Python实现PS滤镜的万花筒效果示例
本文实例讲述了Python实现PS滤镜的万花筒效果。分享给大家供大家参考,具体如下:
这里用 Python 实现 PS 的一种滤镜效果,称为万花筒。也是对图像做各种扭曲变换,最后图像呈现的效果就像从万花筒中看到的一样:
图像的效果可以参考附录说明。具体Python代码如下:
import matplotlib.pyplot as plt from skimage import io from skimage import img_as_float import numpy as np import numpy.matlib import math file_name='D:/Visual Effects/PS Algorithm/4.jpg'; img=io.imread(file_name) img = img_as_float(img) row, col, channel = img.shape # set the parameters radius = 100.0 angle = math.pi/3 angle2 = math.pi/4 sides = 10.0 # set the center of the circle, proportion of the image size centerX = 0.5 centerY = 0.5 iWidth=col iHeight=row center_x=iWidth*centerX center_y=iHeight*centerY 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 = y_mask - center_y r = np.sqrt(xx_dif * xx_dif + yy_dif * yy_dif) theta = np.arctan2(yy_dif, xx_dif+0.0001) - angle - angle2 temp_theta=theta/math.pi*sides*0.5 temp_r = np.mod(temp_theta, 1.0) mask_1 = temp_r < 0.5 theta = temp_r * 2 * mask_1 + (1-temp_r) * 2 * (1 - mask_1) radius_c=radius/np.cos(theta) temp_r = np.mod (r/radius_c, 1.0) mask_1 = temp_r < 0.5 r = radius_c * (temp_r * 2 * mask_1 + (1-temp_r) * 2 * (1 - mask_1)) theta = theta + angle x1_mask = r * np.cos(theta) + center_x y1_mask = r * np.sin(theta) + center_y mask = x1_mask < 0 x1_mask = x1_mask * (1 - mask) mask = x1_mask > (col - 1) x1_mask = x1_mask * (1 - mask) + (x1_mask * 0 + col -2) * mask mask = y1_mask < 0 y1_mask = y1_mask * (1 - mask) mask = y1_mask > (row -1) y1_mask = y1_mask * (1 - mask) + (y1_mask * 0 + row -2) * mask img_out = img * 1.0 int_x = np.floor (x1_mask) int_x = int_x.astype(int) int_y = np.floor (y1_mask) int_y = int_y.astype(int) p_mask = x1_mask - int_x q_mask = y1_mask - int_y img_out = img * 1.0 for ii in range(row): for jj in range (col): new_xx = int_x [ii, jj] new_yy = int_y [ii, jj] # p = p_mask[ii, jj] # q = q_mask[ii, jj] 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()
附:PS 滤镜万花筒效果原理
clc; clear all; close all; addpath('E:\PhotoShop Algortihm\Image Processing\PS Algorithm'); I=imread('4.jpg'); I=double(I); Image=I/255; sz=size(Image); % set the parameters radius = 150; angle = pi/4; angle2=pi/4; sides=10; centerX = 0.5; % set the center of the circle, proportion of the image size centerY = 0.5; iWidth=sz(2); iHeight=sz(1); icenterX=iWidth*centerX; icenterY=iHeight*centerY; Image_new=Image; for i=1:sz(1) for j=1:sz(2) dx=j-icenterX; dy=i-icenterY; r=sqrt(dy*dy+dx*dx); theta=atan2(dy, dx)-angle-angle2; temp_theta=theta/pi*sides*0.5 ; theta=triangle(temp_theta); if (radius) c=cos(theta); radius_c=radius/c; r=radius_c * triangle(r/radius_c); end theta=theta+angle; x=r * cos(theta)+icenterX; y=r * sin(theta)+icenterY; if (x<=1) x=1; end if (x>=sz(2)) x=sz(2)-1; end; if (y>=sz(1)) y=sz(1)-1; end; if (y<1) y=1; end; % % % if (x<=1) continue; end % % % if (x>=sz(2)) continue; end; % % % if (y>=sz(1)) continue; end; % % % if (y<1) continue; end; 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 imshow(Image_new) imwrite(Image_new, 'out.jpg');
参考来源:http://www.jhlabs.com/index.html
原图:
效果图:
更多关于Python相关内容感兴趣的读者可查看本站专题:《Python图片操作技巧总结》、《Python数据结构与算法教程》、《Python Socket编程技巧总结》、《Python函数使用技巧总结》、《Python字符串操作技巧汇总》、《Python入门与进阶经典教程》及《Python文件与目录操作技巧汇总》
希望本文所述对大家Python程序设计有所帮助。
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