EventDrop

class tonic.transforms.EventDrop(sensor_size: Tuple[int, int, int])

Applies EventDrop transformation from the paper “EventDrop: Data Augmentation for Event-based Learning”.

Applies one of the 4 drops of event strategies between:

1. Identity (do nothing)

2. Drop events by time

3. Drop events by area

4. Drop events randomly

For each strategy, the ratio of dropped events are determined in the paper.

Parameters:

sensor_size (Tuple) – size of the sensor that was used [W,H,P]

Example

>>> transform = tonic.transforms.EventDrop(sensor_size=(128,128,2))