(编辑:jimmy 日期: 2024/11/16 浏览:2)
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()
原图:
效果图:
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希望本文所述对大家Python程序设计有所帮助。