Python怎么计算图片数据集的均值方差

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Python批量reshape图片

# -*- coding: utf-8 -*-"""Created on Thu Aug 23 16:06:35 2018@author: libo"""from PIL import Imageimport osdef image_resize(image_path, new_path):           # 统一图片尺寸    print('============>>修改图片尺寸')    for img_name in os.listdir(image_path):        img_path = image_path + "/" + img_name    # 获取该图片全称        image = Image.open(img_path)              # 打开特定一张图片        image = image.resize((512, 512))          # 设置需要转换的图片大小        # process the 1 channel image        image.save(new_path + '/'+ img_name)    print("end the processing!")if __name__ == '__main__':    print("ready for ::::::::  ")    ori_path = r"Z:\pycharm_projects\ssd\VOC2007\JPEGImages"                # 输入图片的文件夹路径    new_path = 'Z:/pycharm_projects/ssd/VOC2007/reshape'                   # resize之后的文件夹路径    image_resize(ori_path, new_path)

import osfrom PIL import Imageimport matplotlib.pyplot as pltimport numpy as npfrom scipy.misc import imreadfilepath = r'Z:\pycharm_projects\ssd\VOC2007\reshape'  # 数据集目录pathDir = os.listdir(filepath)R_channel = 0G_channel = 0B_channel = 0for idx in range(len(pathDir)):    filename = pathDir[idx]    img = imread(os.path.join(filepath, filename)) / 255.0    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) * 512 * 512  # 这里（512,512）是每幅图片的大小，所有图片尺寸都一样R_mean = R_channel / numG_mean = G_channel / numB_mean = B_channel / numR_channel = 0G_channel = 0B_channel = 0for idx in range(len(pathDir)):    filename = pathDir[idx]    img = imread(os.path.join(filepath, filename)) / 255.0    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))

可能有点慢，慢慢等着就行。。。。。。。

最后得到的结果是介个

参考

计算数据集均值和方差

import osfrom PIL import Image  import matplotlib.pyplot as pltimport numpy as npfrom scipy.misc import imread filepath = '/home/JPEGImages' # 数据集目录pathDir = os.listdir(filepath)R_channel = 0G_channel = 0B_channel = 0for idx in xrange(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) * 384 * 512 # 这里（384,512）是每幅图片的大小，所有图片尺寸都一样R_mean = R_channel / numG_mean = G_channel / numB_mean = B_channel / num

R_channel = 0G_channel = 0B_channel = 0

for idx in xrange(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 = R_channel / numG_var = G_channel / numB_var = B_channel / numprint("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))

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