如何用Python编写程序实现PS径向模糊滤镜效果？

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python实现效果：读取图像并转换为浮点数实现代码：from skimage import img_as_floatimport matplotlib.pyplot as pltfrom skimage import ioimport numpy as npimport numpy.matlib

file_name='D:/2020121173119242.png'

实现效果

实现代码

from skimage import img_as_float import matplotlib.pyplot as plt from skimage import io import numpy as np import numpy.matlib file_name='D:/2020121173119242.png' # 图片路径 img=io.imread(file_name) img = img_as_float(img) img_out = img.copy() row, col, channel = img.shape xx = np.arange (col) yy = np.arange (row) x_mask = numpy.matlib.repmat (xx, row, 1) y_mask = numpy.matlib.repmat (yy, col, 1) y_mask = np.transpose(y_mask) center_y = (row -1) / 2.0 center_x = (col -1) / 2.0 R = np.sqrt((x_mask - center_x) **2 + (y_mask - center_y) ** 2) angle = np.arctan2(y_mask - center_y , x_mask - center_x) Num = 20 arr = np.arange(Num) for i in range (row): for j in range (col): R_arr = R[i, j] - arr R_arr[R_arr < 0] = 0 new_x = R_arr * np.cos(angle[i,j]) + center_x new_y = R_arr * np.sin(angle[i,j]) + center_y int_x = new_x.astype(int) int_y = new_y.astype(int) int_x[int_x > col-1] = col - 1 int_x[int_x < 0] = 0 int_y[int_y < 0] = 0 int_y[int_y > row -1] = row -1 img_out[i,j,0] = img[int_y, int_x, 0].sum()/Num img_out[i,j,1] = img[int_y, int_x, 1].sum()/Num img_out[i,j,2] = img[int_y, int_x, 2].sum()/Num plt.figure(1) plt.imshow(img) plt.axis('off') plt.figure(2) plt.imshow(img_out) plt.axis('off') plt.show()

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