Wand statistic() function in Python

Last Updated : 08 May, 2020

Statistic effect is similar to Spread effect, the only difference is that, it replaces each pixel with the result of a mathematical operation performed against neighboring pixel values.The width & height defines the size, or aperture, of the neighboring pixels. The type of statistic operations can be any of the following:

'gradient'
'maximum'
'mean'
'median'
'minimum'
'mode'
'nonpeak'
'root_mean_square'
'standard_deviation'

Syntax : wand.image.statistic(stat, width, height, channel) Parameters:

Parameter Input Type Description

stat basestring The type of statistic to calculate. See STATISTIC_TYPES.

width numbers.Integral The size of neighboring pixels on the X-axis.

height numbers.Integral The size of neighboring pixels on the Y-axis.

channel basestring Optional color channel to target.

Parameter	Input Type	Description
stat	basestring	The type of statistic to calculate. See STATISTIC_TYPES.
width	numbers.Integral	The size of neighboring pixels on the X-axis.
height	numbers.Integral	The size of neighboring pixels on the Y-axis.
channel	basestring	Optional color channel to target.

Input Image:

Example 1:

Python3

# Import Image from wand.image module
from wand.image import Image

# Read image using Image function
with Image(filename ="koala.jpeg") as img:
    img.statistic("median", width = 8, height = 5)
    img.save(filename ="kl-statistic.jpeg")

Output:

Input Image:

Example 2:

Python3

# Import Image from wand.image module
from wand.image import Image

# Read image using Image function
with Image(filename ="road.jpeg") as img:
    img.statistic("median", width = 8, height = 5)
    img.save(filename ="rd-statistic.jpg")