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:
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
|
import numpy as np
import math
import numpy.matlib
from skimage import io
import random
from skimage import img_as_float
import matplotlib.pyplot as plt
def 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, :] = (np.mod((np.floor(np.random.rand( 1 , 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, g3
def 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, j, :] = g2[b10, :]
q3[i, j, :] = g2[b01, :]
q4[i, j, :] = 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 out
file_name = 'D:/Visual Effects/PS Algorithm/4.jpg' ;
img = io.imread(file_name)
img = img_as_float(img)
row, col, channel = img.shape
xScale = 25.0
yScale = 25.0
turbulence = 0.25
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)
x_val = x_mask / xScale
y_val = y_mask / yScale
Index = 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, g1, g2, g3 = Init_arr()
Noise_out = Noise_2(x_val, y_val, P, g2)
Noise_out = 127 * (Noise_out + 1 )
Dis = np.floor(Noise_out)
Dis[Dis> 255 ] = 255
Dis[Dis< 0 ] = 0
Dis = 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.zyiz.net' )
plt.imshow(img)
plt.axis( 'off' );
plt.figure( 2 )
plt.title( 'www.zyiz.net' )
plt.imshow(img_out)
plt.axis( 'off' );
plt.show();
|
运行效果:
附:PS 滤镜 Marble 效果原理
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
|
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, g1, g2, g3] = init_arr();
for ii = 1 :height
% % [ind, g1, g2, 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,jj,:) = ( 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
希望本文所述对大家Python程序设计有所帮助。
原文链接:http://blog.csdn.net/matrix_space/article/details/72283287