torchvision.utils

torchvision.utils.make_grid(tensor, nrow=8, padding=2, normalize=False, range=None, scale_each=False, pad_value=0)

Make a grid of images.

Parameters

• tensor (Tensor or list) – 4D mini-batch Tensor of shape (B x C x H x W) or a list of images all of the same size.

• nrow (int, optional) – Number of images displayed in each row of the grid. The final grid size is (B / nrow, nrow). Default: 8.

• padding (int, optional) – amount of padding. Default: 2.

• normalize (bool, optional) – If True, shift the image to the range (0, 1), by the min and max values specified by range. Default: False.

• range (tuple, optional) – tuple (min, max) where min and max are numbers, then these numbers are used to normalize the image. By default, min and max are computed from the tensor.

• scale_each (bool, optional) – If True, scale each image in the batch of images separately rather than the (min, max) over all images. Default: False.

• pad_value (float, optional) – Value for the padded pixels. Default: 0.

Example

See this notebook here

torchvision.utils.save_image(tensor, filename, nrow=8, padding=2, normalize=False, range=None, scale_each=False, pad_value=0)

Save a given Tensor into an image file.

Parameters

• tensor (Tensor or list) – Image to be saved. If given a mini-batch tensor, saves the tensor as a grid of images by calling make_grid.

• **kwargs – Other arguments are documented in make_grid.