cutcutcodec.core.nn.dataaug.image.RandomResizedCrop
- class cutcutcodec.core.nn.dataaug.image.RandomResizedCrop(shape: tuple[Integral, Integral] | list[Integral], win_area: tuple[Real, Real] | list[Real] | None = (1.0, 9.0))[source]
Resize and Crop an image to reach a final size.
It consists in random rescale and random cropping. It conserve the proportion of the input image.
Attributes
- shapetuple[int, int]
The output shape (readonly).
Examples
>>> import torch >>> from cutcutcodec.core.classes.frame_video import FrameVideo >>> from cutcutcodec.core.nn.dataaug.image import RandomResizedCrop >>> image = FrameVideo(0, torch.randint(0, 256, (480, 720, 3), dtype=torch.uint8)) >>> dataaug = RandomResizedCrop((16, 16)) >>> dataaug(image).shape (16, 16, 3) >>>
Initialise and create the class.
Parameters
- shapeint and int
The pixel dimensions of the final image. The convention adopted is the numpy convention (height, width).
- win_areafloat and float
The max and min ratio of the total surface by the window surface.