实现效果: 实现代码 import numpy as npfrom skimage import img_as_floatimport matplotlib.pyplot as pltfrom skimage import ioimport mathimport numpy.matlibfile_name2='D:/2020121173119242.png' # 图片路径img=io.imread(file_name2)im
实现效果:
实现代码
import numpy as np from skimage import img_as_float import matplotlib.pyplot as plt from skimage import io import math import numpy.matlib file_name2='D:/2020121173119242.png' # 图片路径 img=io.imread(file_name2) img = img_as_float(img) row, col, channel = img.shape img_out = img * 1.0 degree = 70 center_x = (col-1)/2.0 center_y = (row-1)/2.0 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) xx_dif = x_mask - center_x yy_dif = center_y - y_mask r = np.sqrt(xx_dif * xx_dif + yy_dif * yy_dif) theta = np.arctan(yy_dif / xx_dif) mask_1 = xx_dif < 0 theta = theta * (1 - mask_1) + (theta + math.pi) * mask_1 theta = theta + r/degree x_new = r * np.cos(theta) + center_x y_new = center_y - r * np.sin(theta) int_x = np.floor (x_new) int_x = int_x.astype(int) int_y = np.floor (y_new) int_y = int_y.astype(int) for ii in range(row): for jj in range (col): new_xx = int_x [ii, jj] new_yy = int_y [ii, jj] if x_new [ii, jj] < 0 or x_new [ii, jj] > col -1 : continue if y_new [ii, jj] < 0 or y_new [ii, jj] > row -1 : continue img_out[ii, jj, :] = img[new_yy, new_xx, :] plt.figure (1) plt.imshow (img) plt.axis('off') plt.figure (2) plt.imshow (img_out) plt.axis('off') plt.show()
以上就是Python 实现 PS 滤镜的旋涡特效的详细内容,更多关于python ps滤镜漩涡特效的资料请关注易盾网络其它相关文章!