• 本例使用Path(...).glob() from pathlib查找每个目录中的所有图像路径，并将它们解压缩到列表解析中。
• matplotlib.pyplot.imread和matplotlib.axes.Axes.imshow分别用于读取和显示图像。
  *在python 3.12.0、matplotlib 3.8.1中测试

import matplotlib.pyplot as plt
from pathlib import Path

# create a list of directories
dirs = ['../Pictures/dataset1', '../Pictures/dataset2', '../Pictures/dataset3']

# extract the image paths into a list
files = [f for dir_ in dirs for f in list(Path(dir_).glob('*.jpg'))]

# create the figure
fig, axes = plt.subplots(nrows=5, ncols=3, figsize=(10, 10), tight_layout=True)

# flatten the axis into a 1-d array to make it easier to access each axes
axes = axes.flatten()

# iterate through axes and associated file
for ax, file in zip(axes, files):
    
    # read the image in
    pic = plt.imread(file)

    # add the image to the axes
    ax.imshow(pic)

    # add an axes title; .stem is a pathlib method to get the filename
    ax.set(title=file.stem)

    # remove ticks / labels
    ax.axis('off')

# add a figure title
_ = fig.suptitle('Images from https://www.heroforge.com/', fontsize=18)

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的数据

图片间无空白

• 基于此answer

# read in all the images, which are all the same size
images = [plt.imread(file) for file in files]

# get heights for images, the number must match the number for nrows
heights = [im[0].shape[0] for im in images[:5]]  # [images[0][0].shape[0]] * 5

# get widths for images, the number must match the number for ncols
widths = [im.shape[1] for im in images[:3]]  # [images[0].shape[1]] * 3

# set the figure width in inches
fig_width = 9

# calculate the figure width
fig_height = fig_width * sum(heights) / sum(widths)

# create the figure
fig, axes = plt.subplots(nrows=5, ncols=3, figsize=(fig_width, fig_height), 
                         gridspec_kw={'wspace': 0, 'hspace': 0, 'left': 0, 'right': 1,
                                      'bottom': 0, 'top': 1, 'height_ratios': heights})

# flatten the axis into a 1-d array to make it easier to access each axes
axes = axes.flatten()

# iterate through the axes and associated images
for ax, image in zip(axes, images):

    # add the image to the axes
    ax.imshow(image)

    # remove ticks / labels
    ax.axis('off')

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