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| import numpy as np | |
| import functools | |
| import warnings | |
| from scipy import ndimage as ndi | |
| from skimage import morphology | |
| def remove_small_holes(ar, min_size=64, connectivity=1, in_place=False): | |
| """Remove continguous holes smaller than the specified size. | |
| Parameters | |
| ---------- | |
| ar : ndarray (arbitrary shape, int or bool type) | |
| The array containing the connected components of interest. | |
| min_size : int, optional (default: 64) | |
| The hole component size. | |
| connectivity : int, {1, 2, ..., ar.ndim}, optional (default: 1) | |
| The connectivity defining the neighborhood of a pixel. | |
| in_place : bool, optional (default: False) | |
| If `True`, remove the connected components in the input array itself. | |
| Otherwise, make a copy. | |
| Raises | |
| ------ | |
| TypeError | |
| If the input array is of an invalid type, such as float or string. | |
| ValueError | |
| If the input array contains negative values. | |
| Returns | |
| ------- | |
| out : ndarray, same shape and type as input `ar` | |
| The input array with small holes within connected components removed. | |
| Examples | |
| -------- | |
| # >>> from skimage import morphology | |
| # >>> a = np.array([[1, 1, 1, 1, 1, 0], | |
| # ... [1, 1, 1, 0, 1, 0], | |
| # ... [1, 0, 0, 1, 1, 0], | |
| # ... [1, 1, 1, 1, 1, 0]], bool) | |
| # >>> b = morphology.remove_small_holes(a, 2) | |
| # >>> b | |
| # array([[ True, True, True, True, True, False], | |
| # [ True, True, True, True, True, False], | |
| # [ True, False, False, True, True, False], | |
| # [ True, True, True, True, True, False]], dtype=bool) | |
| # >>> c = morphology.remove_small_holes(a, 2, connectivity=2) | |
| # >>> c | |
| # array([[ True, True, True, True, True, False], | |
| # [ True, True, True, False, True, False], | |
| # [ True, False, False, True, True, False], | |
| # [ True, True, True, True, True, False]], dtype=bool) | |
| # >>> d = morphology.remove_small_holes(a, 2, in_place=True) | |
| # >>> d is a | |
| # True | |
| # Notes | |
| # ----- | |
| # If the array type is int, it is assumed that it contains already-labeled | |
| # objects. The labels are not kept in the output image (this function always | |
| # outputs a bool image). It is suggested that labeling is completed after | |
| # using this function. | |
| # """ | |
| # _check_dtype_supported(ar) | |
| #Creates warning if image is an integer image | |
| # if ar.dtype != bool: | |
| # warnings.warn("Any labeled images will be returned as a boolean array. " | |
| # "Did you mean to use a boolean array?", UserWarning) | |
| if in_place: | |
| out = ar | |
| else: | |
| out = ar.copy() | |
| #Creating the inverse of ar | |
| if in_place: | |
| out = np.logical_not(out,out) | |
| else: | |
| out = np.logical_not(out) | |
| #removing small objects from the inverse of ar | |
| out = morphology.remove_small_objects(out, min_size, connectivity, in_place) | |
| if in_place: | |
| out = np.logical_not(out,out) | |
| else: | |
| out = np.logical_not(out) | |
| return out |