torcheval.metrics.StructuralSimilarity

class torcheval.metrics.StructuralSimilarity(device: Optional[device] = None)

Compute the structural similarity index (SSIM) between two sets of images.

Args: device (torch.device): The device where the computations will be performed.

If None, the default device will be used.

__init__(device: Optional[device] = None) → None

Initialize a metric object and its internal states.

Use self._add_state() to initialize state variables of your metric class. The state variables should be either torch.Tensor, a list of torch.Tensor, or a dictionary with torch.Tensor as values

Methods

__init__([device])	Initialize a metric object and its internal states.
compute()	Compute the mean of the mssim across all comparisons.
load_state_dict(state_dict[, strict])	Loads metric state variables from state_dict.
merge_state(metrics)	Merge the metric state with its counterparts from other metric instances.
reset()	Reset the metric state variables to their default value.
state_dict()	Save metric state variables in state_dict.
to(device, *args, **kwargs)	Move tensors in metric state variables to device.
update(images_1, images_2)	Update the metric state with new input.

Attributes

device

The last input device of Metric.to().