metadata

orchard.core.metadata

Dataset Metadata Package.

This package centralizes the specifications for all supported datasets. It serves as the single source of truth for the Orchard, ensuring that data dimensions, labels, and normalization constants are consistent across the entire pipeline.

DatasetMetadata

Bases: BaseModel

Immutable metadata container for a dataset entry.

Ensures dataset-specific constants are grouped and frozen throughout pipeline execution. Serves as static definition feeding into dynamic DatasetConfig.

Attributes:

Name	Type	Description
name	str	Short identifier (e.g., 'pathmnist', 'galaxy10').
display_name	str	Human-readable name for reporting.
md5_checksum	str	MD5 hash for download integrity verification.
url	str	Source URL for dataset download.
path	Path	Local path to the .npz archive.
classes	list[str]	Class labels in index order.
in_channels	int	Number of image channels (1=grayscale, 3=RGB).
native_resolution	int | None	Native pixel resolution (e.g., 28, 224).
mean	tuple[float, ...]	Channel-wise normalization mean.
std	tuple[float, ...]	Channel-wise normalization standard deviation.
is_anatomical	bool	Whether images have fixed anatomical orientation.
is_texture_based	bool	Whether classification relies on texture patterns.

normalization_info property

Formatted mean/std for reporting.

resolution_str property

Formatted resolution string (e.g., '28x28', '224x224').

num_classes property

Total number of target classes.

DatasetRegistryWrapper

Bases: BaseModel

Pydantic wrapper for multi-domain dataset registries.

Merges domain-specific registries (medical, space) based on the selected resolution and provides validated, deep-copied access to dataset metadata entries.

Attributes:

Name	Type	Description
resolution	int	Target dataset resolution (28, 32, 64, 128, or 224).
registry	dict[str, DatasetMetadata]	Deep-copied metadata registry for the selected resolution.

get_dataset(name)

Retrieves specific DatasetMetadata by name.

Parameters:

Name	Type	Description	Default
name	str	Dataset identifier	required

Returns:

Type	Description
DatasetMetadata	Deep copy of DatasetMetadata

Raises:

Type	Description
KeyError	If dataset not found in registry

Source code in orchard/core/metadata/wrapper.py

def get_dataset(self, name: str) -> DatasetMetadata:
    """
    Retrieves specific DatasetMetadata by name.

    Args:
        name: Dataset identifier

    Returns:
        Deep copy of DatasetMetadata

    Raises:
        KeyError: If dataset not found in registry
    """
    if name not in self.registry:
        available = list(self.registry.keys())
        raise KeyError(f"Dataset '{name}' not found. Available: {available}")

    return copy.deepcopy(self.registry[name])