correct-mesh-orientation

correct_mesh_orientation skimage.measure.correct_mesh_orientation(volume, verts, faces, spacing=(1.0, 1.0, 1.0), gradient_direction='descent') [source] Correct orientations of mesh faces. Parameters: volume : (M, N, P) array of doubles Input data volume to find isosurfaces. Will be cast to np.float64. verts : (V, 3) array of floats Array containing (x, y, z) coordinates for V unique mesh vertices. faces : (F, 3) array of ints List of length-3 lists of integers, referencing vertex coord

examples

Module: novice

lena

lena skimage.data.lena(*args, **kwargs) [source] Deprecated function. Use skimage.data.astronaut instead. Colour “Lena” image. This image has been removed from scikit-image due to copyright concerns. The standard, yet sometimes controversial Lena test image was scanned from the November 1972 edition of Playboy magazine. From an image processing perspective, this image is useful because it contains smooth, textured, shaded as well as detail areas.

gabor

gabor skimage.filters.gabor(image, frequency, theta=0, bandwidth=1, sigma_x=None, sigma_y=None, n_stds=3, offset=0, mode='reflect', cval=0) [source] Return real and imaginary responses to Gabor filter. The real and imaginary parts of the Gabor filter kernel are applied to the image and the response is returned as a pair of arrays. Gabor filter is a linear filter with a Gaussian kernel which is modulated by a sinusoidal plane wave. Frequency and orientation representations of the Gabor filter

requiredattr

RequiredAttr class skimage.viewer.utils.RequiredAttr(init_val=None) [source] Bases: object A class attribute that must be set before use. __init__(init_val=None) [source] instances = {(, None): 'Widget is not attached to a Plugin.', (, None): 'Plugin is not attached to ImageViewer'}

slider

Slider class skimage.viewer.widgets.Slider(name, low=0.0, high=1.0, value=None, value_type='float', ptype='kwarg', callback=None, max_edit_width=60, orientation='horizontal', update_on='release') [source] Bases: skimage.viewer.widgets.core.BaseWidget Slider widget for adjusting numeric parameters. Parameters: name : str Name of slider parameter. If this parameter is passed as a keyword argument, it must match the name of that keyword argument (spaces are replaced with underscores). In addi

img-as-int

img_as_int skimage.util.img_as_int(image, force_copy=False) [source] Convert an image to 16-bit signed integer format. Parameters: image : ndarray Input image. force_copy : bool Force a copy of the data, irrespective of its current dtype. Returns: out : ndarray of uint16 Output image. Notes The values are scaled between -32768 and 32767. If the input data-type is positive-only (e.g., uint8), then the output image will still only have positive values.

mesh-surface-area

mesh_surface_area skimage.measure.mesh_surface_area(verts, faces) [source] Compute surface area, given vertices & triangular faces Parameters: verts : (V, 3) array of floats Array containing (x, y, z) coordinates for V unique mesh vertices. faces : (F, 3) array of ints List of length-3 lists of integers, referencing vertex coordinates as provided in verts Returns: area : float Surface area of mesh. Units now [coordinate units] ** 2. See also skimage.measure.marching_cubes, ski

denoise-tv-chambolle

denoise_tv_chambolle skimage.restoration.denoise_tv_chambolle(im, weight=0.1, eps=0.0002, n_iter_max=200, multichannel=False) [source] Perform total-variation denoising on n-dimensional images. Parameters: im : ndarray of ints, uints or floats Input data to be denoised. im can be of any numeric type, but it is cast into an ndarray of floats for the computation of the denoised image. weight : float, optional Denoising weight. The greater weight, the more denoising (at the expense of fidel

projectivetransform

ProjectiveTransform class skimage.transform.ProjectiveTransform(matrix=None) [source] Bases: skimage.transform._geometric.GeometricTransform Matrix transformation. Apply a projective transformation (homography) on coordinates. For each homogeneous coordinate , its target position is calculated by multiplying with the given matrix, , to give : [[a0 a1 a2] [b0 b1 b2] [c0 c1 1 ]]. E.g., to rotate by theta degrees clockwise, the matrix should be: [[cos(theta) -sin(theta) 0] [sin(theta) cos(