[SciPy-User] Gaussian Filter

[Matthieu Brucher]

I don't have OpenCV here, so I can't say for sure but, what is the
relative amplitude of the difference? OpenCV works on floats or
doubles? It may be due to a type difference or a small difference in
the algorithms.

Matthieu

2009/9/4 Brian Thorne <hardbyte at gmail.com>:
> Similar question, but now a bit harder. I have this code (pieced together
> from a few files) that does a gaussian filter on a single image in both
> OpenCV and in SciPy.
> It is now at a point where I cannot tell them apart with a visual
> inspection, but a imshow(image1 - image2) begs to differ. Is it going to be
> possible to get the exact same output?
>
>
> from opencv import cv
> from opencv import adaptors
> from __future__ import division
> import numpy as np
> from numpy import array, uint8
> from scipy import signal, ndimage
> @scipyFromOpenCV
> def gaussianBlur(np_image):
>     """Blur an image with scipy"""
>     sigma = opencvFilt2sigma(43.0)
>
>     result = ndimage.filters.gaussian_filter(np_image,
>                             sigma=(sigma, sigma, 0),
>                             order=0,
>                             mode='reflect'
>                             )
>     return result
> def gaussianBlur(image, filterSize=43, sigma=opencvFilt2sigma(43)):
>     """Blur an image with a particular strength filter.
>     Default is 43, 139 gives a very strong blur, but takes a while
>     """
>
>     # Carry out the filter operation
>     cv.cvSmooth(image, image, cv.CV_GAUSSIAN, filterSize, 0, sigma)
>     return image
> def opencvFilt2sigma(size):
>     """OpenCV defaults to making sigma up with this formula.
>     Learning OpenCV: computer vision with the OpenCV library
>     By Gary Bradski, Adrian Kaehler pg 112"""
>     return (( size*0.5 ) - 1)*0.30 + 0.80
> class scipyFromOpenCV(object):
>     """This decorator can be used to wrap a function that takes
>     and returns a numpy array into one that takes and retuns an
>     opencv CvMat.
>     """
>     def __init__(self, f):
>         self.f = f
>     def __call__(self, image):
>         # Convert CvMat to ndarray
>         np_image = adaptors.Ipl2NumPy(image)
>
>         # Call the original function
>         np_image_filtered = self.f(np_image)
>
>         # Convert back to CvMat
>         return adaptors.NumPy2Ipl(np_image_filtered)
> cheers,
> Brian
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>



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