shapedata - A Library to modify images and the corresponding landmarks

ShapeData

The ShapeData Package provides methods to transform images and the corrisponding landmarks in a similar way.

AbstractSingleImage

class AbstractSingleImage[source]

Bases: object

Abstract Class to define a SingleImage-API

_crop(*args, **kwargs)[source]

Internal implementation of AbstractSingleImage.crop()

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
_crop_lmks(*args, **kwargs)[source]

Crops the landmarks

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
_crop_to_landmarks(*args, **kwargs)[source]

Internal implementation of AbstractSingleImage.crop_to_landmarks()

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
_normalize_rotation(*args, **kwargs)[source]

Internal implementation of AbstractSingleImage.normalize_rotation()

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
_save_landmarks(*args, **kwargs)[source]

Abstract internal Function to save landmarks

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
_transform_img(*args, **kwargs)[source]

Applies a given transformation to image

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
_transform_lmk(*args, **kwargs)[source]

Applies a given transformation to landmarks

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
apply_trafo(*args, **kwargs)[source]

Applies a given transformation to image and landmarks

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
cartesian_coordinates()[source]

Transforms the landmarks into cartesian coordinates

Raises:NotImplementedError – if not overwritten by subclass
crop(*args, **kwargs)[source]

Crops image and landmarks to given range

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
crop_to_landmarks(*args, **kwargs)[source]

Crops image and landmarks to bounding box specified by landmarks

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
classmethod from_files(*args, **kwargs)[source]

Creates a class instance from files

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError
get_landmark_bounds(*args, **kwargs)[source]

Calculates bounds of landmarks

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
homogeneous_coordinates()[source]

Transforms the landmarks into homogeneous coordinates

Raises:NotImplementedError – if not overwritten by subclass
img

Property to get the actual image pixels

Returns:image pixels
Return type:np.array
is_gray

Property returning whether the image is a grayscale image

Raises:NotImplementedError – if not overwritten by subclass
is_homogeneous

Property returning whether the landmarks are in homogeneous coordinates

Raises:NotImplementedError – if not overwritten by subclass
normalize_rotation(*args, **kwargs)[source]

Rotates image and landmarks in a way, that the vector between two given points is parallel to horizontal axis

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
rescale(*args, **kwargs)[source]

Rescales image and landmarks

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
resize(*args, **kwargs)[source]

Resizes image and landmarks

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
rotate(*args, **kwargs)[source]

Rotates image and landmarks

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
save(*args, **kwargs)[source]

Abstract Function to save image and landmarks

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
save_image(*args, **kwargs)[source]

Abstract Function to save image

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
save_landmarks(*args, **kwargs)[source]

Abstract Function to save landmarks

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
to_grayscale()[source]

Converts image to grayscale

Raises:NotImplementedError – if not overwritten by subclass
transform(*args, **kwargs)[source]

Applies a given transformation to image and landmarks

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
transform_about_centre(*args, **kwargs)[source]

Applies a given transformation to image and landmarks at image center (internally shifts image and landmarks center to origin, applies transformation and shifts back)

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
translate(*args, **kwargs)[source]

Translates image and landmarks

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
view(*args, **kwargs)[source]

Plots image and landmarks

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass

BaseSingleImage

class BaseSingleImage(img: <sphinx.ext.autodoc.importer._MockObject object at 0x7f5a875c5eb8>, *args, **kwargs)[source]

Bases: shapedata.base_data_processing.AbstractSingleImage

Holds Single Image

_crop(min_y, min_x, max_y, max_x)[source]

Implements actual cropping inplace

Parameters:
  • min_y (int) – minimum y value
  • min_x (int) – minimum x value
  • max_y (int) – maximum y value
  • max_x (int) – maximum x value
Raises:

NotImplementedError – if not overwritten by subclass
static _crop_lmks(lmks, min_y, min_x, max_y, max_x)[source]

Crops landmarks to given values

Parameters:
  • lmks (np.ndarray) – landmarks to crop
  • min_y (int) – minimum y value
  • min_x (int) – minimum x value
  • max_y (int) – maximum y value
  • max_x (int) – maximum x value
Returns:

cropped landmarks
Return type:

np.ndarray
_crop_to_landmarks(proportion=0.0, **kwargs)[source]

