app_cn.py

import os
import re
import math
import sys
import shutil
import json
import traceback
import PIL.Image as PilImage
import threading
import tkinter as tk
from tkinter import messagebox
from tkinter import ttk
from tkinter import filedialog
from constants import *
from config import ModelConfig, OUTPUT_SHAPE1_MAP, NETWORK_MAP, DataAugmentationEntity, PretreatmentEntity, get_version
from make_dataset import DataSets
from predict_testing import Predict
from trains import Trains
from category import category_extract, SIMPLE_CATEGORY_MODEL
from utils.category_frequency_statistics import fetch_category_list
from gui.utils import LayoutGUI
from gui.data_augmentation import DataAugmentationDialog
from gui.pretreatment import PretreatmentDialog

NOT_EDITABLE_MSG = "只支持从文件中修改"


class Wizard:
    job: threading.Thread
    current_task: Trains = None
    is_task_running: bool = False
    data_augmentation_entity = DataAugmentationEntity()
    pretreatment_entity = PretreatmentEntity()
    extract_regex = ".*?(?=_)"
    label_split = ""
    model_conf: ModelConfig = None

    def __init__(self, parent: tk.Tk):
        self.layout = {
            'global': {
                'start': {'x': 15, 'y': 20},
                'space': {'x': 15, 'y': 25},
                'tiny_space': {'x': 5, 'y': 10}
            }
        }
        self.parent = parent
        self.parent.iconbitmap(Wizard.resource_path("resource/icon.ico"))
        self.current_project: str = ""
        self.project_root_path = "./projects"
        if not os.path.exists(self.project_root_path):
            os.makedirs(self.project_root_path)
        self.parent.title('Eve-深度训练框架 v1({})'.format(get_version()))
        self.parent.resizable(width=False, height=False)
        self.window_width = 815
        self.window_height = 700
        self.layout_utils = LayoutGUI(self.layout, self.window_width)
        screenwidth = self.parent.winfo_screenwidth()
        screenheight = self.parent.winfo_screenheight()
        size = '%dx%d+%d+%d' % (
            self.window_width,
            self.window_height,
            (screenwidth - self.window_width) / 2,
            (screenheight - self.window_height) / 2
        )

        self.parent.bind('<Button-1>', lambda x: self.blank_click(x))

        s = ttk.Style()
        s.configure('my.TButton', font=('simsun', 10))
        # ============================= Menu 1 =====================================
        self.menubar = tk.Menu(self.parent, font=("simsun", 10))
        self.data_menu = tk.Menu(self.menubar, tearoff=False, font=("simsun", 10))
        self.help_menu = tk.Menu(self.menubar, tearoff=False, font=("simsun", 10))
        self.system_menu = tk.Menu(self.menubar, tearoff=False, font=("simsun", 10))
        self.edit_var = tk.DoubleVar()
        self.label_from_var = tk.StringVar()

        self.memory_usage_menu = tk.Menu(self.menubar, tearoff=False)
        self.memory_usage_menu.add_radiobutton(label="50%", variable=self.edit_var, value=0.5)
        self.memory_usage_menu.add_radiobutton(label="60%", variable=self.edit_var, value=0.6)
        self.memory_usage_menu.add_radiobutton(label="70%", variable=self.edit_var, value=0.7)
        self.memory_usage_menu.add_radiobutton(label="80%", variable=self.edit_var, value=0.8)

        self.label_from_menu = tk.Menu(self.menubar, tearoff=False, font=("simsun", 10))
        self.label_from_menu.add_radiobutton(label="文件名", variable=self.label_from_var, value='FileName')
        self.label_from_menu.add_radiobutton(label="文本", variable=self.label_from_var, value='TXT')

        self.menubar.add_cascade(label="系统", menu=self.system_menu)
        self.system_menu.add_cascade(label="显存占用率", menu=self.memory_usage_menu)

        self.data_menu.add_command(label="数据增强", command=lambda: self.popup_data_augmentation())
        self.data_menu.add_command(label="预处理", command=lambda: self.popup_pretreatment())
        self.data_menu.add_separator()
        self.data_menu.add_command(label="重置打包数据集", command=lambda: self.clear_dataset())
        self.data_menu.add_separator()
        self.data_menu.add_cascade(label="标注源", menu=self.label_from_menu)
        self.data_menu.add_command(label="一键获取分类", command=lambda: self.fetch_category())
        self.menubar.add_cascade(label="数据", menu=self.data_menu)

        self.help_menu.add_command(label="关于", command=lambda: self.popup_about())
        self.menubar.add_cascade(label="帮助", menu=self.help_menu)

        self.parent.config(menu=self.menubar)

