Metadata-Version: 2.4
Name: av2
Version: 0.3.6
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Rust
Requires-Dist: av
Requires-Dist: click
Requires-Dist: joblib
Requires-Dist: kornia
Requires-Dist: matplotlib
Requires-Dist: nox
Requires-Dist: numba
Requires-Dist: numpy
Requires-Dist: opencv-python
Requires-Dist: pandas
Requires-Dist: polars
Requires-Dist: pyarrow
Requires-Dist: pyproj
Requires-Dist: rich
Requires-Dist: scipy
Requires-Dist: torch
Requires-Dist: tqdm
Requires-Dist: universal-pathlib
Requires-Dist: black[jupyter] ; extra == 'lint'
Requires-Dist: mypy ; extra == 'lint'
Requires-Dist: ruff ; extra == 'lint'
Requires-Dist: pytest ; extra == 'test'
Requires-Dist: pytest-benchmark ; extra == 'test'
Requires-Dist: pytest-cov ; extra == 'test'
Provides-Extra: lint
Provides-Extra: test
License-File: LICENSE
License-File: NOTICE
Summary: Argoverse 2: Next generation datasets for self-driving perception and forecasting.
Keywords: argoverse,argoverse2,autonomous-driving,av1,av2,3d-object-detection,3d-scene-flow,4d-occupancy-forecasting,e2e-forecasting,motion-forecasting
Home-Page: https://github.com/argoverse/av2-api
Requires-Python: >=3.8
Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM
Project-URL: homepage, https://argoverse.org
Project-URL: repository, https://github.com/argoverse/av2-api

[![PyPI Versions](https://img.shields.io/pypi/pyversions/av2)](https://pypi.org/project/av2/)
![CI Status](https://github.com/argoai/av2-api/actions/workflows/ci.yml/badge.svg)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](./LICENSE)

# Argoverse 2

> _Official_ GitHub repository for the [Argoverse 2](https://www.argoverse.org) family of datasets.

<p align="center">
  <img src="https://argoverse.github.io/user-guide/assets/157802162-e40098c1-8677-4c16-ac60-e9bbded6badf.avif">
</p>

## Getting Started

Please see the [Argoverse User Guide](https://argoverse.github.io/user-guide/).

## Supported Datasets

- Argoverse 2 (AV2)

  - [Sensor](https://argoverse.github.io/user-guide/datasets/sensor.html)
  - [Lidar](https://argoverse.github.io/user-guide/datasets/lidar.html)
  - [Motion Forecasting](https://argoverse.github.io/user-guide/datasets/motion_forecasting.html)
  
- Trust, but Verify (TbV)
  - [Map Change Detection](https://argoverse.github.io/user-guide/datasets/map_change_detection.html)

## Supported Tasks

- Argoverse 2 (AV2)

  - [3D Object Detection](https://argoverse.github.io/user-guide/tasks/3d_object_detection.html)
  - [3D Scene Flow](https://argoverse.github.io/user-guide/tasks/3d_scene_flow.html)
  - [4D Occupancy Forecasting](https://argoverse.github.io/user-guide/tasks/4d_occupancy_forecasting.html)
  - [End-to-End Forecasting](https://argoverse.github.io/user-guide/tasks/e2e_forecasting.html)
  - [Motion Forecasting](https://argoverse.github.io/user-guide/tasks/motion_forecasting.html)
  - [Scenario Mining](https://argoverse.github.io/user-guide/tasks/scenario_mining.html)


## Citing

Please use the following citation when referencing the [Argoverse 2](https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/file/4734ba6f3de83d861c3176a6273cac6d-Paper-round2.pdf) _Sensor_, _Lidar_, or _Motion Forecasting_ Datasets:

```BibTeX
@INPROCEEDINGS { Argoverse2,
  author = {Benjamin Wilson and William Qi and Tanmay Agarwal and John Lambert and Jagjeet Singh and Siddhesh Khandelwal and Bowen Pan and Ratnesh Kumar and Andrew Hartnett and Jhony Kaesemodel Pontes and Deva Ramanan and Peter Carr and James Hays},
  title = {Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting},
  booktitle = {Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks (NeurIPS Datasets and Benchmarks 2021)},
  year = {2021}
}
```

Use the following citation when referencing the [Trust, but Verify](https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/file/6f4922f45568161a8cdf4ad2299f6d23-Paper-round2.pdf) _Map Change Detection_ Dataset:
```BibTeX
@INPROCEEDINGS { TrustButVerify,
  author = {John Lambert and James Hays},
  title = {Trust, but Verify: Cross-Modality Fusion for HD Map Change Detection},
  booktitle = {Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks (NeurIPS Datasets and Benchmarks 2021)},
  year = {2021}
}
```