Crop to landmarks inplace

Parameters:
  • proportion (float) – boundary proportion of cropping
  • **kwargs – additional keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
_normalize_rotation(lmks, index_left, index_right, **kwargs)[source]

normalizes rotation based on two keypoints

Parameters:
  • lmks (np.ndarray) – landmarks for rotation normalization
  • index_left (int) – index for left point
  • index_right (int) – index for right point
  • **kwargs – additional keyword arguments (passed to skimage.transform.warp())
Returns:

transformed Image
Return type:

BaseSingleImage
_save_landmarks(filepath, lmk_type, **kwargs)[source]

Saves landmarks to file

Parameters:
  • filepath (str) – path to file the landmarks should be saved to
  • lmk_type (str) – specifies the type of landmark file
  • **kwargs – additional keyword arguments passed to save function
Raises:

NotImplementedError – If not overwritten by subclass
_transform_img(transformation: <sphinx.ext.autodoc.importer._MockObject object at 0x7f5a875c5be0>, **kwargs)[source]

Apply transformation inplace to image

Parameters:
Returns:

Transformed Image with original Landmarks
Return type:

BaseSingleImage
_transform_lmk(transformation: <sphinx.ext.autodoc.importer._MockObject object at 0x7f5a875c5be0>)[source]

Apply transformation inplace to landmarks

Parameters:transformation (skimage.transform.AffineTransform) – transformation to apply
Returns:Image with Transformed Landmarks
Return type:BaseSingleImage
apply_trafo(transformation: <sphinx.ext.autodoc.importer._MockObject object at 0x7f5a875c5be0>, **kwargs)[source]

Apply transformation inplace to image and landmarks

Parameters:
Returns:

Transformed Image and Landmarks
Return type:

BaseSingleImage
cartesian_coordinates()[source]

Transforms landmark coordinates inplace to cartesian coordinates

Returns:Image with Landmarks in cartesian Coordinates
Return type:BaseSingleImage
crop(min_y, min_x, max_y, max_x)[source]

Crops Image by specified values

Parameters:
  • min_y (int) – minimum y value
  • min_x (int) – minimum x value
  • max_y (int) – maximum y value
  • max_x (int) – maximum x value
Returns:

cropped image
Return type:

BaseSingleImage
crop_to_landmarks(proportion=0.0, **kwargs)[source]

Crop image to landmarks

Parameters:
  • proportion (float) – image proportion to add to size of bounding box
  • **kwargs – additional keyword arguments
Returns:

cropped image
Return type:

BaseSingleImage
classmethod from_files(file, extension=None, **kwargs)[source]

Creates a class instance from files

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError
classmethod from_ljson_files(img_file, **kwargs)[source]

Create class from image or landmark file

Parameters:file (str) – path to image or landmarkfile
Returns:
Return type:BaseSingleImage
classmethod from_npy_files(file, **kwargs)[source]

Create class from image or landmark file

Parameters:file (str) – path to image or landmarkfile
Returns:
Return type:BaseSingleImage
classmethod from_pts_files(file, **kwargs)[source]

Create class from image or landmark file :param file: path to image or landmarkfile :type file: string

Returns:
Return type:BaseSingleImage
static get_landmark_bounds(lmks)[source]

Function to calculate the landmark bounds

Parameters:lmks (np.ndarray) – landmarks
Returns:
  • int (min_y)
  • int (min_x)
  • int (max_y)
  • int (max_x)
homogeneous_coordinates()[source]

Transforms landmark coordinates inplace to homogeneous coordinates

Returns:Image with Landmarks in Homogeneous Coordinates
Return type:BaseSingleImage
img

Property to get the actual image pixels

Returns:image pixels
Return type:np.array
is_gray

Property returning whether the image is a grayscale image

Raises:NotImplementedError – if not overwritten by subclass
is_homogeneous

Property returning whether the landmarks are in homogeneous coordinates

Raises:NotImplementedError – if not overwritten by subclass
normalize_rotation(*args, **kwargs)[source]

