Example of special wave effects for implementing the PS filter function in Python, python Filter

Example of special wave effects for implementing the PS filter function in Python, python Filter

This article describes how to implement the PS filter function in Python. We will share this with you for your reference. The details are as follows:

Here, you can use Python to implement the Wave Effect of the PS filter. For more information about the effect, see the appendix.

import numpy as npfrom skimage import img_as_floatimport matplotlib.pyplot as pltfrom skimage import ioimport numpy.matlibimport mathfile_name2='D:/Visual Effects/PS Algorithm/4.jpg'img=io.imread(file_name2)img = img_as_float(img)row, col, channel = img.shapeimg_out = img * 1.0alpha = 70.0beta = 30.0degree = 20.0center_x = (col-1)/2.0center_y = (row-1)/2.0xx = 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_xyy_dif = center_y - y_maskx = degree * np.sin(2 * math.pi * yy_dif / alpha) + xx_dify = degree * np.cos(2 * math.pi * xx_dif / beta) + yy_difx_new = x + center_xy_new = center_y - y 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.title('www.jb51.net')plt.imshow (img)plt.axis('off')plt.figure (2)plt.title('www.jb51.net')plt.imshow (img_out)plt.axis('off')plt.show()

Appendix: PS filter-wave

% Wave Effect clc; clear all; close all; addpath ('e: \ PhotoShop Algortihm \ Image Processing \ PS algorithm'{ I =imread('4.jpg '); image = double (I); % Image = 0.2989 * I (:,:, 1) + 0.5870 * I (:,:, 2) + 0.1140 * I (:,:, 3); [row, col, channel] = size (Image); R = floor (max (row, col)/2); Image_new = Image; Degree = 30; % control the degree of distortion Center_X = (col + 1)/2; Center_Y = (row + 1)/2; for I = 1: row for j = 1: col x0 = j-Center_X; y0 = Center_Y-i; x = Degree * sin (2 * pi * y0/128) + x0; y = Degree * cos (2 * pi * x0/128) + y0; x = x + col/2; y = row/2-y; if (x> 1 & x <col & y <row & y> 1) x1 = floor (x); y1 = floor (y); p = x-x1; q = y-y1; Image_new (I, j, :) = (1-p) * (1-q) * Image (y1, x1, :) + p * (1-q) * Image (y1, x1 + 1 ,:)... + q * (1-p) * Image (y1 + 1, x1, :) + p * q * Image (y1 + 1, x1 + 1, :); end endfigure, imshow (Image_new/255 );

In this example, the Python running effect is as follows:

Source image