dataset = r'5low:.*|5mix:.*|5normal:.*' para = r'MAE: (.{6})'#意思是MAE： 后面的六个东西 row_data = re.findall(dataset,txt)#正则化找到要读的内容，先找到基本的行（dataset），在找到行里的内容（para） new_row_data = '\n'.join(row_data)#list转化为字符串 final_data = re.findall(para,new_row_data) # print(dataset) # print('\n') # print(new_row_data) # print('\n') # print(final_data) print(len(final_data))#检查一下个数看对不对

然后画图，其实两个代码可以放在一个里面

import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from readdata import final_data
#要画的标签以及每个标签对应的值
labels = [ 'CONet', 'DANet','DCF', 'SP-Net', 'VST', 'CDINet','DFM-Net','TriTransNet','cmSalGAN','D3Net','BiANet','DLMNet','CCAFNet','C2DFNet','MobileSal','JL-DCF','SwinNet','A2S-v2','HRTransNet']
Overall = []
low = []
normal = [] 
#print(final_data)
#把之前读进来的数据分给上面的对应的值
for i in range(len(final_data)):
    final_data[i]=float(final_data[i])
    if i % 3 == 0:
        low.append(final_data[i])
    if i % 3 == 1:
        Overall.append(final_data[i])
    if i % 3 == 2:
        normal.append(final_data[i])
# print(Large)
# print('\n')
# print(Middle)
# print('\n')
# print(Overall)
# print('\n')
# print(Small)
# print('\n')
x = np.arange(len(labels))  # 标签位置
width = 0.2  # 柱状图的宽度，可以根据自己的需求和审美来改
fig, ax = plt.subplots()
rects1 = ax.bar(x - width, low, width, label='Low-light scenes',color=(33/255,158/255,188/255))
rects2 = ax.bar(x + 0.00, normal, width, label='Sunny scenes',color=(19/255,103/255,131/255))
rects3 = ax.bar(x + width, Overall, width, label='Overall',color=(2/255,48/255,74/255))
#为y轴、标题和x轴等添加一些文本。
# ax.set_ylabel(r'$F^{\omega}_{\beta}$', fontsize=12)
# ax.set_xlabel('Models', fontsize=12)
# ax.set_title('Result of 'r'$F^{\omega}_{\beta}$')
# ax.set_xticks(x)
# ax.set_xticklabels(labels,rotation=45)
# ax.set_ylim(0.4,1.1)
# ax.legend(loc='upper right')
ax.set_ylabel('MAE', fontsize=12)
ax.set_xlabel('Models', fontsize=12)
ax.set_title('Result of MAE')
ax.set_xticks(x)
ax.set_xticklabels(labels,rotation=45)
#可以自己控制
#轴的显示范围
#ax.set_ylim(0,0.24)
ax.legend(loc='upper right')
# def autolabel(rects):
#     """在*rects*中的每个柱状条上方附加一个文本标签，显示其高度"""
#     for rect in rects:
#         height = rect.get_height()
#         ax.annotate('{}'.format(height),
#                     xy=(rect.get_x() + rect.get_width() / 2, height),
#                     xytext=(0, 3),  # 3点垂直偏移
#                     textcoords="offset points",
#                     ha='center', va='bottom')
# autolabel(rects1)
# autolabel(rects2)
# autolabel(rects3)
# autolabel(rects4)
#fig.tight_layout()
#plt.xticks(labels, labels, rotation=30)
plt.show()

最后贴个图：

【已解决TypeError: can‘t convert cuda:0 device type tensor to numpy. Use Tensor.cpu() to copy the tensor 46300