Find the average / standard deviation of the brightness values in the image

Purpose

It is a memorandum when calculating the histogram of the brightness value in the image and the average / variance.

code

Find the histogram, mean and standard deviation of the image below lena.png: Test image black.png: Uniformly black image

test.py

import numpy as np
import scipy.stats as sstats
import cv2

def print_stat(fname):

    img_name = fname
    img = cv2.imread(fname,1)
    # Grayscale
    img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
    #One-dimensional array
    img = np.array(img).flatten()
    # img = img[img!=255]

    mean = img.mean()             #Average value
    std = np.std(img)             #standard deviation
    median = np.median(img)       #Median
    mode = sstats.mode(img)[0][0] #Mode

    print("---", img_name)
    print("mean    : ", mean)
    print("stddev  : ", std)
    print("median  : ", median)
    print("mode    : ", mode)

print_stat('lena.png')
print_stat('black.png')

result

$ python test.py
--- lena.png
mean    :  106.4122314453125
stddev  :  45.733566693923045
median  :  107.0
mode    :  44
--- black.png
mean    :  0.0
stddev  :  0.0
median  :  0.0
mode    :  0

Other

If you want to make it a little easier to use from the command line,

test.py

import sys
import numpy as np
import scipy.stats as sstats
import cv2

args = sys.argv

def print_stat(fname):

    img_name = fname
    img = cv2.imread(fname,1)
    # Grayscale
    img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
    #One-dimensional array
    img = np.array(img).flatten()
    # img = img[img!=255]

    mean = img.mean()
    std = np.std(img)
    median = np.median(img)
    mode = sstats.mode(img)[0][0]

    print("name=" + img_name + ",")
    print("mean=" + str(mean) + ",")
    print("stddev=" + str(std) + ",")
    print("median=" + str(median) + ",")
    print("mode=" + str(mode) + ",")

arg1=args[1]
print_stat(arg1)

$ RET=$(python test.py lena.png)
$ echo $RET
name=lena.png , mean=106.4122314453125 , stddev=45.733566693923045 , median=107.0 , mode=44 ,
$ echo $RET | sed -e 's/.*name=//' |  cut -d',' -f 1 | awk '{printf "%-20s\n",$1}'
lena.png
$ echo $RET | sed -e 's/.*mean=//' |  cut -d',' -f 1 | awk '{printf "%-20s\n",$1}'
106.4122314453125

reference

Learn image processing with Python3 & OpenCV [2] ~ Histogram basic experiment for information visualization