o &?e@sLddlZddlmZddlmZmZdddddd d Zd d Zd dZ dS)N)_supported_float_type) apply_kernelapply_kernel_nandF)radiuskernelnansafe num_threadsc Cs,t|}t|j}|j|dd}|durd}|dur!t||j}||}t|j}|d}|t|} | |} tj | |tj k<| |j} | d} tj ||ddtj ftj dd}|rbt nt} | | d| tj||jd  dtj|jtjd tj|jtjd |tj|} | j|jdd} | S) a` Estimate background intensity by rolling/translating a kernel. This rolling ball algorithm estimates background intensity for a ndimage in case of uneven exposure. It is a generalization of the frequently used rolling ball algorithm [1]_. Parameters ---------- image : ndarray The image to be filtered. radius : int, optional Radius of a ball shaped kernel to be rolled/translated in the image. Used if ``kernel = None``. kernel : ndarray, optional The kernel to be rolled/translated in the image. It must have the same number of dimensions as ``image``. Kernel is filled with the intensity of the kernel at that position. nansafe: bool, optional If ``False`` (default) assumes that none of the values in ``image`` are ``np.nan``, and uses a faster implementation. num_threads: int, optional The maximum number of threads to use. If ``None`` use the OpenMP default value; typically equal to the maximum number of virtual cores. Note: This is an upper limit to the number of threads. The exact number is determined by the system's OpenMP library. Returns ------- background : ndarray The estimated background of the image. Notes ----- For the pixel that has its background intensity estimated (without loss of generality at ``center``) the rolling ball method centers ``kernel`` under it and raises the kernel until the surface touches the image umbra at some ``pos=(y,x)``. The background intensity is then estimated using the image intensity at that position (``image[pos]``) plus the difference of ``kernel[center] - kernel[pos]``. This algorithm assumes that dark pixels correspond to the background. If you have a bright background, invert the image before passing it to the function, e.g., using `utils.invert`. See the gallery example for details. This algorithm is sensitive to noise (in particular salt-and-pepper noise). If this is a problem in your image, you can apply mild gaussian smoothing before passing the image to this function. References ---------- .. [1] Sternberg, Stanley R. "Biomedical image processing." Computer 1 (1983): 22-34. :DOI:`10.1109/MC.1983.1654163` Examples -------- >>> import numpy as np >>> from skimage import data >>> from skimage.restoration import rolling_ball >>> image = data.coins() >>> background = rolling_ball(data.coins()) >>> filtered_image = image - background >>> import numpy as np >>> from skimage import data >>> from skimage.restoration import rolling_ball, ellipsoid_kernel >>> image = data.coins() >>> kernel = ellipsoid_kernel((101, 101), 75) >>> background = rolling_ball(data.coins(), kernel=kernel) >>> filtered_image = image - background F)copyNrrZconstant)Zconstant_valuesmode)dtype)npasarrayrrZastype ball_kernelndimshapetupleinfZreshapepadZnewaxisrrZ zeros_likearrayZintp) imagerr r r Z float_typeZimgZ kernel_shapeZ kernel_centerZcenter_intensityZintensity_differencefunc backgroundrb/home/www/facesmatcher.com/pyenv/lib/python3.10/site-packages/skimage/restoration/_rolling_ball.py rolling_balls< J          rcCsztjtjddt|g|Dddidd}tj|ddd}t|}tt|d|dd }tj|||k<|S) aCreate a ball kernel for restoration.rolling_ball. Parameters ---------- radius : int Radius of the ball. ndim : int Number of dimensions of the ball. ``ndim`` should match the dimensionality of the image the kernel will be applied to. Returns ------- kernel : ndarray The kernel containing the surface intensity of the top half of the ellipsoid. See Also -------- rolling_ball cSg|] }t| |dqSrrZarange.0xrrr zball_kernel..indexingijr ZaxisrrN)rstackmeshgridceilsumsqrtclipr)rr kernel_coordsZsum_of_squaresZdistance_from_centerr rrrrxs rcCst|}t|ddd}tjtjdd|Dddidd }dtj||ddd }|tt|d d}tj||d k<|S) a/Create an ellipoid kernel for restoration.rolling_ball. Parameters ---------- shape : arraylike Length of the principal axis of the ellipsoid (excluding the intensity axis). The kernel needs to have the same dimensionality as the image it will be applied to. intensity : int Length of the intensity axis of the ellipsoid. Returns ------- kernel : ndarray The kernel containing the surface intensity of the top half of the ellipsoid. See Also -------- rolling_ball rrNcSrr r!r"rrrr%r&z$ellipsoid_kernel..r'r(r r)r)rrr/r*r+r-r.r)rZ intensityZ semi_axisr0Zintensity_scalingr rrrellipsoid_kernels  r1) numpyrZ _shared.utilsrZ_rolling_ball_cyrrrrr1rrrrs  q &