实现效果
实现代码
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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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原文链接:https://www.cnblogs.com/mtcnn/p/9412386.html