Research - dataset and code for 2016 paper Learning a Driving Simulator

Related tags

Deep Learningresearch
Overview

the people's comma

the paper

Learning a Driving Simulator

the comma.ai driving dataset

7 and a quarter hours of largely highway driving. Enough to train what we had in Bloomberg.

Examples

We present two Machine Learning Experiments to show possible ways to use this dataset:

Training a steering angle predictor

Training a generative image model

Downloading the dataset

./get_data.sh

or get it at archive.org comma dataset

45 GB compressed, 80 GB uncompressed

dog/2016-01-30--11-24-51 (7.7G)
dog/2016-01-30--13-46-00 (8.5G)
dog/2016-01-31--19-19-25 (3.0G)
dog/2016-02-02--10-16-58 (8.1G)
dog/2016-02-08--14-56-28 (3.9G)
dog/2016-02-11--21-32-47 (13G)
dog/2016-03-29--10-50-20 (12G)
emily/2016-04-21--14-48-08 (4.4G)
emily/2016-05-12--22-20-00 (7.5G)
frodo/2016-06-02--21-39-29 (6.5G)
frodo/2016-06-08--11-46-01 (2.7G)

Dataset referenced on this page is copyrighted by comma.ai and published under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. This means that you must attribute the work in the manner specified by the authors, you may not use this work for commercial purposes and if you alter, transform, or build upon this work, you may distribute the resulting work only under the same license.

Dataset structure

The dataset consists of 10 videos clips of variable size recorded at 20 Hz with a camera mounted on the windshield of an Acura ILX 2016. In parallel to the videos we also recorded some measurements such as car's speed, acceleration, steering angle, GPS coordinates, gyroscope angles. See the full log list here. These measurements are transformed into a uniform 100 Hz time base.

The dataset folder structure is the following:

+-- dataset
|   +-- camera
|   |   +-- 2016-04-21--14-48-08
|   |   ...
|   +-- log
|   |   +-- 2016-04-21--14-48-08
|   |   ...

All the files come in hdf5 format and are named with the time they were recorded. The camera dataset has shape number_frames x 3 x 160 x 320 and uint8 type. One of the log hdf5-datasets is called cam1_ptr and addresses the alignment between camera frames and the other measurements.

Requirements

anaconda
tensorflow-0.9
keras-1.0.6
cv2

Hiring

Want a job at comma.ai?

Show us amazing stuff on this dataset

Credits

Riccardo Biasini, George Hotz, Sam Khalandovsky, Eder Santana, and Niel van der Westhuizen

Owner
comma.ai
Make driving chill
comma.ai
Using Streamlit to host a multi-page tool with model specs and classification metrics, while also accepting user input values for prediction.

Predicitng_viability Using Streamlit to host a multi-page tool with model specs and classification metrics, while also accepting user input values for

Gopalika Sharma 1 Nov 08, 2021
Code for the paper "Curriculum Dropout", ICCV 2017

Curriculum Dropout Dropout is a very effective way of regularizing neural networks. Stochastically "dropping out" units with a certain probability dis

Pietro Morerio 21 Jan 02, 2022
Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space"

Sparse Steerable Convolution (SS-Conv) Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and

25 Dec 21, 2022
yolox_backbone is a deep-learning library and is a collection of YOLOX Backbone models.

YOLOX-Backbone yolox-backbone is a deep-learning library and is a collection of YOLOX backbone models. Install pip install yolox-backbone Load a Pret

Yonghye Kwon 21 Dec 28, 2022
Chess reinforcement learning by AlphaGo Zero methods.

About Chess reinforcement learning by AlphaGo Zero methods. This project is based on these main resources: DeepMind's Oct 19th publication: Mastering

Samuel 2k Dec 29, 2022
[ICCV 2021] Official Pytorch implementation for Discriminative Region-based Multi-Label Zero-Shot Learning SOTA results on NUS-WIDE and OpenImages

Discriminative Region-based Multi-Label Zero-Shot Learning (ICCV 2021) [arXiv][Project page coming soon] Sanath Narayan*, Akshita Gupta*, Salman Kh

Akshita Gupta 54 Nov 21, 2022
PyTorch code for Composing Partial Differential Equations with Physics-Aware Neural Networks

FInite volume Neural Network (FINN) This repository contains the PyTorch code for models, training, and testing, and Python code for data generation t

Cognitive Modeling 20 Dec 18, 2022
Official implementation of NLOS-OT: Passive Non-Line-of-Sight Imaging Using Optimal Transport (IEEE TIP, accepted)

NLOS-OT Official implementation of NLOS-OT: Passive Non-Line-of-Sight Imaging Using Optimal Transport (IEEE TIP, accepted) Description In this reposit

Ruixu Geng(耿瑞旭) 16 Dec 16, 2022
Repository for self-supervised landmark discovery

self-supervised-landmarks Repository for self-supervised landmark discovery Requirements pytorch pynrrd (for 3d images) Usage The use of this models i

Riddhish Bhalodia 2 Apr 18, 2022
Official implement of Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer

Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer This repository contains the PyTorch code for Evo-ViT. This work proposes a slow-fas

YifanXu 53 Dec 05, 2022
SAAVN - Sound Adversarial Audio-Visual Navigation,ICLR2022 (In PyTorch)

SAAVN SAAVN Code release for paper "Sound Adversarial Audio-Visual Navigation,IC

YinfengYu 10 Aug 30, 2022
Convert weight file.pth to weight file.blob

CONVERT YOUR MODEL TO IR FORMAT INSTALLATION OpenVino Toolkit Download openvinotoolkit 2021.3 version : Link Instruction of installation : Link Pytorc

Tran Anh Tuan 3 Nov 18, 2021
Code for the paper Learning the Predictability of the Future

Learning the Predictability of the Future Code from the paper Learning the Predictability of the Future. Website of the project in hyperfuture.cs.colu

Computer Vision Lab at Columbia University 139 Nov 18, 2022
Code in conjunction with the publication 'Contrastive Representation Learning for Hand Shape Estimation'

HanCo Dataset & Contrastive Representation Learning for Hand Shape Estimation Code in conjunction with the publication: Contrastive Representation Lea

Computer Vision Group, Albert-Ludwigs-Universität Freiburg 38 Dec 13, 2022
BMW TechOffice MUNICH 148 Dec 21, 2022
Honours project, on creating a depth estimation map from two stereo images of featureless regions

image-processing This module generates depth maps for shape-blocked-out images Install If working with anaconda, then from the root directory: conda e

2 Oct 17, 2022
Consistency Regularization for Adversarial Robustness

Consistency Regularization for Adversarial Robustness Official PyTorch implementation of Consistency Regularization for Adversarial Robustness by Jiho

40 Dec 17, 2022
Pytorch implementation of Straight Sampling Network For Point Cloud Learning (ICIP2021).

Pytorch code for SS-Net This is a pytorch implementation of Straight Sampling Network For Point Cloud Learning (ICIP2021). Environment Code is tested

Sun Ran 1 May 18, 2022
ICCV2021 Oral SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks

Sign-Agnostic Convolutional Occupancy Networks Paper | Supplementary | Video | Teaser Video | Project Page This repository contains the implementation

64 Jan 05, 2023
Code for paper Novel View Synthesis via Depth-guided Skip Connections

Novel View Synthesis via Depth-guided Skip Connections Code for paper Novel View Synthesis via Depth-guided Skip Connections @InProceedings{Hou_2021_W

8 Mar 14, 2022