Python实现PS滤镜功能之波浪特效示例
作者:Matrix_11
这篇文章主要介绍了Python实现PS滤镜功能之波浪特效,结合实例形式分析了Python实现PS滤镜波浪特效的原理与相关操作技巧,需要的朋友可以参考下
本文实例讲述了Python实现PS滤镜功能之波浪特效。分享给大家供大家参考,具体如下:
这里用 Python 实现 PS 滤镜的波浪特效,具体效果可以参考附录说明
import numpy as np from skimage import img_as_float import matplotlib.pyplot as plt from skimage import io import numpy.matlib import math file_name2='D:/Visual Effects/PS Algorithm/4.jpg' img=io.imread(file_name2) img = img_as_float(img) row, col, channel = img.shape img_out = img * 1.0 alpha = 70.0 beta = 30.0 degree = 20.0 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 x = degree * np.sin(2 * math.pi * yy_dif / alpha) + xx_dif y = degree * np.cos(2 * math.pi * xx_dif / beta) + yy_dif x_new = x + center_x y_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()
附录:PS 滤镜——波浪 wave
%%% Wave %%% 波浪效果 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; % 控制扭曲的程度 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 end end figure, imshow(Image_new/255);
本例Python运行效果:
原图
效果图
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