车牌号的识别

前言

这周开始车牌号的识别。

数据集

The number of images in a training set is: 10944
The number of images in a test set is: 2736
The number of batches per epoch is: 684

from torchvision.transforms import transforms
from torch.utils.data       import DataLoader
from torchvision            import datasets
import torchvision.models   as models
import torch.nn.functional  as F
import torch.nn             as nn
import torch,torchvision

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
import os,PIL,random,pathlib
import matplotlib.pyplot as plt
# 支持中文
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号

data_dir = '015_licence_plate'
data_dir = pathlib.Path(data_dir)

data_paths  = list(data_dir.glob('*'))
classeNames = [str(path).split("\\")[1].split("_")[1].split(".")[0] for path in data_paths]
print(classeNames)

data_paths     = list(data_dir.glob('*'))
data_paths_str = [str(path) for path in data_paths]
# plt.figure(figsize=(14, 5))
# plt.suptitle("数据示例", fontsize=15)

# for i in range(18):
#     plt.subplot(3, 6, i + 1)
#     # plt.xticks([])
#     # plt.yticks([])
#     # plt.grid(False)
#
#     # 显示图片
#     images = plt.imread(data_paths_str[i])
#     plt.imshow(images)
#
# plt.show()

import numpy as np

char_enum = ["京","沪","津","渝",