本文小编为大家详细介绍“Python怎么计算图片数据集的均值方差”，内容详细，步骤清晰，细节处理妥当，希望这篇“Python怎么计算图片数据集的均值方差”文章能帮助大家解决疑惑，下面跟着小编的思路慢慢深入，一起来学习新知识吧。
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# -*- coding: utf-8 -*-
"""
Created on Thu Aug 23 16:06:35 2018
@author: libo
"""
from PIL import Image
import os
def 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 os
from PIL import Image
import matplotlib.pyplot as plt
import numpy as np
from scipy.misc import imread
filepath = r'Z:\pycharm_projects\ssd\VOC2007\reshape' # 数据集目录
pathDir = os.listdir(filepath)
R_channel = 0
G_channel = 0
B_channel = 0
for 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 / num
G_mean = G_channel / num
B_mean = B_channel / num
R_channel = 0
G_channel = 0
B_channel = 0
for 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
import os
from PIL import Image
import matplotlib.pyplot as plt
import numpy as np
from scipy.misc import imread
filepath = ‘/home/JPEGImages‘ # 数据集目录
pathDir = os.listdir(filepath)
R_channel = 0
G_channel = 0
B_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])
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 / num
G_mean = G_channel / num
B_mean = B_channel / numR_channel = 0
G_channel = 0
B_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] - 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 / num
G_var = G_channel / num
B_var = 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))读到这里，这篇“Python怎么计算图片数据集的均值方差”文章已经介绍完毕，想要掌握这篇文章的知识点还需要大家自己动手实践使用过才能领会，如果想了解更多相关内容的文章，欢迎关注亿速云行业资讯频道。
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