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

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

Related tags

Overview

the people's comma

the paper

the comma.ai driving dataset

Examples

Downloading the dataset

Dataset structure

Requirements

Hiring

Credits

Owner

comma.ai

Official implementation of Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models at NeurIPS 2021

Unofficial implementation of Google "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization" in PyTorch

Sequence to Sequence Models with PyTorch

thundernet ncnn

This repo contains source code and materials for the TEmporally COherent GAN SIGGRAPH project.

Open source annotation tool for machine learning practitioners.

Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product Operators

List of papers, code and experiments using deep learning for time series forecasting

'Aligned mixture of latent dynamical systems' (amLDS) for stimulus decoding probabilistic manifold alignment across animals. P. Herrero-Vidal et al. NeurIPS 2021 code.

Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park, Rares Ambrus, Vitor Guizilini, Jie Li, and Adrien Gaidon.

BEAMetrics: Benchmark to Evaluate Automatic Metrics in Natural Language Generation

Implemenets the Contourlet-CNN as described in C-CNN: Contourlet Convolutional Neural Networks, using PyTorch

Unofficial pytorch implementation of the paper "Dynamic High-Pass Filtering and Multi-Spectral Attention for Image Super-Resolution"

Source code of the paper PatchGraph: In-hand tactile tracking with learned surface normals.

Official repository of "DeepMIH: Deep Invertible Network for Multiple Image Hiding", TPAMI 2022.

Workshop Materials Delivered on 28/02/2022

Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

Pseudo-Visual Speech Denoising

Code for KDD'20 "An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph"

PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation (TPAMI).

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

Related tags

Overview

the people's comma

the paper

the comma.ai driving dataset

Examples

Downloading the dataset

Dataset structure

Requirements

Hiring

Credits

Owner

comma.ai

Official implementation of Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models at NeurIPS 2021

Unofficial implementation of Google "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization" in PyTorch

Sequence to Sequence Models with PyTorch

thundernet ncnn

This repo contains source code and materials for the TEmporally COherent GAN SIGGRAPH project.

Open source annotation tool for machine learning practitioners.

Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product Operators

List of papers, code and experiments using deep learning for time series forecasting

'Aligned mixture of latent dynamical systems' (amLDS) for stimulus decoding probabilistic manifold alignment across animals. P. Herrero-Vidal et al. NeurIPS 2021 code.

Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park*, Rares Ambrus*, Vitor Guizilini, Jie Li, and Adrien Gaidon.

BEAMetrics: Benchmark to Evaluate Automatic Metrics in Natural Language Generation

Implemenets the Contourlet-CNN as described in C-CNN: Contourlet Convolutional Neural Networks, using PyTorch

Unofficial pytorch implementation of the paper "Dynamic High-Pass Filtering and Multi-Spectral Attention for Image Super-Resolution"

Source code of the paper PatchGraph: In-hand tactile tracking with learned surface normals.

Official repository of "DeepMIH: Deep Invertible Network for Multiple Image Hiding", TPAMI 2022.

Workshop Materials Delivered on 28/02/2022

Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

Pseudo-Visual Speech Denoising

Code for KDD'20 "An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph"

PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation (TPAMI).

Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park, Rares Ambrus, Vitor Guizilini, Jie Li, and Adrien Gaidon.