/scenarionet/blob/main/tutorial/simulation.ipynb)
**Open-Source Platform for Large-Scale Traffic Scenario Simulation and Modeling**
[
[**Webpage**](https://metadriverse.github.io/scenarionet/) |
[**Code**](https://github.com/metadriverse/scenarionet) |
[**Video**](https://youtu.be/3bOqswXP6OA) |
[**Paper**](http://arxiv.org/abs/2306.12241) |
[**Documentation**](https://scenarionet.readthedocs.io/en/latest/) |
[**Colab Example**](https://colab.research.google.com/github/metadriverse/scenarionet/blob/main/tutorial/simulation.ipynb)
[**Documentation**](https://scenarionet.readthedocs.io/en/latest/)
]
ScenarioNet allows users to load scenarios from real-world dataset like Waymo, nuPlan, nuScenes, l5 and synthetic
dataset such as procedural generated ones and safety-critical ones generated by adversarial attack.
The built database provides tools for building training and test sets for ML applications.
Powered by [MetaDrive Simulator](https://github.com/metadriverse/metadrive), the scenarios can be reconstructed for
various applications like AD stack test, reinforcement learning, imitation learning, scenario generation and so on.
***Colab example for running simulation with ScenarioNet:***
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/metadriverse/scenarionet/blob/main/tutorial/simulation.ipynb)
***Colab example for reading established ScenarioNet dataset:***
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/metadriverse/scenarionet/blob/main/tutorial/read_established_scenarionet_dataset.ipynb)
ScenarioNet allows users to load scenarios from real-world datasets like Waymo, nuPlan,
nuScenes, l5 and synthetic dataset such as procedural generated ones and safety-critical
ones generated by adversarial attack. The built database provides tools for building
training and test sets for ML applications.
Powered by [MetaDrive Simulator](https://github.com/metadriverse/metadrive),
the scenarios can be reconstructed for various applications like AD stack test,
reinforcement learning, imitation learning, scenario generation and so on.
![system](docs/asset/system.png)
@@ -32,11 +44,13 @@ conda create -n scenarionet python=3.9
conda activate scenarionet
# Install MetaDrive Simulator
git clone git@github.com:metadriverse/metadrive.git
cd ~/ # Go to the folder you want to host these two repos.
git clone https://github.com/metadriverse/metadrive.git
cd metadrive
pip install -e.
# Install ScenarioNet
cd ~/ # Go to the folder you want to host these two repos.
git clone git@github.com:metadriverse/scenarionet.git
cd scenarionet
pip install -e .
@@ -50,7 +64,7 @@ If you already have ScenarioNet installed, you can check all operations by `pyth
## Citation
If you used this project in your research, please cite
If you used this project in your research, please cite:
```latex
@article{li2023scenarionet,
@@ -58,5 +72,5 @@ If you used this project in your research, please cite
author={Li, Quanyi and Peng, Zhenghao and Feng, Lan and Duan, Chenda and Mo, Wenjie and Zhou, Bolei and others},
journal={arXiv preprint arXiv:2306.12241},
year={2023}
}
}
```