Python: PS滤镜--径向模糊

最新推荐文章于 2023-11-08 14:37:16 发布

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最新推荐文章于 2023-11-08 14:37:16 发布

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原文链接：http://www.cnblogs.com/mtcnn/p/9412386.html

本文介绍如何使用Python实现PS滤镜中的径向模糊效果。通过解析图像像素位置与中心点的距离及角度来生成模糊效果，实现了从读取图片到应用特效并展示结果的全过程。

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本文用 Python 实现 PS 滤镜中的径向模糊特效，具体的算法原理和效果可以参考之前的博客：

http://blog.youkuaiyun.com/matrix_space/article/details/39211735

from skimage import img_as_float
import matplotlib.pyplot as plt
from skimage import io
import numpy as np
import numpy.matlib

file_name='D:/Visual Effects/PS Algorithm/4.jpg';
img=io.imread(file_name)

img = img_as_float(img)

img_out = img.copy()

row, col, channel = img.shape

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)

center_y = (row -1) / 2.0
center_x = (col -1) / 2.0

R = np.sqrt((x_mask - center_x) **2 + (y_mask - center_y) ** 2)

angle = np.arctan2(y_mask - center_y , x_mask - center_x)

Num = 20
arr = np.arange(Num)

for i in range (row):
    for j in range (col):

        R_arr = R[i, j] - arr   
        R_arr[R_arr < 0] = 0

        new_x = R_arr * np.cos(angle[i,j]) + center_x
        new_y = R_arr * np.sin(angle[i,j]) + center_y

        int_x = new_x.astype(int)
        int_y = new_y.astype(int)

        int_x[int_x > col-1] = col - 1
        int_x[int_x < 0] = 0
        int_y[int_y < 0] = 0
        int_y[int_y > row -1] = row -1

        img_out[i,j,0] = img[int_y, int_x, 0].sum()/Num
        img_out[i,j,1] = img[int_y, int_x, 1].sum()/Num
        img_out[i,j,2] = img[int_y, int_x, 2].sum()/Num


plt.figure(1)
plt.imshow(img)
plt.axis('off')

plt.figure(2)
plt.imshow(img_out)
plt.axis('off')

plt.show()