        # ============================= Group 1 =====================================
        self.label_frame_source = ttk.Labelframe(self.parent, text='样本源')
        self.label_frame_source.place(
            x=self.layout['global']['start']['x'],
            y=self.layout['global']['start']['y'],
            width=790,
            height=150
        )

        # 训练集源路径 - 标签
        self.dataset_train_path_text = ttk.Label(self.parent, font=("simsun", 10), text='训练集路径', anchor=tk.W)
        self.layout_utils.inside_widget(
            src=self.dataset_train_path_text,
            target=self.label_frame_source,
            width=90,
            height=20
        )

        # 训练集源路径 - 输入控件
        self.source_train_path_listbox = tk.Listbox(self.parent, font=('微软雅黑', 9))
        self.layout_utils.next_to_widget(
            src=self.source_train_path_listbox,
            target=self.dataset_train_path_text,
            width=600,
            height=50,
            tiny_space=True
        )
        self.source_train_path_listbox.bind(
            sequence="<Delete>",
            func=lambda x: self.listbox_delete_item_callback(x, self.source_train_path_listbox)
        )
        self.listbox_scrollbar(self.source_train_path_listbox)

        # 训练集源路径 - 按钮
        self.btn_browse_train = ttk.Button(
            self.parent, style='my.TButton', text='浏览',
            command=lambda: self.browse_dataset(DatasetType.Directory, RunMode.Trains)
        )
        self.layout_utils.next_to_widget(
            src=self.btn_browse_train,
            target=self.source_train_path_listbox,
            width=60,
            height=24,
            tiny_space=True
        )

        # 验证集源路径 - 标签
        label_edge = self.layout_utils.object_edge_info(self.dataset_train_path_text)
        widget_edge = self.layout_utils.object_edge_info(self.source_train_path_listbox)
        self.dataset_validation_path_text = ttk.Label(self.parent, font=("simsun", 10), text='验证集路径', anchor=tk.W)
        self.dataset_validation_path_text.place(
            x=label_edge['x'],
            y=widget_edge['edge_y'] + self.layout['global']['space']['y'] / 2,
            width=90,
            height=20
        )

        # 验证集源路径 - 输入控件
        self.source_validation_path_listbox = tk.Listbox(self.parent, font=('微软雅黑', 9))
        self.layout_utils.next_to_widget(
            src=self.source_validation_path_listbox,
            target=self.dataset_validation_path_text,
            width=600,
            height=50,
            tiny_space=True
        )
        self.source_validation_path_listbox.bind(
            sequence="<Delete>",
            func=lambda x: self.listbox_delete_item_callback(x, self.source_validation_path_listbox)
        )
        self.listbox_scrollbar(self.source_validation_path_listbox)

        # 训练集源路径 - 按钮
        self.btn_browse_validation = ttk.Button(
            self.parent, style='my.TButton', text='浏览',
            command=lambda: self.browse_dataset(DatasetType.Directory, RunMode.Validation)
        )
        self.layout_utils.next_to_widget(
            src=self.btn_browse_validation,
            target=self.source_validation_path_listbox,
            width=60,
            height=24,
            tiny_space=True
        )

        # ============================= Group 2 =====================================
        self.label_frame_neu = ttk.Labelframe(self.parent, text='神经网络')
        self.layout_utils.below_widget(
            src=self.label_frame_neu,
            target=self.label_frame_source,
            width=790,
            height=120,
            tiny_space=False
        )

        # 最大标签数目 - 标签
        self.label_num_text = ttk.Label(self.parent, font=("simsun", 10), text='标签数', anchor=tk.W)
        self.layout_utils.inside_widget(
            src=self.label_num_text,
            target=self.label_frame_neu,
            width=65,
            height=20,
        )

        # 最大标签数目 - 滚动框
        self.label_num_spin = ttk.Spinbox(self.parent, from_=1, to=12)
        self.label_num_spin.set(1)
        self.layout_utils.next_to_widget(
            src=self.label_num_spin,
            target=self.label_num_text,
            width=50,
            height=20,
            tiny_space=True
        )

        # 图像通道 - 标签
        self.channel_text = ttk.Label(self.parent, font=("simsun", 10), text='通道', anchor=tk.W)
        self.layout_utils.next_to_widget(
            src=self.channel_text,
            target=self.label_num_spin,
            width=50,
            height=20,
            tiny_space=False
        )

