图像处理: jpg格式 存储-读写 时 像素值 微小变化 探究

    for i in range(h):
        for j in range(w):
            if thresh_pic[i, j, 0] == 0 and label_pic[i, j, 0] == 0:
                diff_pic[i, j, :] = 0
            elif thresh_pic[i, j, 0] == 255 and label_pic[i, j, 0] == 255:
                diff_pic[i, j, :] = 255
            elif thresh_pic[i, j, 0] == 0 and label_pic[i, j, 0] == 255:
                diff_pic[i, j, 2] = 255
            elif thresh_pic[i, j, 0] == 255 and label_pic[i, j, 0] == 0:
                diff_pic[i, j, 1] = 255
            else:
                logging.error('({},{}): thresh={}, label={}'.format(i, j, thresh_pic[i, j, 0], label_pic[i, j, 0]))

...
ERROR:root:(279,535): thresh=254, label=0
ERROR:root:(279,576): thresh=253, label=0
ERROR:root:(279,581): thresh=253, label=0
...

    for i in range(h):
        for j in range(w):
            if thresh_pic[i, j, 0] < 10 and label_pic[i, j, 0] < 10:
                diff_pic[i, j, :] = 0
            elif thresh_pic[i, j, 0] > 245 and label_pic[i, j, 0] > 245:
                diff_pic[i, j, :] = 255
            elif thresh_pic[i, j, 0] < 10 and label_pic[i, j, 0] > 245:
                diff_pic[i, j, 2] = 255
            elif thresh_pic[i, j, 0] > 245 and label_pic[i, j, 0] < 10:
                diff_pic[i, j, 1] = 255
            else:
                logging.error('({},{}): thresh={}, label={}'.format(i, j, thresh_pic[i, j, 0], label_pic[i, j, 0]))

# coding=utf-8

first_path = './data/first.jpg'
second_path = './data/second.jpg'
third_path = './data/third.jpg'
forth_path = './data/forth.jpg'
fifth_path = './data/fifth.jpg'

one_hundred_path = './data/one_hundred.jpg'

import cv2
import numpy as np
import logging

# 生成并保存 俩图像 的 差异图
def compare(pic1, pic2, dst_path):
    h, w, c = pic1.shape
    diff_pic = np.zeros_like(pic1, dtype=np.uint8)
    for i in range(h):
        for j in range(w):
            if pic1[i, j, 0] == pic2[i, j, 0]:  # 像素值 不变，该点 置 黑色
                diff_pic[i, j, :] = 0
            elif pic1[i, j, 0] < pic2[i, j, 0]:  # 像素值 增加，该点 置 绿色
                diff_pic[i, j, 1] = 255
            elif pic1[i, j, 0] > pic2[i, j, 0]:  # 像素值 减少，该点 置 红色
                diff_pic[i, j, 2] = 255
            else:
                logging.error('({},{}): pic1={}, pic2={}'.format(i, j, pic1[i, j, 0], pic2[i, j, 0]))

    cv2.imwrite(dst_path, diff_pic)
    return diff_pic

# 指定轮数 进行 循环 存储和读取
def save_and_read_cycle(pic, path, num):
    for _ in xrange(num):
        cv2.imwrite(path, pic)
        pic = cv2.imread(path)
    return pic

# 原图像
origin_pic = cv2.imread('./data/girl.jpg')

# 需要 循环 １次 的图像
first_pic = origin_pic.copy()
first_pic = save_and_read_cycle(first_pic, first_path, 1)

# 需要 循环 ２次 的图像
second_pic = origin_pic.copy()
second_pic = save_and_read_cycle(second_pic, second_path, 2)

# 需要 循环 ３次 的图像
third_pic = origin_pic.copy()
third_pic = save_and_read_cycle(third_pic, third_path, 3)

# 需要 循环 ４次 的图像
forth_pic = origin_pic.copy()
forth_pic = save_and_read_cycle(forth_pic, forth_path, 4)

# 需要 循环 ５次 的图像
fifth_pic = origin_pic.copy()
fifth_pic = save_and_read_cycle(fifth_pic, fifth_path, 5)

# 需要 循环 １００次 的图像
one_hundred_pic = origin_pic.copy()
one_hundred_pic = save_and_read_cycle(one_hundred_pic, one_hundred_path, 100)

# 求 循环 存储和读取 后 该图片 与 原图像 差异
ori_fir = compare(origin_pic, first_pic, 'data/ori_fir.jpg')
fir_sec = compare(first_pic, second_pic, 'data/fir_sec.jpg')
sec_thi = compare(second_pic, third_pic, 'data/sec_thi.jpg')
thi_for = compare(third_pic, forth_pic, 'data/thi_for.jpg')
for_fif = compare(forth_pic, fifth_pic, 'data/for_fif.jpg')
ori_hundred = compare(origin_pic, one_hundred_pic, 'data/ori_hundred.jpg')