Python实现PS图像抽象画风效果的方法_Python

本文实例讲述了Python实现PS图像抽象画风效果的方法。分享给大家供大家参考，具体如下：

今天介绍一种基于图像分割和color map 随机采样生成一种抽象画风的图像特效，简单来说，就是先生成一张 color map 图，颜色是渐变的，然后针对要处理的图像，进行分割，这里用的是 SLIC 分割算法，然后从 color map 中随机采样，将采样得到的像素值赋予分割后的图像区域。

									# -*- coding: utf-8 -*-

									"""

									Created on Sun Aug 20 08:31:04 2017

									@author: shiyi

									"""

									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='D:/Visual Effects/PS Algorithm/9.jpg';

									img=io.imread(file_name)

									row, col, channel = img.shape

									# define the colormap

									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

									# segment the image

									N_block = 100

									segments = slic(img, n_segments=N_block, compactness=10)

									# plt.imshow(segments, plt.cm.gray)

									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()