        # 图像通道 - 下拉框
        self.comb_channel = ttk.Combobox(self.parent, values=(3, 1), state='readonly')
        self.comb_channel.current(1)
        self.layout_utils.next_to_widget(
            src=self.comb_channel,
            target=self.channel_text,
            width=38,
            height=20,
            tiny_space=True
        )

        # 卷积层 - 标签
        self.neu_cnn_text = ttk.Label(self.parent, font=("simsun", 10), text='卷积层', anchor=tk.W)
        self.layout_utils.next_to_widget(
            src=self.neu_cnn_text,
            target=self.comb_channel,
            width=65,
            height=20,
            tiny_space=False
        )

        # 卷积层 - 下拉框
        self.comb_neu_cnn = ttk.Combobox(self.parent, values=[_.name for _ in CNNNetwork], state='readonly')
        self.comb_neu_cnn.current(0)
        self.layout_utils.next_to_widget(
            src=self.comb_neu_cnn,
            target=self.neu_cnn_text,
            width=80,
            height=20,
            tiny_space=True
        )

        # 循环层 - 标签
        self.neu_recurrent_text = ttk.Label(self.parent, font=("simsun", 10), text='循环层', anchor=tk.W)
        self.layout_utils.next_to_widget(
            src=self.neu_recurrent_text,
            target=self.comb_neu_cnn,
            width=95,
            height=20,
            tiny_space=False
        )

        # 循环层 - 下拉框
        self.comb_recurrent = ttk.Combobox(self.parent, values=[_.name for _ in RecurrentNetwork], state='readonly')
        self.comb_recurrent.current(1)
        self.layout_utils.next_to_widget(
            src=self.comb_recurrent,
            target=self.neu_recurrent_text,
            width=112,
            height=20,
            tiny_space=True
        )
        self.comb_recurrent.bind("<<ComboboxSelected>>", lambda x: self.auto_loss(x))

        # 循环层单元数 - 标签
        self.units_num_text = ttk.Label(self.parent, font=("simsun", 10), text='单元数', anchor=tk.W)
        self.layout_utils.next_to_widget(
            src=self.units_num_text,
            target=self.comb_recurrent,
            width=60,
            height=20,
            tiny_space=False
        )

        # 循环层单元数 - 下拉框
        self.units_num_spin = ttk.Spinbox(self.parent, from_=16, to=512, increment=16, wrap=True)
        self.units_num_spin.set(64)
        self.layout_utils.next_to_widget(
            src=self.units_num_spin,
            target=self.units_num_text,
            width=55,
            height=20,
            tiny_space=True
        )

        # 损失函数 - 标签
        self.loss_func_text = ttk.Label(self.parent, font=("simsun", 10), text='损失函数', anchor=tk.W)
        self.layout_utils.below_widget(
            src=self.loss_func_text,
            target=self.label_num_text,
            width=65,
            height=20,
            tiny_space=True
        )

        # 损失函数 - 下拉框
        self.comb_loss = ttk.Combobox(self.parent, values=[_.name for _ in LossFunction], state='readonly')
        self.comb_loss.current(1)
        self.layout_utils.next_to_widget(
            src=self.comb_loss,
            target=self.loss_func_text,
            width=101,
            height=20,
            tiny_space=True
        )

        # 优化器 - 标签
        self.optimizer_text = ttk.Label(self.parent, font=("simsun", 10), text='优化器', anchor=tk.W)
        self.layout_utils.next_to_widget(
            src=self.optimizer_text,
            target=self.comb_loss,
            width=60,
            height=20,
            tiny_space=False
        )

        # 优化器 - 下拉框
        self.comb_optimizer = ttk.Combobox(self.parent, values=[_.name for _ in Optimizer], state='readonly')
        self.comb_optimizer.current(0)
        self.layout_utils.next_to_widget(
            src=self.comb_optimizer,
            target=self.optimizer_text,
            width=88,
            height=20,
            tiny_space=True
        )

        # 学习率 - 标签
        self.learning_rate_text = ttk.Label(self.parent, font=("simsun", 10), text='学习率', anchor=tk.W)
        self.layout_utils.next_to_widget(
            src=self.learning_rate_text,
            target=self.comb_optimizer,
            width=50,
            height=20,
            tiny_space=False
        )

