torchvision.utils¶

torchvision.utils.make_grid(tensor: Union[torch.Tensor, List[torch.Tensor]], nrow: int = 8, padding: int = 2, normalize: bool = False, range: Union[Tuple[int, int], NoneType] = None, scale_each: bool = False, pad_value: int = 0) → torch.Tensor[source]

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: Union[torch.Tensor, List[torch.Tensor]], fp: Union[str, pathlib.Path, BinaryIO], nrow: int = 8, padding: int = 2, normalize: bool = False, range: Union[Tuple[int, int], NoneType] = None, scale_each: bool = False, pad_value: int = 0, format: Union[str, NoneType] = None) → None[source]

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. fp (string or file object) – A filename or a file object format (Optional) – If omitted, the format to use is determined from the filename extension. If a file object was used instead of a filename, this parameter should always be used. **kwargs – Other arguments are documented in make_grid.