Matlab的Conv2等价于OpenCV [英] Matlab's Conv2 equivalent in OpenCV

问题描述

我一直在尝试使用OpenCV进行2D矩阵的卷积。我实际上通过了此代码 http：// blog.timmlinder.com/2011/07/opencv-equivalent-to-matlabs-conv2-function/#respond ，但它只在肯定的情况下产生正确的答案。在Matlab中有一个简单的函数如conv2在OpenCV或C ++？

I have been trying to do Convolution of a 2D Matrix using OpenCV. I actually went through this code http://blog.timmlinder.com/2011/07/opencv-equivalent-to-matlabs-conv2-function/#respond but it yields correct answers only in positive cases. Is there a simple function like conv2 in Matlab for OpenCV or C++?

以下是一个示例：

A= [
  1 -2
  3  4
]

[ - 0.707 0.707]

由MATLAB的conv2产生的结果是

And the result as by conv2 from Matlab is

 -0.7071    2.1213   -1.4142
 -2.1213   -0.7071    2.8284

有些函数在OpenCV或C ++中计算此输出？

Some function to compute this output in OpenCV or C++? I will be grateful for a response.

推荐答案

如果您想要一个独占的OpenCV解决方案，请使用 cv2.filter2D <强>功能。但是如果你想得到和matlab一样的正确输出，你应该调整borderType标志。

If you want an exclusive OpenCV solution, use cv2.filter2D function. But you should adjust the borderType flag if you want to get the correct output as that of matlab.

>>> A = np.array([ [1,-2],[3,4] ]).astype('float32')
>>> A
array([[ 1., -2.],
       [ 3.,  4.]], dtype=float32)

>>> B = np.array([[ 0.707,-0.707]])
>>> B
array([[ 0.707, -0.707]])

>>> cv2.filter2D(A2,-1,B,borderType = cv2.BORDER_CONSTANT)
array([[-0.70700002,  2.12100005, -1.41400003],
       [-2.12100005, -0.70700002,  2.82800007]], dtype=float32)

borderType很重要。要找到卷积，您需要在数组外部的值。如果你想得到matlab的输出，你需要传递cv2.BORDER_CONSTANT。请参阅输出大小大于输入。

borderType is important. To find the convolution you need values outside the array. If you want to get matlab like output, you need to pass cv2.BORDER_CONSTANT. See output is greater in size than input.

这篇关于Matlab的Conv2等价于OpenCV的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！