        # 学习率 - 滚动框
        self.learning_rate_spin = ttk.Spinbox(self.parent, from_=0.00001, to=0.1, increment='0.0001')
        self.learning_rate_spin.set(0.001)
        self.layout_utils.next_to_widget(
            src=self.learning_rate_spin,
            target=self.learning_rate_text,
            width=67,
            height=20,
            tiny_space=True
        )

        # Resize - 标签
        self.resize_text = ttk.Label(self.parent, font=("simsun", 10), text='重置尺寸', anchor=tk.W)
        self.layout_utils.next_to_widget(
            src=self.resize_text,
            target=self.learning_rate_spin,
            width=60,
            height=20,
            tiny_space=False
        )

        # Resize - 输入框
        self.resize_val = tk.StringVar()
        self.resize_val.set('[150, 50]')
        self.resize_entry = ttk.Entry(self.parent, textvariable=self.resize_val, justify=tk.LEFT)
        self.layout_utils.next_to_widget(
            src=self.resize_entry,
            target=self.resize_text,
            width=60,
            height=20,
            tiny_space=True
        )

        # Size - 标签
        self.size_text = ttk.Label(self.parent, font=("simsun", 10), text='图片尺寸', anchor=tk.W)
        self.layout_utils.next_to_widget(
            src=self.size_text,
            target=self.resize_entry,
            width=60,
            height=20,
            tiny_space=False
        )

        # Size - 输入框
        self.size_val = tk.StringVar()
        self.size_val.set('[-1, -1]')
        self.size_entry = ttk.Entry(self.parent, textvariable=self.size_val, justify=tk.LEFT)
        self.layout_utils.next_to_widget(
            src=self.size_entry,
            target=self.size_text,
            width=60,
            height=20,
            tiny_space=True
        )

        # 类别 - 标签
        self.category_text = ttk.Label(self.parent, font=("simsun", 10), text='分类', anchor=tk.W)
        self.layout_utils.below_widget(
            src=self.category_text,
            target=self.loss_func_text,
            width=65,
            height=20,
            tiny_space=True
        )

        # 类别 - 下拉框
        self.comb_category = ttk.Combobox(self.parent, values=(
            'CUSTOMIZED',
            'NUMERIC',
            'ALPHANUMERIC',
            'ALPHANUMERIC_LOWER',
            'ALPHANUMERIC_UPPER',
            'ALPHABET_LOWER',
            'ALPHABET_UPPER',
            'ALPHABET',
            'ARITHMETIC',
            'FLOAT',
            'CHS_3500',
            'ALPHANUMERIC_CHS_3500_LOWER',
            'DOCUMENT_OCR'
        ), state='readonly')
        self.comb_category.current(1)
        self.comb_category.bind("<<ComboboxSelected>>", lambda x: self.comb_category_callback(x))
        self.layout_utils.next_to_widget(
            src=self.comb_category,
            target=self.category_text,
            width=225,
            height=20,
            tiny_space=True
        )

        # 类别 - 自定义输入框
        self.category_val = tk.StringVar()
        self.category_val.set('')
        self.category_entry = ttk.Entry(self.parent, textvariable=self.category_val, justify=tk.LEFT, state=tk.DISABLED)
        self.layout_utils.next_to_widget(
            src=self.category_entry,
            target=self.comb_category,
            width=440,
            height=20,
            tiny_space=False
        )

        # ============================= Group 3 =====================================
        self.label_frame_train = ttk.Labelframe(self.parent, text='训练配置')
        self.layout_utils.below_widget(
            src=self.label_frame_train,
            target=self.label_frame_neu,
            width=790,
            height=60,
            tiny_space=True
        )

        # 任务完成标准 - 准确率 - 标签
        self.end_acc_text = ttk.Label(self.parent, font=("simsun", 10), text='结束准确率', anchor=tk.W)
        self.layout_utils.inside_widget(
            src=self.end_acc_text,
            target=self.label_frame_train,
            width=85,
            height=20,
        )

        # 任务完成标准 - 准确率 - 输入框
        self.end_acc_val = tk.DoubleVar()
        self.end_acc_val.set(0.95)
        self.end_acc_entry = ttk.Entry(self.parent, textvariable=self.end_acc_val, justify=tk.LEFT)
        self.layout_utils.next_to_widget(
            src=self.end_acc_entry,
            target=self.end_acc_text,
            width=56,
            height=20,
            tiny_space=True
        )

        # 任务完成标准 - 平均损失 - 标签
        self.end_cost_text = ttk.Label(self.parent, font=("simsun", 10), text='结束Cost', anchor=tk.W)
        self.layout_utils.next_to_widget(
            src=self.end_cost_text,
            target=self.end_acc_entry,
            width=60,
            height=20,
            tiny_space=False
        )