Rotates image and landmarks in a way, that the vector between two given points is parallel to horizontal axis

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass
rescale(scale, **kwargs)[source]

Scale Image and landmarks

Parameters:
  • scale – scale parameter
  • **kwargs – additional keyword arguments (passed to skimage.transform.warp())
Returns:

transformed Image
Return type:

BaseSingleImage
resize(target_shape, **kwargs)[source]

resize image and scale landmarks :param target_shape: target shape for resizing :type target_shape: tuple or list :param **kwargs: additional keyword arguments (passed to

skimage.transform.warp())
Returns:transformed Image
Return type:BaseSingleImage
rotate(angle, degree=True, **kwargs)[source]

Rotates the image and landmarks by given angle

Parameters:
  • angle (float or int) – rotation angle
  • degree (bool) – whether the angle is given in degree or radiant
  • **kwargs – additional keyword arguments (passed to skimage.transform.warp())
Returns:

transformed Image
Return type:

BaseSingleImage
save(directory, filename, lmk_type='LJSON', **kwargs)[source]

Saves Image and optionally landmarks to files

Parameters:
  • directory (str) – string containing the directory to save
  • filename (str) – string containing the filename (without the extension)
  • lmk_type (str or None) – if None: no landmarks will be saved if str: specifies type of landmark file
  • **kwargs – additional keyword arguments passed to save function for landmarks
save_image(filepath)[source]

Saves Image to file

Parameters:filepath (str) – file to save the image to
save_landmarks(filepath, lmk_type='LJSON', **kwargs)[source]

Saves landmarks to file

Parameters:
  • filepath (str) – path to file the landmarks should be saved to
  • lmk_type (str) – specifies the type of landmark file
  • **kwargs – additional keyword arguments passed to save function
to_grayscale()[source]

Convert Image to grayscale

Returns:Grayscale Image
Return type:BaseSingleImage
transform(transform=None, rotation=None, scale=None, translation=None, shear=None, trafo_matrix=None, return_matrix=False, **kwargs)[source]

transform image and landmarks by parameters or transformation matrix See skimage.transform.AffineTransform for a detailed parameter explanation

Parameters:
  • transform (skimage.transform.AffineTransform) – if transform is specified it overwrites all other arguments
  • rotation (float or None) – rotation angle in radiant
  • scale (float or None) – scale value
  • translation – translation params
  • shear – shear params
  • trafo_matrix – transformation matrix
  • return_matrix (bool) – whether to return the transformation matrix along the transformed object
  • **kwargs – additional keyword arguments
Returns:

  • BaseSingleImage – transformed Image
  • [optional] np.ndarray – transformation matrix
transform_about_centre(transform=None, rotation=None, scale=None, translation=None, shear=None, trafo_matrix=None, return_matrix=False, **kwargs)[source]

Perform transformations about the image center. (internally shifting image to origin, perform transformation and shift it back)

Parameters:
  • transform (skimage.transform.AffineTransform) – if transform is specified it overwrites all other arguments
  • rotation (float) – rotation angle in radiant
  • scale (float) – scale value
  • translation – translation params
  • shear – shear params
  • trafo_matrix – transformation matrix
  • return_matrix (bool) – whether to return the transformation matrix along the transformed object
  • **kwargs – additional keyword arguments
Returns:

  • BaseSingleImage – transformed Image
  • [optional] np.ndarray – transformation matrix
translate(translation, relative=False, **kwargs)[source]

translates image and landmarks

translation :
translation parameters
relative : bool
whether translation parameters are relative to image size
**kwargs :
additional keyword arguments (passed to skimage.transform.warp())
BaseSingleImage
transformed Image
view(*args, **kwargs)[source]

Plots image and landmarks

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError – if not overwritten by subclass

Single Shape

The single_shape subpackage implements dataprocessing and image-landmark-transformations for 2D images. Furthermore it provides a delira compatible dataset.

