dataeval.data¶

Dataset organization tools: build views, filter, split, and reshape dataset views.

Classes¶

`ClassBalance`	Select a balanced subset of images based on class distribution.
`ClassFilter`	Select dataset indices based on class labels, keeping only those present in classes.
`DatasetSplits`	Output class containing test indices and a list of TrainValSplits.
`DetectionCrops`	Present an object-detection dataset’s ground-truth boxes as an image-classification dataset.
`Indices`	Selects only the given indices from the dataset.
`Limit`	Cap the dataset to the first `size` items currently selected.
`Operation`	Abstract base for a single step in a `View` pipeline.
`Relabel`	Conform a dataset’s class labels to a target vocabulary via a class mapping.
`Reverse`	Select dataset indices in reverse order.
`Shuffle`	Select dataset indices in a random order.
`TrainValSplit`	Dataclass containing train and validation indices.
`View`	Dataset view built from an ordered pipeline of `Operation`.

`build_tracks`	Build track dicts for a single target or an entire dataset.
`merge_datasets`	Concatenate datasets that share a label vocabulary into one dataset view.
`split_dataset`	Dataset splitting function. Returns a dataclass containing a list of train and validation indices.
`unzip_dataset`	Unzips a dataset into separate generators for images and targets.