def filterGaussian(img, size=(5, 5), stdv=0):
    'Summary of filterGaussian\n    This will apply a noise reduction filter, we will use s 5x5 Gaussian filter to smooth\n        the image to lower the sensitivity to noise. (The smaller the size the less visible the blur)\n\n    To populate the Gaussian matrix we will use a kernel of normally distributed[stdv=1] numbers which will\n        set each pixel value equal to the weighted average of its neighboor pixels\n\n    The Gaussian distribution:\n        Gd = (1/2pi*stdv^2)exp(-((i-(k+1)^2) + (j - (k+1)^2))/(2*stdv^2))\n\n        i,j E [1,2k+1] for the kernel of size: (2k+1)x(2k+1) \n    '
    if (not isCV(img)):
        raise ValueError('Image not in np.array format')
    if (not isinstance(size, tuple)):
        raise ValueError('filterGaussian: Size for Gaussian filter not tuple')
    return cv.GaussianBlur(img, size, stdv)
Summary of filterGaussian
This will apply a noise reduction filter, we will use s 5x5 Gaussian filter to smooth
    the image to lower the sensitivity to noise. (The smaller the size the less visible the blur)

To populate the Gaussian matrix we will use a kernel of normally distributed[stdv=1] numbers which will
    set each pixel value equal to the weighted average of its neighboor pixels

The Gaussian distribution:
    Gd = (1/2pi*stdv^2)exp(-((i-(k+1)^2) + (j - (k+1)^2))/(2*stdv^2))

    i,j E [1,2k+1] for the kernel of size: (2k+1)x(2k+1)
def filterGaussian(img, size=(5, 5), stdv=0):
    'Summary of filterGaussian\n    This will apply a noise reduction filter, we will use s 5x5 Gaussian filter to smooth\n        the image to lower the sensitivity to noise. (The smaller the size the less visible the blur)\n\n    To populate the Gaussian matrix we will use a kernel of normally distributed[stdv=1] numbers which will\n        set each pixel value equal to the weighted average of its neighboor pixels\n\n    The Gaussian distribution:\n        Gd = (1/2pi*stdv^2)exp(-((i-(k+1)^2) + (j - (k+1)^2))/(2*stdv^2))\n\n        i,j E [1,2k+1] for the kernel of size: (2k+1)x(2k+1) \n    '
    if (not isCV(img)):
        raise ValueError('Image not in np.array format')
    if (not isinstance(size, tuple)):
        raise ValueError('filterGaussian: Size for Gaussian filter not tuple')
    return cv.GaussianBlur(img, size, stdv)