图像的均值方差统计

# -*- coding: utf-8 -*-

import os
import cv2
import numpy as np

def compute_mean(path):
    file_names = os.listdir(path)
    file_names.sort()

    per_image_Rmean = []
    per_image_Gmean = []
    per_image_Bmean = []

    image_R_std = []
    image_G_std = []
    image_B_std = []
	// 我这里是两个子文件夹
    for file in file_names:
        file_path = os.path.join(path, file)
        img_list = os.listdir(file_path)
        img_list.sort()
        for img_path in img_list:
            img_ = os.path.join(file_path, img_path)
            print(img_)

            img = cv2.imread(img_)
            per_image_Bmean.append(np.mean(img[:, :, 0] / 255.0))
            per_image_Gmean.append(np.mean(img[:, :, 1] / 255.0))
            per_image_Rmean.append(np.mean(img[:, :, 2] / 255.0))

            image_B_std.append(np.std(img[:, :, 0] / 255.0))
            image_G_std.append(np.std(img[:, :, 1] / 255.0))
            image_R_std.append(np.std(img[:, :, 2] / 255.0))

    R_mean = np.mean(per_image_Rmean)
    G_mean = np.mean(per_image_Gmean)
    B_mean = np.mean(per_image_Bmean)

    R_std = np.std(image_R_std)
    G_std = np.std(image_G_std)
    B_std = np.std(image_B_std)
    return R_mean, G_mean, B_mean, R_std, G_std, B_std

def main():
    path = '/home/Disc_Z/youku/train/LR'
    R_mean, G_mean, B_mean, R_std, G_std, B_std = compute_mean(path)
    print('R_mean', R_mean)
    print('G_mean', G_mean)
    print('B_mean', B_mean)

    print('R_std', R_std)
    print('G_std', G_std)
    print('B_std', B_std)

if __name__ == '__main__':
    main()