Python实现PS滤镜特效之扇形变换效果示例

这篇文章主要介绍了Python实现PS滤镜特效之扇形变换效果,结合实例形式分析了Python实现PS滤镜扇形变换效果的原理与相关操作技巧,需要的朋友可以参考下

本文实例讲述了Python实现PS滤镜特效之扇形变换效果分享给大家供大家参考,具体如下:

这里用 Python 实现 PS 滤镜中的一种几何变换特效,称为扇形变换,将图像扭曲成一个扇形,具体的算法原理和效果图可以参考附录说明

import numpy as np from skimage import img_as_float import matplotlib.pyplot as plt from skimage import io import math import numpy.matlib file_name2='D:/Visual Effects/PS Algorithm/4.jpg' img=io.imread(file_name2) img = img_as_float(img) # control the radius of the inner circle radius = 150 # control the distance between the inner circle and outer circle high = 200 angle = 0 spreadAngle = math.pi # set the center of the circle, proportion of the image size centerX = 0.5 centerY = 1.0 row, col, channel = img.shape icenterX = col * centerX icenterY = row * centerY img_out = img * 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) xx_dif = x_mask - icenterX yy_dif = y_mask - icenterY theta = np.arctan2(-yy_dif, -xx_dif+0.0001) r = np.sqrt(xx_dif*xx_dif + yy_dif * yy_dif) theta = np.mod(theta, 2 * math.pi) x1_mask = col * theta/(spreadAngle+0.00001) y1_mask = row * (1-(r-radius)/(high+0.00001)) ''' mask = x1_mask (col - 1) x1_mask = x1_mask * (1 - mask) + (x1_mask * 0 + col -2) * mask mask = y1_mask (row -1) y1_mask = y1_mask * (1 - mask) + (y1_mask * 0 + row -2) * mask ''' int_x = np.floor (x1_mask) int_x = int_x.astype(int) int_y = np.floor (y1_mask) int_y = int_y.astype(int) for ii in range(row): for jj in range (col): new_xx = int_x [ii, jj] new_yy = int_y [ii, jj] if x1_mask [ii, jj] col -1 : continue if y1_mask [ii, jj] row -1 : continue img_out[ii, jj, :] = img[new_yy, new_xx, :] plt.figure (1) plt.title('www.html.cn') plt.imshow (img) plt.axis('off') plt.figure (2) plt.title('www.html.cn') plt.imshow (img_out) plt.axis('off') plt.show()

附录:PS 滤镜― ―扇形warp

clc; clear all; close all; addpath('E:PhotoShop AlgortihmImage ProcessingPS Algorithm'); I=imread('4.jpg'); I=double(I); Image=I/255; [height, width, depth]=size(Image); % set the parameters radius = 150; % control the radius of the inner circle high = 200; % control the distance between the inner circle and outer circle angle = 0; spreadAngle=pi; centerX = 0.5; % set the center of the circle, proportion of the image size centerY = 1.0; icenterX=width*centerX; icenterY=height*centerY; Image_new=Image*0; for i=1:height for j=1:width dx=j-icenterX; dy=i-icenterY; theta=atan2(-dy, -dx)+angle; r=sqrt(dy*dy+dx*dx); theta=mod(theta, 2*pi); x=width * theta/(spreadAngle+0.00001); y=height * (1-(r-radius)/(high+0.00001)); % % if (x=width) x=width-1; end; % % if (y>=height) y=height-1; end; % % if (y=width) continue; end; if (y>=height) continue; end; if (y

参考来源:http://www.jhlabs.com/index.html

本例Python运行效果

原图

效果

更多关于Python相关内容感兴趣的读者可查看本站专题:《Python图片操作技巧总结》、《Python数据结构与算法教程》、《Python Socket编程技巧总结》、《Python函数使用技巧总结》、《Python字符串操作技巧汇总》、《Python入门与进阶经典教程》及《Python文件与目录操作技巧汇总》

希望本文所述对大家Python程序设计有所帮助。

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