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DDD20 End-to-End Event Camera Driving Dataset

See https://sites.google.com/view/davis-driving-dataset-2020/home for details.

Software released as part of the publication

  • Hu, Y., Binas, J., Neil, D., Liu, S.-C., and Delbruck, T. (2020). "DDD20 End-to-End Event Camera Driving Dataset: Fusing Frames and Events with Deep Learning for Improved Steering Prediction". Special session Beyond Traditional Sensing for Intelligent Transportation, The 23rd IEEE International Conference on Intelligent Transportation Systems, September 20 – 23, 2020, Rhodes, Greece. arXiv [cs.CV]. arXiv. http://arxiv.org/abs/2005.08605

  • Binas, J., Neil, D., Liu, S.-C., and Delbruck, T. (2017). DDD17: End-To-End DAVIS Driving Dataset. in ICML’17 Workshop on Machine Learning for Autonomous Vehicles (MLAV 2017), Sydney, Australia. Available at: arXiv:1711.01458 [cs] http://arxiv.org/abs/1711.01458

Installation instructions using conda and Python 2.7

This project currently works with Python 2.7 under linux.

  1. First, create an Python 2.7 environment

    conda create -n ddd20 python=2.7

  2. Install all dependencies:

    pip install future
pip install numpy h5py opencv-python-headless openxc==0.15.0

  3. There is no step 3, have fun! 🎉

Usage:

See https://sites.google.com/view/davis-driving-dataset-2020/home for details

viewing

  • Play a file from the beginning

    $ python view.py <recorded_file.hdf5>

  • Play a file, starting at X percent

    $ python view.py <recorded_file.hdf5> X%

  • Play a file starting at second X

    $ python view.py <recorded_file.hdf5> Xs

Exporting raw data into standard data types

The DDD20 recordings are recorded using a custom data structure in HDF5. This design choice made the batch processing restricted without reformatting/exporting.

We prepared a script that can convert the original HDF5 recording into a nicer data strcture that user can directly work on.

$ python export_ddd20_hdf.py [-h] [--rotate ROTATE] filename

The newly exported file is an HDF5 file that is called filename.exported.hdf5. This file is saved at the same folder of the filename. This HDF5 file has a very simple structure, it has three datasets:

event: (N events x 4)  # each row is an event.
frame: (M frames x 260 x 346)
frame_ts: (M frames x 1)

Added now is option to turn off the display (thanks youkaichao) so that issue #4 can be resolved by simply adding the option:

python export_ddd20_hdf.py filename --display 0

Exporting to frame-based representation

$ python export.py [-h] [--tstart TSTART] [--tstop TSTOP] [--binsize BINSIZE]
                 [--update_prog_every UPDATE_PROG_EVERY]
                 [--export_aps EXPORT_APS] [--export_dvs EXPORT_DVS] [--display 0]
                 [--out_file OUT_FILE]
                 filename

License

This software is released under the GNU LESSER GENERAL PUBLIC LICENSE Version 3.