本文实例为大家分享了python自动计算图像数据集的RHdhCmsTestcppcns测试数据GB均值,供大家参考,具体内容如下
图像数据集往往要进行去均值,以保证更快的收敛。
代码:
创建一个mean.py,写入如下代码。修改路径即可使用
''' qhy 2018.12.3 ''' import os import numpy as np import cv2 ims_path='C:/Users/my/Desktop/JPEGImages/'# 图像数据集的路径 ims_list=os.listdir(ims_path) R_means=[] G_means=[] B_means=[] for im_list in ims_list: im=cv2.imread(ims_path+im_list) #extrect value of diffient channel im_R=im[:,:,0] im_G=im[:,:,1] im_B=im[:,:,2] #count me 编程客栈 an for every channel im_R_mean=np.mean(im_R) im_G_me 编程客栈 an=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[{},{},{}]'.fHdhCmsTestcppcns测试数据ormat(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 cha 编程客栈 nnel 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],mean[1],mean[2]) ) #cv.imread()读取Img时候将rgb转换为了bgr,谢谢taylover-pei的修正。
终端运行: python mean.py
结果示例如下:
以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持我们。
查看更多关于python自动计算图像数据集的RGB均值的详细内容...
声明:本文来自网络,不代表【好得很程序员自学网】立场,转载请注明出处:http://www.haodehen.cn/did125151