Python實(shí)現(xiàn)PS濾鏡的萬(wàn)花筒效果示例

更新時(shí)間：2018年01月23日 08:56:40 作者：Matrix_11

這篇文章主要介紹了Python實(shí)現(xiàn)PS濾鏡的萬(wàn)花筒效果,結(jié)合實(shí)例形式分析了Python基于skimage模塊操作圖片實(shí)現(xiàn)PS濾鏡萬(wàn)花筒效果的原理與相關(guān)操作技巧,需要的朋友可以參考下

本文實(shí)例講述了Python實(shí)現(xiàn)PS濾鏡的萬(wàn)花筒效果。分享給大家供大家參考，具體如下：

這里用 Python 實(shí)現(xiàn) PS 的一種濾鏡效果，稱為萬(wàn)花筒。也是對(duì)圖像做各種扭曲變換，最后圖像呈現(xiàn)的效果就像從萬(wàn)花筒中看到的一樣：

圖像的效果可以參考附錄說(shuō)明。具體Python代碼如下：

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 濾鏡萬(wàn)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');

參考來(lái)源：http://www.jhlabs.com/index.html

原圖：