计算数据集中图像均值

import os
import numpy as np
import cv2
 
ims_path = r'E:\Datasets/'   # Path to Images
#ims_list = os.listdir(ims_path)

g = os.walk(ims_path)
ims_list = ['%s\\%s' % (i[0], j) for i in g if i[0].endswith('JPEGImages') for j in i[-1] if j.endswith('jpg')]
print(len(ims_list))
R_means = []
G_means = []
B_means = []
for im_list in ims_list:
	im = cv2.imread(im_list)
#extrect value of diffient channel
	im_R = im[:,:,0]
	im_G = im[:,:,1]
	im_B = im[:,:,2]
#count mean for every channel
	im_R_mean = np.mean(im_R)
	im_G_mean = np.mean(im_G)
	im_B_mean = np.mean(im_B)
#save single mean value to a set of means
	R_means.append(im_R_mean)
	G_means.append(im_G_mean)
	B_means.append(im_B_mean)
	print('图片：{} 的 RGB平均值为 \n[{}，{}，{}]'.format(im_list,im_R_mean,im_G_mean,im_B_mean) )
#three sets  into a large set
a = [R_means,G_means,B_means]
mean = [0,0,0]
#count the sum of different channel means
mean[0] = np.mean(a[0])
mean[1] = np.mean(a[1])
mean[2] = np.mean(a[2])
print('数据集的BGR平均值为\n[{}，{}，{}]'.format( mean[0]/255, mean[1]/255, mean[2]/255) )