Python实现PS滤镜特效Marble Filter玻璃条纹扭曲效果示例

概述本文实例讲述了Python实现PS滤镜特效MarbleFilter玻璃条纹扭曲效果。分享给大家供大家参考，具体如下：

本文实例讲述了Python实现PS滤镜特效Marble Filter玻璃条纹扭曲效果。分享给大家供大家参考，具体如下：

这里用 Python 实现 PS 滤镜特效，Marble Filter,这种滤镜使图像产生不规则的扭曲，看起来像某种玻璃条纹， 具体的代码如下:

import numpy as npimport mathimport numpy.matlibfrom skimage import ioimport randomfrom skimage import img_as_floatimport matplotlib.pyplot as pltdef Init_arr():  B = 256  P = np.zeros((B+B+2,1))  g1 = np.zeros((B+B+2,1))  g2 = np.zeros((B+B+2,2))  g3 = np.zeros((B+B+2,3))  N_max = 1e6  for i in range(B+1):    P[i] = i    g1[i] = (((math.floor(random.random()*N_max)) % (2*B))-B)*1.0/B    g2[i,:] = (np.mod((np.floor(np.random.rand(1,2)*N_max)),(2*B))-B)*1.0/B    g2[i,:] = g2[i,:] / np.sum(g2[i,:] **2)    g3[i,3)*N_max)),(2*B))-B)*1.0/B    g3[i,:] = g3[i,:] / np.sum(g3[i,:] **2)  for i in range(B,-1,-1):    k = P[i]    j = math.floor(random.random()*N_max) % B    P [i] = P [j]    P [j] = k  P[B+1:2*B+2]=P[0:B+1];  g1[B+1:2*B+2]=g1[0:B+1];  g2[B+1:2*B+2,:]=g2[0:B+1,:]  g3[B+1:2*B+2,:]=g3[0:B+1,:]  P = P.astype(int)  return P,g1,g2,g3def Noise_2(x_val,y_val,P,g2):  BM=255  N=4096  t = x_val + N  bx0 = ((np.floor(t).astype(int)) & BM) + 1  bx1 = ((bx0 + 1).astype(int) & BM) + 1  rx0 = t - np.floor(t)  rx1 = rx0 - 1.0  t = y_val + N  by0 = ((np.floor(t).astype(int)) & BM) + 1  by1 = ((bx0 + 1).astype(int) & BM) + 1  ry0 = t - np.floor(t)  ry1 = rx0 - 1.0  sx = rx0 * rx0 * (3 - 2.0 * rx0)  sy = ry0 * ry0 * (3 - 2.0 * ry0)  row,col = x_val.shape  q1 = np.zeros((row,col,2))  q2 = q1.copy()  q3 = q1.copy()  q4 = q1.copy()  for i in range(row):    for j in range(col):      ind_i = P[bx0[i,j]]      ind_j = P[bx1[i,j]]      b00 = P[ind_i + by0[i,j]]      b01 = P[ind_i + by1[i,j]]      b10 = P[ind_j + by0[i,j]]      b11 = P[ind_j + by1[i,j]]      q1[i,j,:] = g2[b00,:]      q2[i,:] = g2[b10,:]      q3[i,:] = g2[b01,:]      q4[i,:] = g2[b11,:]  u1 = rx0 * q1[:,:,0] + ry0 * q1[:,1]  v1 = rx1 * q2[:,0] + ry1 * q2[:,1]  a = u1 + sx * (v1 - u1)  u2 = rx0 * q3[:,0] + ry0 * q3[:,1]  v2 = rx1 * q4[:,0] + ry1 * q4[:,1]  b = u2 + sx * (v2 - u2)  out = (a + sy * (b - a)) * 1.5  return outfile_name='D:/Visual Effects/PS Algorithm/4.jpg';img=io.imread(file_name)img = img_as_float(img)row,channel = img.shapexScale = 25.0yScale = 25.0turbulence =0.25xx = np.arange (col)yy = np.arange (row)x_mask = numpy.matlib.repmat (xx,row,1)y_mask = numpy.matlib.repmat (yy,1)y_mask = np.transpose(y_mask)x_val = x_mask / xScaley_val = y_mask / yScaleIndex = np.arange(256)sin_T=-yScale*np.sin(2*math.pi*(Index)/255*turbulence);cos_T=xScale*np.cos(2*math.pi*(Index)/255*turbulence)P,g3 = Init_arr()Noise_out = Noise_2(x_val,g2)Noise_out = 127 * (Noise_out + 1)dis = np.floor(Noise_out)dis[dis>255] = 255dis[dis<0] = 0dis = dis.astype(int)img_out = img.copy()for ii in range(row):  for jj in range(col):    new_x = jj + sin_T[dis[ii,jj]]    new_y = ii + cos_T[dis[ii,jj]]    if (new_x > 0 and new_x < col-1 and new_y > 0 and new_y < row-1):      int_x = int(new_x)      int_y = int(new_y)      img_out[ii,jj,:] = img[int_y,int_x,:]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();

运行效果：

@H_403_17@

附：PS 滤镜 Marble 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;  xScale = 20;  yScale = 20;  amount = 1;  turbulence =0.25;  Image_new=Image;  [height,wIDth,depth]=size(Image);  Index=1:256;  sin_T=-yScale*sin(2*pi*(Index-1)/256*turbulence);  cos_T=xScale*cos(2*pi*(Index-1)/256*turbulence);  [ind,g3]=init_arr();  for ii=1:height  % %   [ind,g3]=init_arr();    for jj=1:wIDth      dis=min(max( floor(127*(1+Noise2(jj/xScale,ii/yScale,ind,g2))),1),256);      x=jj+sin_T(dis);      y=ii+cos_T(dis);  % %     if (x<=1)   x=1; end  % %     if (x>=wIDth)  x=wIDth-1; end;  % %     if (y>=height) y=height-1; end;  % %     if (y<1) y=1;   end;  % %           if (x<=1)   continue; end      if (x>=wIDth)  continue; end;      if (y>=height) continue; end;      if (y<1) continue;   end;      x1=floor(x);      y1=floor(y);      p=x-x1;      q=y-y1;      Image_new(ii,:)=(1-p)*(1-q)*Image(y1,x1,:)+P*(1-q)*Image(y1,x1+1,:)...        +q*(1-p)*Image(y1+1,:)+P*q*Image(y1+1,:);     end  end  imshow(Image_new)  imwrite(Image_new,'out.jpg');

参考来源：http://www.jhlabs.com/index.html

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