ThreeET_Eyetracking

ThreeET_Eyetracking#

class tonic.datasets.ThreeET_Eyetracking(save_to: str, split: str = 'train', transform: Optional[Callable] = None, target_transform: Optional[Callable] = None, transforms: Optional[Callable] = None)[source]#

3ET DVS eye tracking 3ET

@article{chen20233et,
    title={3ET: Efficient Event-based Eye Tracking using a Change-Based ConvLSTM Network},
    author={Chen, Qinyu and Wang, Zuowen and Liu, Shih-Chii and Gao, Chang},
    journal={arXiv preprint arXiv:2308.11771},
    year={2023}
}
Parameters:

  • save_to (string) – Location to save files to on disk.

  • transform (callable, optional) – A callable of transforms to apply to the data.

  • split (string, optional) – The dataset split to use, train or val.

  • 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.

Returns:

A dataset object that can be indexed or iterated over. One sample returns a tuple of (events, targets).

__getitem__(index: int) → Tuple[Any, Any][source]#
Returns:

(events, target) where target is index of the target class.

Parameters:

index (int) –

Return type:

Tuple[Any, Any]

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