vision_unlearning.metrics.image_and_image

Classes

MetricImageImage

!!! abstract "Usage Documentation"

Module Contents

class vision_unlearning.metrics.image_and_image.MetricImageImage(/, **data: Any)

Bases: vision_unlearning.metrics.base.Metric

!!! abstract “Usage Documentation”

[Models](../concepts/models.md)

A base class for creating Pydantic models.

__class_vars__

The names of the class variables defined on the model.

__private_attributes__

Metadata about the private attributes of the model.

__signature__

The synthesized __init__ [Signature][inspect.Signature] of the model.

__pydantic_complete__

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__

The core schema of the model.

__pydantic_custom_init__

Whether the model has a custom __init__ function.

__pydantic_decorators__

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_generic_metadata__

A dictionary containing metadata about generic Pydantic models. The origin and args items map to the [__origin__][genericalias.__origin__] and [__args__][genericalias.__args__] attributes of [generic aliases][types-genericalias], and the parameter item maps to the __parameter__ attribute of generic classes.

__pydantic_parent_namespace__

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__

The name of the post-init method for the model, if defined.

__pydantic_root_model__

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__

The pydantic-core SchemaValidator used to validate instances of the model.

__pydantic_fields__

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.

__pydantic_computed_fields__

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_extra__

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to ‘allow’.

__pydantic_fields_set__

The names of fields explicitly set during instantiation.

__pydantic_private__

Values of private attributes set on the model instance.

_loss_alex: lpips.lpips.LPIPS | None
_loss_vgg: lpips.lpips.LPIPS | None
metrics: List[Literal['rmse', 'psnr', 'ssim', 'fsim', 'issm', 'sre', 'sam', 'uiq', 'lpips_alex', 'lpips_vgg']]
model_post_init(__context: dict | None = None) None

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

_evaluate_lpips(org_img_path: str, pred_img_path: str, loss_fn: lpips.lpips.LPIPS) float
_score_from_paths(org_img_path: str, pred_img_path: str) Dict[str, float]
static _pil_or_array_to_path(img: str | PIL.Image.Image | numpy.ndarray) tuple[str, bool]

Return (file_path, is_temp). Caller must unlink when is_temp is True.

score(org_img: str | PIL.Image.Image, pred_img: str | PIL.Image.Image) Dict[str, float]
score_batch(org_imgs: List[str | PIL.Image.Image], pred_imgs: List[str | PIL.Image.Image]) List[Dict[str, float]]

Warning: this function don’t improve performance. The underlying libraries still work serially. Returns per-pair results in the same order.