Pythonはピクチャデータセットの平均分散を計算する

データセット全体の平均分散値を得る

import os
from PIL import Image
import matplotlib.pyplot as plt
import numpy as np
# from scipy.misc import imread 
## scipy_1.3.1 not allowed
from imageio import imread

filepath = '/home/deeplearning/NEW/tianchi_data/VOC2007-4/JPEGImages'  #      

pathDir = os.listdir(filepath)
 
R_channel = 0
G_channel = 0
B_channel = 0
for idx in range(len(pathDir)):
    filename = pathDir[idx]
    img = imread(os.path.join(filepath, filename))
    R_channel = R_channel + np.sum(img[:, :, 0])
    G_channel = G_channel + np.sum(img[:, :, 1])
    B_channel = B_channel + np.sum(img[:, :, 2])
 
num = len(pathDir) * 1024 * 1024  #   （1024,1024）        ，         
R_mean = R_channel / num  # or /255.0
G_mean = G_channel / num
B_mean = B_channel / num
 
R_channel = 0
G_channel = 0
B_channel = 0
for idx in range(len(pathDir)):
    filename = pathDir[idx]
    img = imread(os.path.join(filepath, filename))
    R_channel = R_channel + np.sum((img[:, :, 0] - R_mean) ** 2)
    G_channel = G_channel + np.sum((img[:, :, 1] - G_mean) ** 2)
    B_channel = B_channel + np.sum((img[:, :, 2] - B_mean) ** 2)
 
R_var = np.sqrt(R_channel / num)
G_var = np.sqrt(G_channel / num)
B_var = np.sqrt(B_channel / num)
print("R_mean is %f, G_mean is %f, B_mean is %f" % (R_mean, G_mean, B_mean))
print("R_var is %f, G_var is %f, B_var is %f" % (R_var, G_var, B_var))

# R_mean is 143.532975, G_mean is 145.831770, B_mean is 151.186388
# R_var is 48.226279, G_var is 45.276815, B_var is 40.371132

参照先:https://blog.csdn.net/weixin_41765699/article/details/100118660