Image.mean#

Image.mean(**kwargs: Any) → generic | ndarray[source]#

Mean value of all pixels

Parameters:

kwargs (dict) – additional keyword arguments passed to numpy.nanmean

Returns:

mean value

Example:

>>> from machinevisiontoolbox import Image
>>> img = Image.Read('flowers1.png')
>>> img.mean()  # mean over all planes
np.float64(105.4632164514867)
>>> img.mean(axis=(0,1))  # per-plane mean
array([103.68  , 112.0241, 100.6856])

Note

  • The return value type is the same as the image type.

  • NaN values are ignored

  • For axis remember the axes are in NumPy order: 0=rows, 1=columns, 2=planes.

Seealso:

stats hist Hough std median numpy.nanmean numnan