        # 任务完成标准 - 平均损失 - 输入框
        self.end_cost_val = tk.DoubleVar()
        self.end_cost_val.set(0.5)
        self.end_cost_entry = ttk.Entry(self.parent, textvariable=self.end_cost_val, justify=tk.LEFT)
        self.layout_utils.next_to_widget(
            src=self.end_cost_entry,
            target=self.end_cost_text,
            width=58,
            height=20,
            tiny_space=True
        )

        # 任务完成标准 - 循环轮次 - 标签
        self.end_epochs_text = ttk.Label(self.parent, font=("simsun", 10), text='结束轮次', anchor=tk.W)
        self.layout_utils.next_to_widget(
            src=self.end_epochs_text,
            target=self.end_cost_entry,
            width=72,
            height=20,
            tiny_space=False
        )

        # 任务完成标准 - 循环轮次 - 输入框
        self.end_epochs_spin = ttk.Spinbox(self.parent, from_=0, to=10000)
        self.end_epochs_spin.set(2)
        self.layout_utils.next_to_widget(
            src=self.end_epochs_spin,
            target=self.end_epochs_text,
            width=50,
            height=20,
            tiny_space=True
        )

        # 训练批次大小 - 标签
        self.batch_size_text = ttk.Label(self.parent, font=("simsun", 10), text='训练批次大小', anchor=tk.W)
        self.layout_utils.next_to_widget(
            src=self.batch_size_text,
            target=self.end_epochs_spin,
            width=90,
            height=20,
            tiny_space=False
        )

        # 训练批次大小 - 输入框
        self.batch_size_val = tk.IntVar()
        self.batch_size_val.set(64)
        self.batch_size_entry = ttk.Entry(self.parent, textvariable=self.batch_size_val, justify=tk.LEFT)
        self.layout_utils.next_to_widget(
            src=self.batch_size_entry,
            target=self.batch_size_text,
            width=40,
            height=20,
            tiny_space=True
        )

        # 验证批次大小 - 标签
        self.validation_batch_size_text = ttk.Label(self.parent, font=("simsun", 10), text='验证批次大小', anchor=tk.W)
        self.layout_utils.next_to_widget(
            src=self.validation_batch_size_text,
            target=self.batch_size_entry,
            width=120,
            height=20,
            tiny_space=False
        )

        # 验证批次大小 - 输入框
        self.validation_batch_size_val = tk.IntVar()
        self.validation_batch_size_val.set(300)
        self.validation_batch_size_entry = ttk.Entry(self.parent, textvariable=self.validation_batch_size_val,
                                                     justify=tk.LEFT)
        self.layout_utils.next_to_widget(
            src=self.validation_batch_size_entry,
            target=self.validation_batch_size_text,
            width=40,
            height=20,
            tiny_space=True
        )

        # ============================= Group 5 =====================================
        self.label_frame_project = ttk.Labelframe(self.parent, text='项目配置')
        self.layout_utils.below_widget(
            src=self.label_frame_project,
            target=self.label_frame_train,
            width=790,
            height=60,
            tiny_space=True
        )

        # 项目名 - 标签
        self.project_name_text = ttk.Label(self.parent, font=("simsun", 10), text='项目名', anchor=tk.W)
        self.layout_utils.inside_widget(
            src=self.project_name_text,
            target=self.label_frame_project,
            width=90,
            height=20
        )

        # 项目名 - 下拉输入框
        self.comb_project_name = ttk.Combobox(self.parent)
        self.layout_utils.next_to_widget(
            src=self.comb_project_name,
            target=self.project_name_text,
            width=430,
            height=20,
            tiny_space=True
        )
        self.comb_project_name.bind(
            sequence="<Return>",
            func=lambda x: self.project_name_fill_callback(x)
        )
        self.comb_project_name.bind(
            sequence="<Button-1>",
            func=lambda x: self.fetch_projects()
        )

        def read_conf(event):
            threading.Thread(target=self.read_conf).start()

        self.comb_project_name.bind("<<ComboboxSelected>>", read_conf)

        # 保存配置 - 按钮
        self.btn_save_conf = ttk.Button(
            self.parent, style='my.TButton', text='保存配置', command=lambda: self.save_conf()
        )
        self.layout_utils.next_to_widget(
            src=self.btn_save_conf,
            target=self.comb_project_name,
            width=130,
            height=24,
            tiny_space=False,
            offset_y=-2
        )

