基于模块差的3*3子图的对比

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提醒：本文最后更新于 2024-08-30 16:07，文中所关联的信息可能已发生改变，请知悉！

原图：https://gitee.com/icvuln/server_backup_denoise18/blob/master/rsc/03.png

详见：https://gitee.com/icvuln/server_backup_denoise18/blob/master/one2k.py

import cv2 as cv
import numpy as np

def separate(img, k):
    row, col = img.shape
    kimg = np.zeros((k, k, row//k, col//k), dtype=int)
    for i in range(0, row, k):
        for j in range(0, col, k):
            for m in range(k):
                for n in range(k):
                    if i//k < row//k and j//k < col//k:
                        kimg[m][n][i//k][j//k] = img[i + m][j + n]

    for i in range(k):
        for j in range(k):
            cv.imwrite('out/one2k/k3/%d%d.png' % (i, j), kimg[i][j])

def main():
    img_dir = 'rsc/03.png'
    k = 3
    img = cv.imread(img_dir, 0)
    separate(img, k)

if __name__ == '__main__':
    main()

结果：https://gitee.com/icvuln/server_backup_denoise18/tree/master/out/one2k/k3

import max_sub_min as msm
import os
import cv2 as cv
import denoise18 as dn
import matplotlib.pyplot as plt

def get_img_addrs(root_addr):
    img_addrs = os.listdir(root_addr)
    return img_addrs

if __name__ == '__main__':
    img_dir = 'out/one2k/k3'
    img_addrs = get_img_addrs(img_dir)
    for img_addr in img_addrs:
        img_addr_path = os.path.join(img_dir, img_addr)
        if os.path.isdir(img_addr_path):
            break
        print(img_addr_path)
        img = cv.imread(img_addr_path, 0)
        differ = dn.get_dif(img)

        max_min_differ = msm.get_max_min(differ)

        cnt = msm.get_cnt(max_min_differ, 150)

        plt.plot(cnt, color='blue')
        plt.rcParams['axes.unicode_minus'] = False
        plt.title('max-min', fontsize=24, color='black')
        plt.savefig(os.path.join('out/one2k/k3/max_sub_min', img_addr))
        plt.show()

import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt

import denoise18 as dn

def get_max_min(differ):
    row, col, _ = differ.shape
    max_min = np.zeros((row, col), dtype=int)
    for i in range(row):
        for j in range(col):
            max_min[i][j] = max(differ[i][j]) - min(differ[i][j])
    return max_min

def get_cnt(array, len):
    cnt = np.zeros(len, dtype=int)
    row, col = array.shape
    for i in range(row):
        for j in range(col):
            if array[i][j] < len:
                cnt[array[i][j]] += 1
    return cnt

def main():
    img_addr = 'out/03.png'
    img = cv.imread(img_addr, 0)
    differ = dn.get_dif(img)

    max_min_differ = get_max_min(differ)

    cnt = get_cnt(max_min_differ, 150)

    plt.plot(cnt, color='blue')
    # plt.rcParams['font.sans-serif'] = ['SimHei']
    plt.rcParams['axes.unicode_minus'] = False
    plt.title('max-min', fontsize=24, color='black')
    plt.savefig('out/max-min.png')
    plt.show()

if __name__ == '__main__':
    main()

# python3.6
# utf-8
# LF

import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from mpl_toolkits.mplot3d import Axes3D

import show_3d

def get_1D_2_2D(x):
    d = {0:[-1, -1], 1:[-1, 0], 2:[-1, 1], 3:[0, 1], 4:[1, 1], 5:[1, 0], 6:[1, -1], 7:[0, -1]}
    return d[x]

def get_dif(img):
    raw, col = img.shape
    dif = np.zeros((raw - 1, col - 1, 8), dtype=int)

    for i in range(raw - 1):
        for j in range(col - 1):
            for m in range(8):
                d = get_1D_2_2D(m)
                if(i + d[0] >= 0 and i + d[0] + 1 <= raw - 1 and j + d[1] >= 0 and j + d[1] + 1 <= col -1):
                    dif[i][j][m] = abs(int(img[i][j]) - int(img[i + d[0]][j + d[1]])) + \
                                    abs(int(img[i][j + 1]) - int(img[i + d[0]][j + d[1] + 1])) + \
                                    abs(int(img[i + 1][j + 1]) - int(img[i + d[0] + 1][j + d[1] + 1])) + \
                                    abs(int(img[i + 1][j]) - int(img[i + d[0] + 1][j + d[1]]))
    return dif

def drew_graph(array, flag):
    cnt = np.zeros(100)
    raw, col, _ = array.shape
    for i in range(raw):
        for j in range(col):
            d = sorted(array[i][j])
            # print(d)
            if int(d[flag]) < 100:
                cnt[int(d[flag])] += 1

    plt.plot(cnt, color='red')
    # plt.rcParams['font.sans-serif'] = ['SimHei']
    plt.rcParams['axes.unicode_minus'] = False
    plt.title('max', fontsize=24, color='black')
    plt.savefig('fenbu.png')
    plt.show()

def get_show(ary):
    raw, col, _ = ary.shape
    imin = np.zeros((raw, col))
    for i in range(raw):
        for j in range(col):
            d = sorted(ary[i][j])
            if d[0] <= 20:
                imin[i][j] = 255
    cv.imwrite('min.png', imin)

    imax = np.zeros((raw, col))
    for i in range(raw):
        for j in range(col):
            d = sorted(ary[i][j])
            if d[7] > 60:
                imax[i][j] = 255
    cv.imwrite('max.png', imax)

def get_3d(ary):
    raw, col, _ = ary.shape
    minmax = 0
    for i in range(raw):
        for j in range(col):
            d = sorted(ary[i][j])
            if d[0] > minmax:
                minmax = d[0]

    maxmax = 0
    for i in range(raw):
        for j in range(col):
            d = sorted(ary[i][j])
            if d[7] > maxmax:
                maxmax = d[7]

    data = np.zeros((int(minmax) + 1, int(maxmax) + 1))
    for i in range(raw):
        for j in range(col):
            d = sorted(ary[i][j])
            data[int(d[0])][int(d[7])] += 1

    np.savetxt('data.csv', data, delimiter=',')
    '''
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')
    for i in range(int(minmax) + 1):
        for j in range(int(maxmax) + 1):
            ax.scatter(i, j, data[i][j], marker='o')
    plt.savefig('3d.png')
    plt.show()
    '''

def main(imgdir):
    img = cv.imread(imgdir, 0)
    differ = get_dif(img)
    # drew_graph(differ, 7)
    # get_show(differ)
    get_3d(differ)

if __name__ == '__main__':
    img_dir = '03.png'
    main(img_dir)

部分结果如下：

所有结果：https://gitee.com/icvuln/server_backup_denoise18/tree/master/out/one2k/k3/max_sub_min

正文完