vision_unlearning.metrics.fid
Classes
!!! abstract "Usage Documentation" |
Module Contents
- class vision_unlearning.metrics.fid.FrechetInceptionDistance(/, **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.
- metrics: Literal['FID'] = ['FID']
- real_imgs_path: str | None = None
- gen_imgs_path: str | None = None
- real_imgs: List[torch.Tensor] | None = None
- gen_imgs: List[torch.Tensor] | None = None
- 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.
- verify_images_in_path(path: str) bool
Verifies if the given path contains image files. :param path: Path to the folder to check. :return: True if images are found, False otherwise.
- process_tensor_images(tensor_list: List[torch.Tensor])
- load_images_from_folder(folder_path: str, transform: torchvision.transforms.Compose) torch.Tensor
Loads all images from a folder, applies transformations, and returns them as a torch.Tensor. :param folder_path: Path to the folder containing images. :param transform: Transformations to apply to each image. :return: A torch.Tensor containing all images in the folder.
- score() Dict[str, float]