ShapeDataset

class ShapeDataset(data_path, img_size, crop=None, extension=None, rotate=None, cached=False, random_offset=False, random_scale=False, point_indices=None)[source]

Bases: sphinx.ext.autodoc.importer._MockObject

Dataset to load image and corresponding shape

_make_dataset(path)[source]

default_loader

default_loader(data: str, img_size: tuple, crop=None, extension=None, rotate=None, cached=False, random_offset=False, random_scale=False, point_indices=None)[source]

Helper Function to load single sample

Parameters:
  • data (str or SingleImage2D) – image file to load
  • img_size (tuple) – image size for resizing
  • crop (None or float) – if None: nor cropping will be applied if float: specifies boundary proportion for cropping
  • extension (str or None:) – specifiying the extension
  • rotate (int or None) – specifies to image rotation (in degrees)
  • cached (bool) – whether or not the data is already cached
  • random_offset (bool or float) – if bool: must be False -> No Random Shift is applied if float: specifies the maximal number of pixels to shift
  • random_scale (bool or float) – if bool: must be False -> No random scaling is applied if float: specifies the maximum amount of scaling
  • point_indices (None or Iterable) – if None: All landmarks are returned if Iterable: only landmarks corresponding to indices are returned
Returns:

  • np.ndarray – image
  • np.ndarray – landmarks

preprocessing

preprocessing(img: shapedata.single_shape.data_processing.SingleImage2D, img_size: tuple, crop=None, rotate=None, random_offset=False, random_scale=False, point_indices=None)[source]

Helper Function to preprocess a single sample

Parameters:
  • img (SingleImage2D) – image file to preprocess
  • img_size (tuple) – image size for resizing
  • crop (None or float) – if None: nor cropping will be applied if float: specifies boundary proportion for cropping
  • extension (str or None:) – specifiying the extension
  • rotate (int or None) – specifies to image rotation (in degrees)
  • random_offset (bool or float) – if bool: must be False -> No Random Shift is applied if float: specifies the maximal number of pixels to shift
  • random_scale (bool or float) – if bool: must be False -> No random scaling is applied if float: specifies the maximum amount of scaling
  • point_indices (None or Iterable) – if None: All landmarks are returned if Iterable: only landmarks corresponding to indices are returned
Returns:

  • np.ndarray – image
  • np.ndarray – landmarks

DataProcessing

class DataProcessing(samples, dim=2, **kwargs)[source]

Bases: object

Process multiple SingleImages

See also

SingleImage2D

static _get_files(directory, extensions)[source]

return files with extensions

Parameters:
  • directory (str) – directory containing the files
  • extensions (list) – list of strings specifying valid extensions
Returns:

valid files
Return type:

list
classmethod from_dir(data_dir, verbose=True, n_jobs=None, n_dim=2)[source]

create class instance from directory

Parameters:
  • data_dir (str) – directory where shapedata is stored
  • verbose (bool) – whether or not to print current progress
  • n_jobs (int) – number of jobs for loading data (default: None -> all available CPUs are used)
  • n_dim (int) – Integer indicating the dimensionality of the image (default: 2)
Returns:

class instance
Return type:

DataProcessing
images

get list of samples’ pixels

Returns:pixels
Return type:list
landmarks

get list of samples’ landmarks

Returns:landmarks
Return type:list
lmk_pca(scale: bool, center: bool, pt_indices=[], *args, **kwargs)[source]

perform PCA on samples’ landmarks

Parameters:
  • scale (bool) – whether or not to scale the principal components with the corresponding eigen value
  • center (bool) – whether or not to substract mean before pca
  • pt_indices (int) – indices to include into PCA (if empty: include all points)
  • args (list) – additional positional arguments (passed to pca)
  • **kwargs – additional keyword arguments (passed to pca)
Returns:

eigen_shapes
Return type:

np.array
resize(img_size)[source]

resize all samples

Parameters:img_size (tuple) – new image size

SingleImage2D

class SingleImage2D(img, lmk=None, **kwargs)[source]

Bases: shapedata.base_data_processing.BaseSingleImage

Holds Single Image

_crop(min_y, min_x, max_y, max_x)[source]

