import numpy as np
import matplotlib.pyplot as plt
from skimage import io
from skimage.segmentation import slic
import numpy.matlib
import random
file_name='C:/Users/xpp/Desktop/Lena.png';
img=io.imread(file_name)
row,col,channel=img.shape
#颜色映射
color_map=img.copy()
rNW=0.5
rNE=1.0
rSW=0.0
rSE=0.5
gNW=0.0
gNE=0.5
gSW=0.0
gSE=1.0
bNW=1.0
bNE=0.0
bSW=0.5
bSE=0.0
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)
fx=x_mask*1.0/col
fy=y_mask*1.0/row
p=rNW (rNE-rNW)*fx
q=rSW (rSE-rSW)*fx
r=(p (q-p)*fy )
r[r<0]=0
r[r>1]=1
p=gNW (gNE-gNW)*fx
q=gSW (gSE-gSW)*fx
g=(p (q-p)*fy )
g[g<0]=0
g[g>1]=1
p=bNW (bNE-bNW)*fx
q=bSW (bSE-bSW)*fx
b=(p (q-p)*fy )
b[b<0]=0.0
b[b>1]=1.0
color_map[:,:,0]=r*255
color_map[:,:,1]=g*255
color_map[:,:,2]=b*255
#图像分割
N_block=100
segments=slic(img,n_segments=N_block,compactness=10)
seg_img=img.copy()
T_mask=img.copy()
for i in range(N_block):
mask=(segments==i)
T_mask[:,:,0]=mask
T_mask[:,:,1]=mask
T_mask[:,:,2]=mask
x_ind=int(random.random()*(col-1))
y_ind=int(random.random()*(row-1))
color=color_map[y_ind,x_ind,:]
T_img=seg_img*T_mask
T_img=color
seg_img=seg_img*(1-T_mask) T_img*T_mask
plt.figure(2)
plt.imshow(seg_img)
plt.show()
算法：图像抽象画风是图像分割和随机采样生成抽象画风的图像特效。
