膨胀运算的函数:scipy.ndimage.binary_dilation(input, structure=None, iterations=1, mask=None, output=None, border_value=0, origin=0, brute_force=False),其中input是待膨胀的二值矩阵,structure是膨胀结构,其他参数可自行查阅。接下来举例说明函数用法。 首先import库,随意创建一个5*5的矩阵a,并将a[2, ...
This library contains both 2D and 3D void filling algorithms, similar in function toscipy.ndimage.morphology.binary_fill_holes, but with an eye towards higher performance. The SciPy hole filling algorithm uses slow serial dilations. The current version of this library uses a scan line flood fill...
例子: >>>fromscipyimportndimage>>>importnumpyasnp>>>a = np.zeros((5,5))>>>a[2,2] =1>>>a array([[0.,0.,0.,0.,0.], [0.,0.,0.,0.,0.], [0.,0.,1.,0.,0.], [0.,0.,0.,0.,0.], [0.,0.,0.,0.,0.]])>>>ndimage.binary_dilation(a) array([[False,Fals...
stringent_worm = canny.canny_hysteresis(local_maxima, gradient, low_worm, high_worm)# Expand out 20 pixels from the stringent worm edges to make our search spacestringent_area = ndimage.binary_dilation(stringent_worm, mask=well_mask, iterations=20)# now use the relaxed threshold but only in ...
示例2: test_binary_dilation22 ▲点赞 6▼ # 需要导入模块: from scipy import ndimage [as 别名]# 或者: from scipy.ndimage importbinary_dilation[as 别名]deftest_binary_dilation22(self):expected = [[0,1,0,0,0,0,0,0], [1,1,1,0,0,0,0,0], ...
# 需要导入模块: from scipy.ndimage import morphology [as 别名]# 或者: from scipy.ndimage.morphology importbinary_dilation[as 别名]defmask_and_normalize_peaks(peaks, tract_seg_path, bundles, dilation, nr_cpus=-1):""" runtime TOM: 2min 40s (~8.5GB) ...
本文简要介绍 python 语言中 scipy.ndimage.generate_binary_structure 的用法。 用法: scipy.ndimage.generate_binary_structure(rank, connectivity)# 为二元形态学运算生成二元结构。 参数 :: rank: int 将应用结构元素的数组的维数,由 np.ndim 返回。 connectivity: int 连通性确定输出数组的哪些元素属于该结构,即...
input2_border = input2 -binary_erosion(input2, structure=footprint, iterations=1)# compute average surface distance# Note: scipys distance transform is calculated only inside the borders of the# foreground objects, therefore the input has to be reverseddt = distance_transform_edt(~input2_border...
>>> from scipy import ndimage >>> import numpy as np >>> a = np.zeros((5,5), dtype=int) >>> a[1:4, 1:4] = 1; a[4, 4] = 1 >>> a array([[0, 0, 0, 0, 0], [0, 1, 1, 1, 0], [0, 1, 1, 1, 0], [0, 1, 1, 1, 0], [0, 0, 0, 0, 1]])...
obdr = label_mask^binary_dilation(label_mask, struct) ibdr = label_mask^binary_erosion(label_mask, struct) yob, xob = y[obdr], x[obdr] ynb, xnb = yob.reshape(-1,1)+shifty, xob.reshape(-1,1)+shiftx wallnb = np.min(map_coords(wall, (ynb, xnb))*(map_coords(ibdr, (ynb...