ImageBatch

Methods

This are most important functions to be used for image classes

ImageBatch.project(coordinates[, crs_s, ...])	Calculate projection of 3d points into image.
ImageBatch.map_center_point([mapper, ...])	Map center point of image to 3d
ImageBatch.map_footprint([points_per_edge, ...])	Map footprint of images of batch to 3d
ImageBatch.add_images(images)	Add images to the batch.

class weitsicht.ImageBatch(images: dict[str, ImageBase], mapper: MappingBase | None = None)

Container for running operations on a set of named images.

Parameters:

• images (dict[str, ImageBase])

• mapper (MappingBase | None)

__init__(images: dict[str, ImageBase], mapper: MappingBase | None = None)

Initialize an image batch.

Parameters:

• images (dict[str, ImageBase]) – Dictionary of images.

• mapper (MappingBase | None) – Optional default mapper assigned to images without a mapper, defaults to None.

add_images(images: dict[str, ImageBase])

Add images to the batch.

Parameters:

images (dict[str, ImageBase]) – Images to add.

Raises:

KeyError – If any keys already exist in the batch.

index(indices: int) → ImageBase

index(indices: list[int] | tuple[int]) → dict[str, ImageBase]

index get images by indices

Get the images by using indices. Will return the image at the indices of the image dict from ImageBatch.

Parameters:

indices (list[int] | tuple[int] | int) – The indices you want to get images for

Raises:

• TypeError – Indices type not valid

• IndexError – One of the indices is not valid

Returns:

return single image or dict of images for multiple indices

Return type:

ImageBase | dict[str, ImageBase]

map_center_point(mapper: MappingBase | None = None, transformer: CoordinateTransformer | None = None) → dict[str, MappingResultSuccess | ResultFailure[Issue]]

Map center point of image to 3d

Parameters:

• mapper (MappingBase | None) – Specify Mapper to be used, can be different to the one assigned in the class

• transformer (CoordinateTransformer | None) – A CoordinateTransfoer object which can be passed instead using crs_s

Returns:

MappingResult for all images

Raises:

• ValueError – Image Batch is empty

• NotGeoreferencedError – If an image is not geo-referenced

• MapperMissingError – If no mapper is available

• CRSInputError – If CRS/transformer input is invalid

• CoordinateTransformationError – If coordinate transformation fails

• MappingError – If mapping fails

Return type:

dict[str, MappingResultSuccess | ResultFailure[Issue]]

map_footprint(points_per_edge: int = 0, mapper: MappingBase | None = None, transformer: CoordinateTransformer | None = None) → dict[str, MappingResultSuccess | ResultFailure[Issue]]

Map footprint of images of batch to 3d

Parameters:

• points_per_edge (int) – The number of points which should be inserted between corners. 0: only corner points are mapped

• mapper (MappingBase | None) – Optional specify another Mapper to be used, can be different to the one assigned in the image class

• transformer (CoordinateTransformer | None) – A CoordinateTransfoer object which can be passed instead using crs_s

Returns:

MappingResult for all images

Raises:

• ValueError – Image Batch is empty

• NotGeoreferencedError – If an image is not geo-referenced

• MapperMissingError – If no mapper is available

• CRSInputError – If CRS/transformer input is invalid

• CoordinateTransformationError – If coordinate transformation fails

• MappingError – If mapping fails

Return type:

dict[str, MappingResultSuccess | ResultFailure[Issue]]

project(coordinates: ndarray[tuple[Any, ...], dtype[_ScalarT]], crs_s: CRS | None = None, transformer: CoordinateTransformer | None = None, only_valid: bool = False) → dict[str, ProjectionResultSuccess | ResultFailure[Issue]] | None

Calculate projection of 3d points into image. If points was outsize image size and to_distortion is true the undistorted projection will be returned

Parameters:

• coordinates (ArrayNx3) – Array of (nx3) with the point positions

• crs_s (CRS | None) – The coordinate system of the input coordinates

• transformer (CoordinateTransformer | None) – A CoordinateTransfoer object which can be passed instead using crs_s

• only_valid (bool) – If true only return images with valid projections.

Returns:

dict[ImageName, ProjectionResult] or None if for filtered (only_valid) no projections are valid

Raises:

• ValueError – If the image batch is empty.

• CRSInputError – If both crs_s and transformer are provided.

• NotGeoreferencedError – If an image is not geo-referenced.

• MapperMissingError – If a required mapper is missing.

• CoordinateTransformationError – If coordinate transformation fails.

Return type:

dict[str, ProjectionResultSuccess | ResultFailure[Issue]] | None