dataeval.metrics.stats.VisualStatsOutput¶

class dataeval.metrics.stats.VisualStatsOutput¶

Output class for visualstats() stats metric.

brightness¶

Brightness of the images

contrast¶

Image contrast ratio

darkness¶

Darkness of the images

sharpness¶

Sharpness of the images

percentiles¶

Percentiles of the pixel values of the images with quartiles of (0, 25, 50, 75, 100)

data()¶

The output data as a dictionary.

factors(filter=None, exclude_constant=False)¶

Returns all 1-dimensional data as a dictionary of numpy arrays.

Parameters:¶

filter : str, Sequence[str] or None, default None:¶: If provided, only returns keys that match the filter.
exclude_constant : bool, default False¶: If True, exclude arrays that contain only a single unique value.

Return type:¶

Mapping[str, NDArray[Any]]

get_channel_mask(channel_index, channel_count=None)¶

Boolean mask for results filtered to specified channel index and optionally the count of the channels per image.

Parameters:¶

channel_index : int | Iterable[int] | None¶: Index or indices of channel(s) to filter for
channel_count : int | Iterable[int] | None¶: Optional count(s) of channels to filter for

Return type:¶

collections.abc.Sequence[bool]

meta()¶

Metadata about the execution of the function or method for the Output class.

Plots the statistics as a set of histograms.

Parameters:¶

log : bool¶: If True, plots the histograms on a logarithmic scale.
channel_limit : int or None¶: The maximum number of channels to plot. If None, all channels are plotted.
channel_index : int, Iterable[int] or None¶: The index or indices of the channels to plot. If None, all channels are plotted.

Return type:¶

matplotlib.Figure

to_dataframe()¶

Returns the processed factors a polars dataframe of shape (factors, samples)