Python实现PS滤镜的万花筒效果示例，python万花筒

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');