Implements actual cropping inplace

Parameters:
  • min_y (int) – minimum y value
  • min_x (int) – minimum x value
  • max_y (int) – maximum y value
  • max_x (int) – maximum x value
Returns:

cropped image
Return type:

SingleImage2D
static _crop_lmks(lmks, min_y, min_x, max_y, max_x)

Crops landmarks to given values

Parameters:
  • lmks (np.ndarray) – landmarks to crop
  • min_y (int) – minimum y value
  • min_x (int) – minimum x value
  • max_y (int) – maximum y value
  • max_x (int) – maximum x value
Returns:

cropped landmarks
Return type:

np.ndarray
_crop_to_landmarks(proportion=0.0, **kwargs)[source]

Crop to landmarks

Parameters:
  • proportion (float) – Cropping Proportion
  • **kwargs – additional keyword arguments (ignored here)
Returns:

Cropped Image
Return type:

SingleImage2D
_normalize_rotation(lmks, index_left, index_right, **kwargs)

normalizes rotation based on two keypoints

Parameters:
  • lmks (np.ndarray) – landmarks for rotation normalization
  • index_left (int) – index for left point
  • index_right (int) – index for right point
  • **kwargs – additional keyword arguments (passed to skimage.transform.warp())
Returns:

transformed Image
Return type:

BaseSingleImage
_save_landmarks(filepath, lmk_type, **kwargs)[source]

Saves landmarks to file

Parameters:
  • filepath (str) – path to file the landmarks should be saved to
  • lmk_type (str) – specifies the type of landmark file
  • **kwargs – additional keyword arguments passed to save function
Raises:

ValueError – no valid landmarktype is given
_transform_img(transformation: <sphinx.ext.autodoc.importer._MockObject object at 0x7f5a875c5be0>, **kwargs)

Apply transformation inplace to image

Parameters:
Returns:

Transformed Image with original Landmarks
Return type:

BaseSingleImage
_transform_lmk(transformation: <sphinx.ext.autodoc.importer._MockObject object at 0x7f5a875b4470>)[source]

Apply transformation inplace to landmarks

Parameters:transformation (skimage.transform.AffineTransform) – transformation to apply
Returns:Image with Transformed Landmarks
Return type:BaseSingleImage
apply_trafo(transformation: <sphinx.ext.autodoc.importer._MockObject object at 0x7f5a875c5be0>, **kwargs)

Apply transformation inplace to image and landmarks

Parameters:
Returns:

Transformed Image and Landmarks
Return type:

BaseSingleImage
cartesian_coordinates()[source]

Transforms landmark coordinates inplace to cartesian coordinates

Returns:class – Image with Landmarks in cartesian Coordinates
Return type:SingleImage2D
crop(min_y, min_x, max_y, max_x)

Crops Image by specified values

Parameters:
  • min_y (int) – minimum y value
  • min_x (int) – minimum x value
  • max_y (int) – maximum y value
  • max_x (int) – maximum x value
Returns:

cropped image
Return type:

BaseSingleImage
crop_to_landmarks(proportion=0.0, **kwargs)

Crop image to landmarks

Parameters:
  • proportion (float) – image proportion to add to size of bounding box
  • **kwargs – additional keyword arguments
Returns:

cropped image
Return type:

BaseSingleImage
classmethod from_files(file, extension=None, **kwargs)

Creates a class instance from files

Parameters:
  • *args – positional arguments
  • **kwargs – keyword arguments
Raises:

NotImplementedError
classmethod from_ljson_files(img_file, **kwargs)[source]

Creates class from menpo pts landmarks and image

Parameters:
  • img_file (str) – image file to load
  • **kwargs – additional keyword arguments
Returns:

class instance
Return type:

SingleImage2D
classmethod from_npy_files(file, **kwargs)[source]

Create class from image file :param file: path to image file :type file: str :param **kwargs: additional keyword arguments

Returns:class instance
Return type:SingleImage2D
classmethod from_pts_files(img_file, **kwargs)[source]

Creates class from menpo ljson landmarks and image

Parameters:
  • img_file (str) – image file to load
  • **kwargs – additional keyword arguments
Returns:

class instance
Return type:

