nuscenes-devkit | The devkit of the nuScenes dataset | Dataset library

by nutonomy Python Version: 1.1.11 License: Non-SPDX

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | nuscenes-devkit Summary

nuscenes-devkit is a Python library typically used in Artificial Intelligence, Dataset, Deep Learning, Numpy applications. nuscenes-devkit has no bugs, it has no vulnerabilities and it has medium support. However nuscenes-devkit build file is not available and it has a Non-SPDX License. You can install using 'pip install nuscenes-devkit' or download it from GitHub, PyPI.

The devkit of the nuScenes dataset.

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Quality

Security

License

Reuse

Support

nuscenes-devkit has a medium active ecosystem.

It has 1779 star(s) with 559 fork(s). There are 57 watchers for this library.

It had no major release in the last 12 months.

There are 3 open issues and 630 have been closed. On average issues are closed in 2 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of nuscenes-devkit is 1.1.11

Quality

nuscenes-devkit has 0 bugs and 0 code smells.

Security

nuscenes-devkit has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

nuscenes-devkit code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

nuscenes-devkit has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

nuscenes-devkit releases are available to install and integrate.

Deployable package is available in PyPI.

nuscenes-devkit has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

It has 13276 lines of code, 885 functions and 131 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed nuscenes-devkit and discovered the below as its top functions. This is intended to give you an instant insight into nuscenes-devkit implemented functionality, and help decide if they suit your requirements.

Convert scenes to Kitti
Transform a rotation matrix into a rotation matrix
Split log file into samples
Returns a list of eval boxes
Render a map in an image
Clips the points behind the given plane
Returns a dict of record names in layer_coords
Extracts a polygon
Render a scene
Render a scene channel channel
Loads evaluation boxes for a given box
Render numpy images
Validate submission
Render scenes on aancy map
Generate a histogram plot
Generate panoptic labels
Render a sample
Render geoposes on a scene
Export a scene pointcloud
Visualize a sample
Render a record
Render a scene channel
Construct a PointCloudCloud from a multisweweep
Get statistics for a single segment
Compute and return a TrackingMetrics object
Convert an annotation list to a dictionary

Get all kandi verified functions for this library.

nuscenes-devkit Key Features

No Key Features are available at this moment for nuscenes-devkit.

nuscenes-devkit Examples and Code Snippets

[ICRA2022] AutoPlace: Robust Place Recognition with Single-Chip Automotive Radar,1. Dataset preprocessing

Python

Lines of Code : 17

License : No License

Copy

cd autoplace/preprocess
./gene_woDTR.sh
./gene_wDTR.sh

dataset
├── 7n5s_xy11
│   ├── pcl_parameter.json
│   ├── img
│   ├── pcl
│   ├── rcs
│   ├── nuscenes_test.mat
│   ├── nuscenes_train.mat
│   ├── nuscenes_val.mat
│   ├── database.csv
│   ├── tr

Multi-Object Tracking with Poisson Multi-Bernoulli Mixture (PMBM) Filter,Using This Repo,Installation

Python

Lines of Code : 9

License : No License

Copy

git clone --recursive git@github.com:erikbohnsack/murty.git

mkdir build
cd build
cmake ..
make

git clone https://github.com/quan-dao/pmbm-filter

git clone https://github.com/nutonomy/nuscenes-devkit.git
cd nuscenes-devkit
pip install -r setup/requ

NuScenes Map to OpenStreetMap Exporter,Exporting the maps

Python

Lines of Code : 4

License : Permissive (BSD-3-Clause)

Copy

pip install -r requirements.txt

python nuscenes_map_to_osm_exporter.py ~/data/nuscenes

python nuscenes_to_osm_exporter.py ~/data/nuscenes v1.0-trainval

python nuscenes_to_gpx_exporter.py ~/data/nuscenes v1.0-trainval

Community Discussions

Trending Discussions on nuscenes-devkit

Reading Point Cloud .bin file using C++

QUESTION

Reading Point Cloud .bin file using C++

Asked 2021-Jan-05 at 00:13

I'm trying to read .bin point cloud files. I found this link suggesting a python code that I can convert to C++. I came up with the following code, but the precision of the floating point numbers are different compared to the results that I got from running the python code in the above link. I noticed that some coordinate values in the middle are totally missing, or in other words, the count of the floating point values that resulted from python is more than that of the C++ code:

...

ANSWER

Answered 2021-Jan-05 at 00:13

Here's a code that produces exactly the same output as the Python version:

Source https://stackoverflow.com/questions/65570879

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install nuscenes-devkit

We use a common devkit for nuScenes and nuImages. The devkit is tested for Python 3.6 and Python 3.7. To install Python, please check here.
To download nuImages you need to go to the Download page, create an account and agree to the nuScenes Terms of Use. For the devkit to work you will need to download at least the metadata and samples, the sweeps are optional. Please unpack the archives to the /data/sets/nuimages folder *without* overwriting folders that occur in multiple archives. Eventually you should have the following folder structure:. If you want to use another folder, specify the dataroot parameter of the NuImages class (see tutorial).
Please follow these steps to make yourself familiar with the nuImages dataset:.
Get the nuscenes-devkit code.
Run the tutorial using:
See the database schema and annotator instructions.
To download nuScenes you need to go to the Download page, create an account and agree to the nuScenes Terms of Use. After logging in you will see multiple archives. For the devkit to work you will need to download all archives. Please unpack the archives to the /data/sets/nuscenes folder *without* overwriting folders that occur in multiple archives. Eventually you should have the following folder structure:. If you want to use another folder, specify the dataroot parameter of the NuScenes class (see tutorial).
Please follow these steps to make yourself familiar with the nuScenes dataset:.
Read the dataset description.
Explore the lidar viewer and videos.
Download the dataset.
Get the nuscenes-devkit code.
Read the online tutorial or run it yourself using:
Read the nuScenes paper for a detailed analysis of the dataset.
Run the map expansion tutorial.
Take a look at the experimental scripts.
For instructions related to the object detection task (results format, classes and evaluation metrics), please refer to this readme.
See the database schema and annotator instructions.
See the FAQs.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: