dataeval.data.Metadata¶
-
class dataeval.data.Metadata(dataset, *, continuous_factor_bins=
None, auto_bin_method='uniform_width', exclude=None, include=None)¶ Class containing binned metadata using Polars DataFrames.
- Parameters:¶
- dataset : ImageClassificationDataset or ObjectDetectionDataset¶
Dataset to access original targets and metadata from.
- continuous_factor_bins : Mapping[str, int | Sequence[float]] | None, default None¶
Mapping from continuous factor name to the number of bins or bin edges
- auto_bin_method : Literal["uniform_width", "uniform_count", "clusters"], default "uniform_width"¶
Method for automatically determining the number of bins for continuous factors
- exclude : Sequence[str] | None, default None¶
Filter metadata factors to exclude the specified factors, cannot be set with include
- include : Sequence[str] | None, default None¶
Filter metadata factors to include the specified factors, cannot be set with exclude
- add_factors(factors)¶
Add additional factors to the metadata.
The number of measures per factor must match the number of images in the dataset or the number of detections in the dataset.
- get_factors_by_type(factor_type)¶
Get the names of factors of a specific type.
- property auto_bin_method : 'uniform_width' | 'uniform_count' | 'clusters'¶
Binning method to use when continuous_factor_bins is not defined.
- Return type:¶
Literal[‘uniform_width’, ‘uniform_count’, ‘clusters’]
- property class_labels : numpy.typing.NDArray[numpy.intp]¶
Class labels as a NumPy array.
- Return type:¶
numpy.typing.NDArray[numpy.intp]
- property class_names : collections.abc.Sequence[str]¶
Class names as a list of strings.
- Return type:¶
Sequence[str]
- property continuous_factor_bins : Mapping[str, int | collections.abc.Sequence[float]]¶
Map of factor names to bin counts or bin edges.
- Return type:¶
Mapping[str, int | Sequence[float]]
- property dataframe : polars.DataFrame¶
Dataframe containing target information and metadata factors.
- Return type:¶
polars.DataFrame
- property discretized_data : numpy.typing.NDArray[numpy.int64]¶
Factor data with continuous data discretized.
- Return type:¶
numpy.typing.NDArray[numpy.int64]
- property dropped_factors : Mapping[str, collections.abc.Sequence[str]]¶
Factors that were dropped during preprocessing and the reasons why they were dropped.
- Return type:¶
Mapping[str, Sequence[str]]
- property factor_data : numpy.typing.NDArray[Any]¶
Factor data as a NumPy array.
- Return type:¶
numpy.typing.NDArray[Any]
- property factor_info : Mapping[str, FactorInfo]¶
Factor types of the metadata.
- Return type:¶
Mapping[str, FactorInfo]
- property factor_names : collections.abc.Sequence[str]¶
Factor names of the metadata.
- Return type:¶
Sequence[str]