SingleImage2D
static get_landmark_bounds(lmks)

Function to calculate the landmark bounds

Parameters:lmks (np.ndarray) – landmarks
Returns:
  • int (min_y)
  • int (min_x)
  • int (max_y)
  • int (max_x)
homogeneous_coordinates()[source]

Transforms landmark coordinates inplace to homogeneous coordinates

Returns:Image with Landmarks in Homogeneous Coordinates
Return type:SingleImage2D
img

Property to get the actual image pixels

Returns:image pixels
Return type:np.array
is_gray

Property returning whether the image is a grayscale image

Raises:NotImplementedError – if not overwritten by subclass
is_homogeneous

Property returning whether the landmarks are in homogeneous coordinates

Raises:NotImplementedError – if not overwritten by subclass
normalize_rotation(index_left, index_right, **kwargs)[source]

normalizes rotation based on two keypoints

index_left : int
landmark-index of the left point
index_right : int
landmark-index of the right point
**kwargs:
additional keyword arguments (passed to warp())
Returns:normalized image
Return type:SingleImage2D
rescale(scale, **kwargs)

Scale Image and landmarks

Parameters:
  • scale – scale parameter
  • **kwargs – additional keyword arguments (passed to skimage.transform.warp())
Returns:

transformed Image
Return type:

BaseSingleImage
resize(target_shape, **kwargs)

resize image and scale landmarks :param target_shape: target shape for resizing :type target_shape: tuple or list :param **kwargs: additional keyword arguments (passed to

skimage.transform.warp())
Returns:transformed Image
Return type:BaseSingleImage
rotate(angle, degree=True, **kwargs)

Rotates the image and landmarks by given angle

Parameters:
  • angle (float or int) – rotation angle
  • degree (bool) – whether the angle is given in degree or radiant
  • **kwargs – additional keyword arguments (passed to skimage.transform.warp())
Returns:

transformed Image
Return type:

BaseSingleImage
save(directory, filename, lmk_type='LJSON', **kwargs)

Saves Image and optionally landmarks to files

Parameters:
  • directory (str) – string containing the directory to save
  • filename (str) – string containing the filename (without the extension)
  • lmk_type (str or None) – if None: no landmarks will be saved if str: specifies type of landmark file
  • **kwargs – additional keyword arguments passed to save function for landmarks
save_image(filepath)

Saves Image to file

Parameters:filepath (str) – file to save the image to
save_landmarks(filepath, lmk_type='LJSON', **kwargs)

Saves landmarks to file

Parameters:
  • filepath (str) – path to file the landmarks should be saved to
  • lmk_type (str) – specifies the type of landmark file
  • **kwargs – additional keyword arguments passed to save function
to_grayscale()

Convert Image to grayscale

Returns:Grayscale Image
Return type:BaseSingleImage
transform(transform=None, rotation=None, scale=None, translation=None, shear=None, trafo_matrix=None, return_matrix=False, **kwargs)

transform image and landmarks by parameters or transformation matrix See skimage.transform.AffineTransform for a detailed parameter explanation

Parameters:
  • transform (skimage.transform.AffineTransform) – if transform is specified it overwrites all other arguments
  • rotation (float or None) – rotation angle in radiant
  • scale (float or None) – scale value
  • translation – translation params
  • shear – shear params
  • trafo_matrix – transformation matrix
  • return_matrix (bool) – whether to return the transformation matrix along the transformed object
  • **kwargs – additional keyword arguments
Returns:

  • BaseSingleImage – transformed Image
  • [optional] np.ndarray – transformation matrix
transform_about_centre(transform=None, rotation=None, scale=None, translation=None, shear=None, trafo_matrix=None, return_matrix=False, **kwargs)

Perform transformations about the image center. (internally shifting image to origin, perform transformation and shift it back)

Parameters:
  • transform (skimage.transform.AffineTransform) – if transform is specified it overwrites all other arguments
  • rotation (float) – rotation angle in radiant
  • scale (float) – scale value
  • translation – translation params
  • shear – shear params
  • trafo_matrix – transformation matrix
  • return_matrix (bool) – whether to return the transformation matrix along the transformed object
  • **kwargs – additional keyword arguments
Returns:

