tonic.datasets.mvsec#

Module Contents#

Classes#

MVSEC

MVSEC

class tonic.datasets.mvsec.MVSEC(save_to: str, scene: str, transform: Optional[Callable] = None, target_transform: Optional[Callable] = None, transforms: Optional[Callable] = None)[source]#

Bases: tonic.dataset.Dataset

MVSEC

@article{zihao2018multi,
  title={The Multi Vehicle Stereo Event Camera Dataset: An Event Camera Dataset for 3D Perception},
  author={Zihao Zhu, Alex and Thakur, Dinesh and Ozaslan, Tolga and Pfrommer, Bernd and Kumar, Vijay and Daniilidis, Kostas},
  journal={arXiv e-prints},
  pages={arXiv--1801},
  year={2018}
}
Parameters:
  • save_to (string) – Location to save files to on disk.

  • scene (string) – Choose one of 4 scenes: outdoor_night, outdoor_day, indoor_flying, motorcycle. If you already have the data on your system, make sure to place the .bag files in a subfolder ‘MVSEC/{scene}/bag_files.bag’.

  • transform (callable, optional) – A callable of transforms to apply to events and / or images for both left and right cameras.

  • target_transform (callable, optional) – A callable of transforms to apply to the targets/labels.

  • transforms (callable, optional) – A callable of transforms that is applied to both data and labels at the same time.

resources#
base_url = 'http://visiondata.cis.upenn.edu/mvsec/'#
sensor_size = (346, 260, 2)#
dtype#
ordering#
__getitem__(index)[source]#
Returns:

tuple of (data, targets), where data is another tuple of (events_left, events_right, imu_left, imu_right, images_left, images_right) and targets is a tuple of (depth_rect_left, depth_rect_right, pose) for ground truths.

__len__()[source]#
download()[source]#

Downloads from a given url, places into target folder and verifies the file hash.