Python Scipy–ndi image . spline _ filter 1d()函数
原文:https://www.geesforgeks.org/python-scipy-ndi image-spline _ filter 1d-function/
该方法用于沿给定轴计算一维样条滤波器。这些由样条过滤器过滤。
语法:scipy . ndi image . spline _ filter 1d(输入，顺序=3，轴=-1，输出= < class 'numpy.float64' >)
参数
输入:array _ like–输入数组
顺序:int–样条的顺序，默认为 3。
轴: int，–应用样条线过滤器的轴。默认为最后一个轴。
输出:n 数组–放置输出的数组，或返回数组的数据类型。默认值为 numpy.float64。
例 1:
蟒蛇 3
# importing spline filter with one dimension.
from scipy.ndimage import spline_filter1d
# importing matplot library for visualization
import matplotlib.pyplot as plt
# importing munpy module
import numpy as np
# creating an image
geek_image = np.eye(80)
# returns an image array format
geek_image[40, :] = 1.0
print(geek_image)
输出:
例 2:
蟒蛇 3
# importing spline filter with one dimension.
from scipy.ndimage import spline_filter1d
# importing matplot library for visualization
import matplotlib.pyplot as plt
# importing munpy module
import numpy as np
# creating an image
geek_image = np.eye(80)
geek_image[40, :] = 1.0
# in axis=0
axis_0 = spline_filter1d(geek_image, axis=0)
# in axis=1
axis_1 = spline_filter1d(geek_image, axis=1)
f, ax = plt.subplots(1, 3, sharex=True)
for ind, data in enumerate([[geek_image, "geek_image original"],
[axis_0, "spline filter in axis 0"],
[axis_1, "spline filter in axis 1"]]):
ax[ind].imshow(data[0], cmap='gray_r')
# giving title
ax[ind].set_title(data[1])
# orientation layout of our image
plt.tight_layout()
# to show image
plt.show()
输出:
