torch_geometric.transforms.ToSLIC
- class ToSLIC(add_seg: bool = False, add_img: bool = False, **kwargs: Any)[source]
Bases:
BaseTransform
Converts an image to a superpixel representation using the
skimage.segmentation.slic()
algorithm, resulting in atorch_geometric.data.Data
object holding the centroids of superpixels indata.pos
and their mean color indata.x
(functional name:to_slic
).This transform can be used with any
torchvision
dataset.from torchvision.datasets import MNIST import torchvision.transforms as T from torch_geometric.transforms import ToSLIC transform = T.Compose([T.ToTensor(), ToSLIC(n_segments=75)]) dataset = MNIST('/tmp/MNIST', download=True, transform=transform)
- Parameters:
add_seg (bool, optional) – If set to True, will add the segmentation result to the data object. (default:
False
)add_img (bool, optional) – If set to True, will add the input image to the data object. (default:
False
)**kwargs (optional) – Arguments to adjust the output of the SLIC algorithm. See the SLIC documentation for an overview.