在Python中歪曲数组 [英] Skewing an array in Python

问题描述

我有一个2D数组，我将使用 scipy.misc.toimage（）保存为灰度图像。在这之前，我想将图像倾斜一个给定的角度，插值如 scipy.ndimage.interpolation.rotate（）：

I have a 2D array that I will save as a grayscale image using scipy.misc.toimage(). Before doing so, I want to skew the image by a given angle, interpolating like scipy.ndimage.interpolation.rotate():

上图仅用于说明偏斜过程。我知道我必须放大我的图像才能包含偏斜的版本。我怎样才能做到这一点？我更喜欢使用scipy。

The image above is just to illustrate the skewing process. I am aware that I have to enlarge my image in order to contain the skewed version. How can I achieve this? I would prefer to use scipy for this.

推荐答案

这个脚本可以做到这一点。

This script can do that.

a=imread("sorNB.png")
h,l=a.shape
dl=50
b=numpy.zeros((h,l+dl),dtype=a.dtype)
for y in range(h):
    dec=(dl*(h-y))//h
    b[y,dec:dec+l]=a[y,:]

由于内部作业（b [y，dec：dec + l] = a [y，：]）是纯粹的numpy，这非常快。

Since the inner assignment (b[y,dec:dec+l]=a[y,:]) is pure numpy, this is very fast.

编辑

感谢ivan_pozdeev。插值的方法：

thanks to ivan_pozdeev. a way for interpolation :

from scipy.ndimage.interpolation import geometric_transform
a=imread("sorNB.png")
h,l=a.shape
def mapping(lc):
    l,c=lc
    dec=(dl*(l-h))/h
    return l,c+dec
figure(1)    
dl=50;c=geometric_transform(a,mapping,(h,l+dl),order=5,mode='nearest')
imshow (concatenate((a,zeros((225,50)),c),axis=-1),cmap=cm.gray)

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