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CenterCrop#
CenterCrop
crops the events to a central size.
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers). Got range [0.0..2.0].
import tonic
nmnist = tonic.datasets.NMNIST("../../tutorials/data", train=False)
events, label = nmnist[0]
cropped_size = (18, 18)
transform = tonic.transforms.Compose(
[
tonic.transforms.CenterCrop(sensor_size=nmnist.sensor_size, size=cropped_size),
tonic.transforms.ToFrame(
sensor_size=(*cropped_size, 2),
time_window=10000,
),
]
)
frames = transform(events)
ani = tonic.utils.plot_animation(frames)
Total running time of the script: (0 minutes 2.606 seconds)