  • BaseSingleImage – transformed Image
  • [optional] np.ndarray – transformation matrix
translate(translation, relative=False, **kwargs)

translates image and landmarks

translation :
translation parameters
relative : bool
whether translation parameters are relative to image size
**kwargs :
additional keyword arguments (passed to skimage.transform.warp())
BaseSingleImage
transformed Image
view(view_landmarks=False, create_fig=False, **kwargs)[source]

Shows image (and optional the landmarks)

Parameters:
  • view_landmarks (bool) – whether or not to show the landmarks
  • **kwargs – additional keyword arguments (are passed to imshow)
Returns:

figure with plot
Return type:

Figure

ljson_importer

ljson_importer(filepath)[source]

Importer for the Menpo JSON format. This is an n-dimensional landmark type for both images and meshes that encodes semantic labels in the format. Landmark set label: JSON Landmark labels: decided by file

Parameters:filepath (str) – Absolute filepath of the file.
Returns:loaded landmarks
Return type:np.ndarray

pts_importer

pts_importer(filepath, image_origin=True, z=False, **kwargs)[source]

Importer for the PTS file format. Assumes version 1 of the format. Implementations of this class should override the _build_points() which determines the ordering of axes. For example, for images, the x and y axes are flipped such that the first axis is y (height in the image domain). Note that PTS has a very loose format definition. Here we make the assumption (as is common) that PTS landmarks are 1-based. That is, landmarks on a 480x480 image are in the range [1-480]. As Menpo is consistently 0-based, we subtract 1 off each landmark value automatically. If you want to use PTS landmarks that are 0-based, you will have to manually add one back on to landmarks post importing. Landmark set label: PTS

Parameters:
  • filepath (str) – Absolute filepath of the file.
  • image_origin (bool, optional) – If True, assume that the landmarks exist within an image and thus the origin is the image origin.
  • **kwargs (dict, optional) – Any other keyword arguments.
Returns:

imported points
Return type:

np.ndarray

ljson_exporter

ljson_exporter(lmk_points, filepath, **kwargs)[source]

Given a file handle to write in to (which should act like a Python file object), write out the landmark data. No value is returned. Writes out the LJSON format which is a verbose format that closely resembles the labelled point graph format. It describes semantic labels and connectivity between labels. The first axis of the format represents the image y-axis and is consistent with ordering within Menpo.

Parameters:
  • lmk_points (np.ndarray) – The shape to write out.
  • filepath (str) – The file to write in to

pts_exporter

pts_exporter(pts, file_handle, **kwargs)[source]

Given a file handle to write in to (which should act like a Python file object), write out the landmark data. No value is returned. Writes out the PTS format which is a very simple format that does not contain any semantic labels. We assume that the PTS format has been created using Matlab and so use 1-based indexing and put the image x-axis as the first coordinate (which is the second axis within Menpo). Note that the PTS file format is only powerful enough to represent a basic pointcloud. Any further specialization is lost.

Parameters:
  • pts (np.ndarray) – points to save
  • file_handle (file-like object) – The file to write in to

IMG_EXTENSIONS_2D

IMG_EXTENSIONS_2D

Contains the typical 2D file-extensions for images.

LMK_EXTENSIONS

LMK_EXTENSIONS

Contains all supported file-extensions for landmark files.

is_image_file

is_image_file(filename)[source]

Helper Function to determine whether a file is an image file or not

Parameters:filename (str) – the filename containing a possible image
Returns:True if file is image file, False otherwise
Return type:bool

is_landmark_file

is_landmark_file(filename)[source]

Helper Function to determine whether a file is a landmark file or not

Parameters:filename (str) – the filename containing possible landmarks
Returns:True if file is landmark file, False otherwise
Return type:bool

make_dataset

make_dataset(dir)[source]

Helper Function to make a dataset containing all images in a certain directory

Parameters:dir (the directory containing the dataset) –
Returns:list of image paths
Return type:list

Indices and tables