tfds_defect_detection.data# Module Contents# Classes# DatasetBuilder class tfds_defect_detection.data.DatasetBuilder(**data: Any)[source]# Bases: pydantic.BaseModel class Config[source]# arbitrary_types_allowed = True[source]# underscore_attrs_are_private = True[source]# property ds[source]# property num_classes[source]# property num_files[source]# anomaly_composition[source]# anomaly_size :Optional[int][source]# batch_size = 8[source]# color_dict[source]# create_artificial_anomalies = True[source]# crop_to_aspect_ratio = False[source]# drop_masks = False[source]# global_transform[source]# height = 256[source]# image_directory[source]# mask_directory :Optional[pathlib.Path][source]# pairing_mode :typing_extensions.Literal[result_only, result_with_original, result_with_contrastive_pair] = result_only[source]# peek = True[source]# process_deviation[source]# repeat = True[source]# seed = 123[source]# shuffle = True[source]# subset :typing_extensions.Literal[training, validation, ] = training[source]# validation_split = 0.2[source]# width = 256[source]# peek_dataset()[source]#