ellipse skimage.draw.ellipse(r, c, yradius, xradius, shape=None) [source] Generate coordinates of pixels within ellipse. Parameters: r, c : double Centre coordinate of ellipse. yradius, xradius : double Minor and major semi-axes. (x/xradius)**2 + (y/yradius)**2 = 1. shape : tuple, optional Image shape which is used to determine the maximum extent of output pixel coordinates. This is useful for ellipses which exceed the image size. By default the full extent of the ellipse are used. R

show skimage.io.show() [source] Display pending images. Launch the event loop of the current gui plugin, and display all pending images, queued via imshow. This is required when using imshow from non-interactive scripts. A call to show will block execution of code until all windows have been closed. Examples >>> import skimage.io as io >>> for i in range(4): ... ax_im = io.imshow(np.random.rand(50, 50)) >>> io.show()

find_available_plugins skimage.io.find_available_plugins(loaded=False) [source] List available plugins. Parameters: loaded : bool If True, show only those plugins currently loaded. By default, all plugins are shown. Returns: p : dict Dictionary with plugin names as keys and exposed functions as values.

Module: viewer.widgets Widgets for interacting with ImageViewer. These widgets should be added to a Plugin subclass using its add_widget method or calling: plugin += Widget(...) on a Plugin instance. The Plugin will delegate action based on the widget’s parameter type specified by its ptype attribute, which can be: 'arg' : positional argument passed to Plugin's `filter_image` method. 'kwarg' : keyword argument passed to Plugin's `filter_image` method. 'plugin' : attribute of Plugin. You'll pro

greycoprops skimage.feature.greycoprops(P, prop='contrast') [source] Calculate texture properties of a GLCM. Compute a feature of a grey level co-occurrence matrix to serve as a compact summary of the matrix. The properties are computed as follows: ‘contrast’: ‘dissimilarity’: ‘homogeneity’: ‘ASM’: ‘energy’: ‘correlation’: Parameters: P : ndarray Input array. P is the grey-level co-occurrence histogram for which to compute the specified property. The value P[i,j,d,theta] is the n

remove_small_objects skimage.morphology.remove_small_objects(ar, min_size=64, connectivity=1, in_place=False) [source] Remove connected components smaller than the specified size. Parameters: ar : ndarray (arbitrary shape, int or bool type) The array containing the connected components of interest. If the array type is int, it is assumed that it contains already-labeled objects. The ints must be non-negative. min_size : int, optional (default: 64) The smallest allowable connected compone

push skimage.io.push(img) [source] Push an image onto the shared image stack. Parameters: img : ndarray Image to push.

inverse skimage.filters.inverse(data, impulse_response=None, filter_params={}, max_gain=2, predefined_filter=None) [source] Apply the filter in reverse to the given data. Parameters: data : (M,N) ndarray Input data. impulse_response : callable f(r, c, **filter_params) Impulse response of the filter. See LPIFilter2D.__init__. filter_params : dict Additional keyword parameters to the impulse_response function. max_gain : float Limit the filter gain. Often, the filter contains zeros, wh

radon skimage.transform.radon(image, theta=None, circle=False) [source] Calculates the radon transform of an image given specified projection angles. Parameters: image : array_like, dtype=float Input image. The rotation axis will be located in the pixel with indices (image.shape[0] // 2, image.shape[1] // 2). theta : array_like, dtype=float, optional (default np.arange(180)) Projection angles (in degrees). circle : boolean, optional Assume image is zero outside the inscribed circle, ma

rocket skimage.data.rocket() [source] Launch photo of DSCOVR on Falcon 9 by SpaceX. This is the launch photo of Falcon 9 carrying DSCOVR lifted off from SpaceX’s Launch Complex 40 at Cape Canaveral Air Force Station, FL. Notes This image was downloaded from SpaceX Photos. The image was captured by SpaceX and released in the public domain.