voi<SSKrSSKrSSKJr SSS.Sjjrg)N)gaussiannearest) boundary_modec rUS;a[SU<35eX-nUS:a7SU- nXp-n[R"SU<SU<SUSUSUS 3 [S S 9 Un[R R U5n [U/U-5n [R"U 5n [[S U- 5U-S 5n X R X,45-R[5n S U [SU 55'[U SU-U-SUS9n [R"U SS U- -5n[R"X:5$)a 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 (where the output is 1). Should be in [0, 1]. rng : {`numpy.random.Generator`, int}, optional Pseudo-random number generator. By default, a PCG64 generator is used (see :func:`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. boundary_mode : str, default "nearest" The `mode` parameter passed to the Gaussian filter. Use "wrap" for periodic boundary conditions. Returns ------- blobs : ndarray of bools Output binary image Examples -------- >>> from skimage import data >>> data.binary_blobs(length=5, blob_size_fraction=0.2) # doctest: +SKIP array([[ True, False, True, True, True], [ True, True, True, False, True], [False, True, False, True, True], [ True, False, False, True, True], [ True, False, False, False, True]]) >>> blobs = data.binary_blobs(length=256, blob_size_fraction=0.1) >>> # Finer structures >>> blobs = data.binary_blobs(length=256, blob_size_fraction=0.05) >>> # Blobs cover a smaller volume fraction of the image >>> blobs = data.binary_blobs(length=256, volume_fraction=0.3) >wraprzunsupported `boundary_mode`: 皙?z`blob_size_fraction=z` together with `length=z!` would result in a blob size of z] pixels. Small blob sizes likely lead to unexpected results! Clamping to `blob_size_fraction=z` and a blob size of z- pixels to avoid allocating excessive memory.r)category stacklevelg?c3$# UHov M g7f)N).0indicess V/var/www/html/land-ocr/venv/lib/python3.13/site-packages/skimage/data/_binary_blobs.py binary_blobs..bs-f7wfsg?F)sigmapreserve_rangemoded) ValueErrorwarningswarnRuntimeWarningnprandom default_rngtuplezerosmaxintastyper percentile logical_not)lengthblob_size_fractionn_dimvolume_fractionrngr blob_sizeclamped_size_fractionclamped_blob_sizersshapemaskn_ptspoints thresholds r binary_blobsr4siF//88IJKK"+I3 #f 1: #"$$=fY? k"//D.EF#$$Q  S $ 3   s #B 6(U" #E 88E?D C,,-6 :Eyy%00 8 8 =F12D-f- -.  Vm00   D  dC1+>$?@I >>$* ++)ir rg?N)rnumpyr_shared.filtersrr4rr5rr8s0&   b,b,r5