运行RADAR和LIDAR视频

# choose scene
my_scene_token = nusc.field2token('scene', 'name', 'scene-0049')[0]
scene_rec = nusc.get('scene',my_scene_token)

# save the picture which are load latter——只需一次
inf_list = nusc.save_sample_data(scene_rec['first_sample_token'], 'LIDAR_TOP')

# show picture
nusc.render_pointcloud_channel()

nuScenes devkit

Welcome to the devkit of the nuScenes dataset.

Overview

Changelog
Dataset download
Devkit setup
Tutorial
Object detection task
Frequently asked questions
Setting up a new virtual environment
Backward compatibility

Changelog

Dec. 20, 2018: Initial evaluation code released. See notes on backward compatibility.
Nov. 21, 2018: RADAR filtering and multi sweep aggregation.
Oct. 4, 2018: Code to parse RADAR data released.
Sep. 12, 2018: Devkit for teaser dataset released.

Dataset download

To download nuScenes you need to go to the Download page, create an account and confirm the nuScenes Terms of Use. After logging in you will see multiple archives for images, pointclouds and meta data. For the devkit to work you will need to download all archives. Please unpack the archives to the /data/nuscenes folder *without* overwriting folders that occur in multiple archives. Eventually you should have the following folder structure:

/data/nuscenes
    maps	-	Large image files (~500 Gigapixel) that depict the drivable surface and sidewalks in the scene.
    samples	-	Sensor data for keyframes.
    sweeps	-	Sensor data for intermediate frames.
    v0.1	-	JSON tables that include all the meta data and annotations.

If you want to use another folder, specify the dataroot parameter of the NuScenes class below.

Devkit setup

Download the devkit to your home directory using:

cd && git clone https://github.com/nutonomy/nuscenes-devkit.git

The devkit is tested for Python 3.7. To install Python 3.7 and set up a new virtual environment, you can look at these instructions. To install the required packages, run the following command in your favourite virtual environment:

pip install -r requirements.txt

Also add the python-sdk directory to your PYTHONPATH environmental variable, e.g. by adding the following to your ~/.virtualenvs/nuscenes/bin/postactivate (virtual environment) or ~/.bashrc (global):

export PYTHONPATH="${PYTHONPATH}:$HOME/nuscenes-devkit/python-sdk"

Tutorial

To get started with the nuScenes devkit, please run the tutorial as an IPython notebook:

jupyter notebook $HOME/nuscenes-devkit/python-sdk/tutorial.ipynb

In case you want to avoid downloading and setting up the data, you can also take a look at the rendered notebook on nuScenes.org. To learn more about the dataset, go to nuScenes.org or take a look at the database schema and annotator instructions.

Object detection task

For instructions related to the object detection task, the results format, classes and evaluation metrics, please refer to this readme.

Frequently asked questions

How come some objects visible in the camera images are not annotated? In the annotator instructions we specify that an object should only be annotated if it is covered by at least one LIDAR point. This is done to have precise location annotations, speedup the annotation process and remove faraway objects.
I have found an incorrect annotation. Can you correct it? Please make sure that the annotation is indeed incorrect according to the annotator instructions. Then send an email to nuScenes@nutonomy.com.
How can I use the RADAR data? We recently added features to parse and visualize RADAR point-clouds. More visualization tools will follow.
Why are there less sample pointclouds than samples? See this issue. Scenes 169 and 170 overlap and going forward we will remove scene 169.

Setting up a new virtual environment

It is recommended to install the devkit in a new virtual environment. Here are the steps you can follow to create one:

Python 3.7 installation

If you don't have Python 3.7 on your system, you can use the following steps to install it.

Ubuntu:

sudo add-apt-repository ppa:deadsnakes/ppa
sudo apt-get update
sudo apt-get install python3.7

Mac OS: Download from https://www.python.org/downloads/mac-osx/ and install.

Install virtualenvwrapper

pip install virtualenvwrapper

Add these two lines to ~/.bashrc (~/.bash_profile on MAC OS) to set the location where the virtual environments should live and the location of the script installed with this package:

export WORKON_HOME=$HOME/.virtualenvs
source [VIRTUAL_ENV_LOCATION]

Replace [VIRTUAL_ENV_LOCATION] with either /usr/local/bin/virtualenvwrapper.sh or ~/.local/bin/virtualenvwrapper.sh depending on where it is installed on your system.

After editing it, reload the shell startup file by running e.g. source ~/.bashrc.

Create the virtual environment

mkvirtualenv nuscenes --python [PYTHON_BINARIES]

PYTHON_BINARIES are typically at either /usr/local/bin/python3.7 or /usr/bin/python3.7.

Activating the virtual environment

If you are inside the virtual environment, your shell prompt should look like: (nuscenes) user@computer:~$ If that is not the case, you can enable the virtual environment using:

workon nuscenes

To deactivate the virtual environment, use:

deactivate

Backward compatibility

Dec. 20, 2018: We restructured the nuscenes-devkit code, which breaks backward compatibility. The new structure has a top-level package nuscenes which contains packages eval, export and utils. Therefor existing imports from nuscenes_utils should be replaced by nuscenes.nuscenes.

WJ-Lai / nuscenes-devkit