machinevisiontoolbox.Image.mean
- Image.mean(*args, **kwargs)[source]
Mean value of all pixels
- Parameters:
args – additional positional arguments to
numpy.mean
kwargs – additional keyword arguments to
numpy.mean
- Returns:
mean value
Example:
>>> from machinevisiontoolbox import Image >>> img = Image.Read('flowers1.png') >>> img.mean() 105.4632164514867 >>> img = Image.Read('flowers1.png', dtype='float32') >>> img.mean(axis=2) array([[0.2092, 0.2065, 0.2837, ..., 0.8471, 0.8523, 0.949 ], [0.2026, 0.2092, 0.2863, ..., 0.881 , 0.915 , 0.9987], [0.2039, 0.2065, 0.2719, ..., 0.7869, 0.9699, 0.9948], ..., [0.3595, 0.2928, 0.2784, ..., 0.366 , 0.3739, 0.3908], [0.3438, 0.2837, 0.2471, ..., 0.3569, 0.3634, 0.3804], [0.3216, 0.268 , 0.2353, ..., 0.3386, 0.3529, 0.3686]], dtype=float32)
- Note:
The return value type is the same as the image type.
By default the result is a scalar computed over all pixels, if the
axis
option is given the results is a 1D or 2D NumPy array.
- Seealso: