blur_image

ketos.audio.utils.filter.blur_image(img, size=20, sigma=5, gaussian=True)

Smooth the input image using a median or Gaussian blur filter.

Note that the input image is recasted as np.float32.

This is essentially a wrapper around the scipy.ndimage.median_filter and scipy.ndimage.gaussian_filter methods.

For further details, see https://docs.scipy.org/doc/scipy/reference/ndimage.html

Args:

imgnumpy array

Image to be processed.

size: int

Only used by the median filter. Describes the shape that is taken from the input array, at every element position, to define the input to the filter function.

sigma: float or array

Only used by the Gaussian filter. Standard deviation for Gaussian kernel. May be given as a single number, in which case all axes have the same standard deviation, or as an array, allowing for the axes to have different standard deviations.

Gaussian: bool

Switch between median and Gaussian (default) filter

Returns:

blur_img: numpy array

Blurred image.

Example:

>>> from ketos.audio.utils.filter import blur_image
>>> img = np.array([[0,0,0],
...                 [0,1,0],
...                 [0,0,0]])
>>> # blur using Gaussian filter with sigma of 0.5
>>> img_blur = blur_image(img, sigma=0.5)
>>> img_blur = np.around(img_blur, decimals=2) # only keep up to two decimals
>>> print(img_blur)
[[0.01 0.08 0.01]
 [0.08 0.62 0.08]
 [0.01 0.08 0.01]]