neodroidvision.data.mixed.penn_fudan.PennFudanDataset

class neodroidvision.data.mixed.penn_fudan.PennFudanDataset(root: Union[str, Path], split: SplitEnum = SplitEnum.training, return_variant: PennFudanReturnVariantEnum = PennFudanReturnVariantEnum.binary)

Bases: SupervisedDataset

description

__init__(root: Union[str, Path], split: SplitEnum = SplitEnum.training, return_variant: PennFudanReturnVariantEnum = PennFudanReturnVariantEnum.binary)

Parameters

• root –

• split –

Methods

__init__(root[, split, return_variant])	param root
get_all(idx)	Return all info including bounding boxes for each instance
get_binary(idx)	Return a single binary channel target for all instances in image
get_instanced(idx)	Return a separate channel target for each instance in image
get_transforms(split)	param split
get_tuple_transforms(split)	param split

Attributes

categories
image_size
image_size_T
predictor_channels
predictor_shape	return: :rtype:
response_channels_binary
response_channels_instanced
response_channels_two_classes
response_shape	return: :rtype:
split_names	return: :rtype:

class PennFudanReturnVariantEnum(value)

Bases: Enum

Return binary mask, instanced or all annotations

get_all(idx)

Return all info including bounding boxes for each instance

Parameters

idx –

Returns

Return type

get_binary(idx)

Return a single binary channel target for all instances in image

Parameters

idx –

Returns

Return type

get_instanced(idx)

Return a separate channel target for each instance in image

Parameters

idx –

Returns

Return type

static get_transforms(split: SplitEnum)

Parameters

split –

Returns

Return type

static get_tuple_transforms(split: SplitEnum)

Parameters

split –

Returns

Return type

property predictor_shape: Tuple[int, ...]

return: :rtype:

property response_shape: Tuple[int, ...]

return: :rtype:

property split_names: Dict[SplitEnum, str]

return: :rtype: