拼接不同文件夹中同名图片的方法

有时候为了方便对比不同文件夹中同名图片，需要拼接在一起，这里提供一个拼接方法，当然不同命文件也可以实现拼接，稍微改改就能实现

如下图，在文件夹中有五个文件夹中的图片需要拼接，拼接后的图片存放在img_hebing

代码如下，为了隐去了一些项目私密信息

import warnings
warnings.filterwarnings('ignore')
import matplotlib.pyplot as plt
from matplotlib import cm as CM
import matplotlib.gridspec as gridspec
import os
import glob
import numpy as np
import scipy.io as scio
from scipy.io import loadmat
from PIL import Image; import cv2
import torch
from torchvision import transforms

DATA_PATH = f"D:/TEST/image_test/"

img_path1 = glob.glob(os.path.join(DATA_PATH, "four_visualization_1", "*.png"))  
img_path2 = glob.glob(os.path.join(DATA_PATH, "four_visualization_2", "*.png"))  
img_path3 = glob.glob(os.path.join(DATA_PATH, "four_visualization_3", "*.png"))  
img_path4 = glob.glob(os.path.join(DATA_PATH, "four_visualization_4", "*.png"))  
img_path5 = glob.glob(os.path.join(DATA_PATH, "four_visualization_5", "*.png")) 
save_path = f'D:/TEST/image_test/img_hebing'
img_path1.sort()
img_path2.sort()
img_path3.sort()
img_path3.sort()
img_path5.sort()
for idx in range(0, len(img_path3)):
    img_path = img_path3[idx]
    filename = img_path.split('/')[-1].split('\\')[-1].split('.')[0].split('_')[2:-1]
    filename = '_'.join(filename)  # 文件名
    # 读取图像
    img1 = cv2.imread(img_path1[idx])
    img2 = cv2.imread(img_path2[idx])    
    img3 = cv2.imread(img_path3[idx])
    img4 = cv2.imread(img_path4[idx])
    img5 = cv2.imread(img_path5[idx])
    # 获取图像高度和宽度
    height0, width0 = img1.shape[:2]
    height1, width1 = img2.shape[:2]
    height2, width2 = img3.shape[:2]
    height3, width3 = img4.shape[:2]    
    height4, width4 = img5.shape[:2]
    # 获取最宽宽度
    max_width = max(width0, width1, width2, width3, width4)
    # 计算放大倍率
    scaling_factor0 = max_width / width0
    scaling_factor1 = max_width / width1
    scaling_factor2 = max_width / width2
    scaling_factor3 = max_width / width3
    scaling_factor4 = max_width / width4

    # 调整图像大小并进行比例放大
    image0_resized = cv2.resize(img1, (max_width, int(height0 * scaling_factor0)))
    image1_resized = cv2.resize(img2, (max_width, int(height1 * scaling_factor1)))
    image2_resized = cv2.resize(img3, (max_width, int(height2 * scaling_factor2)))
    image3_resized = cv2.resize(img4, (max_width, int(height3 * scaling_factor3)))    
    image4_resized = cv2.resize(img5, (max_width, int(height4 * scaling_factor4)))
    # 拼接
    combined_iamge = np.vstack((image4_resized, image2_resized, image3_resized, image0_resized, image1_resized))
    # 安装路径保存
    cv2.imwrite(os.path.join(save_path, "{}.png".format(filename)), combined_iamge)