mean_std.py

# -*- coding: utf-8 -*-
import numpy as np
import cv2
import random
import os

# calculate means and std  注意换行\n符号
# train.txt中每一行是图像的位置信息
path = 'train.txt'
means = [0, 0, 0]
stdevs = [0, 0, 0]

index = 1
num_imgs = 0
with open(path, 'r') as f:
    lines = f.readlines()
    # random.shuffle(lines)
    print(lines)
    for line in lines:
        print(line)
        print('{}/{}'.format(index, len(lines)))
        index += 1
        a = os.path.join(line)
        # print(a[:-1])
        num_imgs += 1
        img = cv2.imread(a[:-1])
        img = np.asarray(img)
        print(img)
        img = img.astype(np.float32) / 255.
        for i in range(3):
            try:
                means[i] += img[:, :, i].mean()
                stdevs[i] += img[:, :, i].std()
            except:
                print('IndexError：此处图像出现错误, 但是不影响均值和方差的计算。')
                break
print(num_imgs)
means.reverse()
stdevs.reverse()

means = np.asarray(means) / num_imgs
stdevs = np.asarray(stdevs) / num_imgs

print("normMean = {}".format(means))
print("normStd = {}".format(stdevs))
print('transforms.Normalize(normMean = {}, normStd = {})'.format(means, stdevs))