本文实例为大家分享了python自动计算图像数据集的RGB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
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'''
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 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 ],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。
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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服务器之家。
原文链接:https://blog.csdn.net/gusui7202/article/details/84751598