`skimage.data._binary_blobs:binary_blobs`

source: /dev/scikit-image/src/skimage/data/_binary_blobs.py :5

Signature

   def     binary_blobs (    length    =  512   ,    blob_size_fraction    =  0.1   ,    n_dim    =  2   ,    volume_fraction    =  0.5   ,    rng    =  None   ,  * ,     boundary_mode    =  nearest     )

Summary

Generate synthetic binary image with several rounded blob-like objects.

Parameters

length : int, optional

Linear size of output image.

blob_size_fraction : float, optional

Typical linear size of blob, as a fraction of length, should be smaller than 1.

n_dim : int, optional

Number of dimensions of output image.

volume_fraction : float, default 0.5

Fraction of image pixels covered by the blobs. Should be in [0, 1].

rng : {`numpy.random.Generator`, int}, optional

Pseudo-random number generator. By default, a PCG64 generator is used (see numpy.random.default_rng). If rng is an int, it is used to seed the generator.

boundary_mode : {'nearest', 'wrap'}, optional

The blobs are created by smoothing and then thresholding an array consisting of ones at seed positions. This mode determines which values are filled in when the smoothing kernel overlaps the seed array's boundary.

'nearest' (a a a a | a b c d | d d d d): By default, when applying the Gaussian filter, the seed array is extended by replicating the last boundary value. This will increase the size of blobs whose seed or center lies exactly on the edge.
'wrap' (a b c d | a b c d | a b c d): The seed array is extended by wrapping around to the opposite edge. The resulting blob array can be tiled and blobs will be contiguous and have smooth edges across tile boundaries.

Returns

blobs : ndarray of bools: Output binary image.

Examples

from skimage import data
blobs = data.binary_blobs(length=256, blob_size_fraction=0.1)
blobs = data.binary_blobs(length=256, blob_size_fraction=0.05)
blobs = data.binary_blobs(length=256, volume_fraction=0.3)

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Aliases

skimage.data.binary_blobs