        # 删除项目 - 按钮
        self.btn_delete = ttk.Button(
            self.parent, style='my.TButton', text='删除', command=lambda: self.delete_project()
        )
        self.layout_utils.next_to_widget(
            src=self.btn_delete,
            target=self.btn_save_conf,
            width=80,
            height=24,
            tiny_space=False,
        )

        # ============================= Group 6 =====================================
        self.label_frame_dataset = ttk.Labelframe(
            self.parent, text='样本数据集',
        )
        self.layout_utils.below_widget(
            src=self.label_frame_dataset,
            target=self.label_frame_project,
            width=790,
            height=170,
            tiny_space=True
        )

        # 附加训练集 - 按钮
        self.btn_attach_dataset = ttk.Button(
            self.parent,
            style='my.TButton',
            text='附加数据',
            command=lambda: self.attach_dataset()
        )
        self.layout_utils.inside_widget(
            src=self.btn_attach_dataset,
            target=self.label_frame_dataset,
            width=120,
            height=24,
        )

        # 附加训练集 - 显示框
        self.attach_dataset_val = tk.StringVar()
        self.attach_dataset_val.set('')
        self.attach_dataset_entry = ttk.Entry(
            self.parent, textvariable=self.attach_dataset_val, justify=tk.LEFT, state=tk.DISABLED
        )
        self.layout_utils.next_to_widget(
            src=self.attach_dataset_entry,
            target=self.btn_attach_dataset,
            width=420,
            height=24,
            tiny_space=True
        )

        # 验证集数目 - 标签
        self.validation_num_text = ttk.Label(self.parent, font=("simsun", 10), text='验证集数目', anchor=tk.W)
        self.layout_utils.next_to_widget(
            src=self.validation_num_text,
            target=self.attach_dataset_entry,
            width=120,
            height=20,
            tiny_space=False,
            offset_y=2
        )

        # 验证集数目 - 输入框
        self.validation_num_val = tk.IntVar()
        self.validation_num_val.set(300)
        self.validation_num_entry = ttk.Entry(self.parent, textvariable=self.validation_num_val, justify=tk.LEFT)
        self.layout_utils.next_to_widget(
            src=self.validation_num_entry,
            target=self.validation_num_text,
            width=71,
            height=20,
            tiny_space=True
        )

        # 训练集路径 - 标签
        self.dataset_train_path_text = ttk.Label(self.parent, font=("simsun", 10), text='训练集数据集', anchor=tk.W)
        self.layout_utils.below_widget(
            src=self.dataset_train_path_text,
            target=self.btn_attach_dataset,
            width=100,
            height=20,
            tiny_space=False
        )

        # 训练集路径 - 列表框
        self.dataset_train_listbox = tk.Listbox(self.parent, font=('微软雅黑', 9))
        self.layout_utils.next_to_widget(
            src=self.dataset_train_listbox,
            target=self.dataset_train_path_text,
            width=640,
            height=36,
            tiny_space=False
        )
        self.dataset_train_listbox.bind(
            sequence="<Delete>",
            func=lambda x: self.listbox_delete_item_callback(x, self.dataset_train_listbox)
        )
        self.listbox_scrollbar(self.dataset_train_listbox)

        # 验证集路径 - 标签
        label_edge = self.layout_utils.object_edge_info(self.dataset_train_path_text)
        widget_edge = self.layout_utils.object_edge_info(self.dataset_train_listbox)
        self.dataset_validation_path_text = ttk.Label(self.parent, font=("simsun", 10), text='验证集数据集', anchor=tk.W)
        self.dataset_validation_path_text.place(
            x=label_edge['x'],
            y=widget_edge['edge_y'] + self.layout['global']['space']['y'] / 2,
            width=100,
            height=20
        )

        # 验证集路径 - 下拉输入框
        self.dataset_validation_listbox = tk.Listbox(self.parent, font=('微软雅黑', 9))
        self.layout_utils.next_to_widget(
            src=self.dataset_validation_listbox,
            target=self.dataset_validation_path_text,
            width=640,
            height=36,
            tiny_space=False
        )
        self.dataset_validation_listbox.bind(
            sequence="<Delete>",
            func=lambda x: self.listbox_delete_item_callback(x, self.dataset_validation_listbox)
        )
        self.listbox_scrollbar(self.dataset_validation_listbox)

        self.sample_map = {
            DatasetType.Directory: {
                RunMode.Trains: self.source_train_path_listbox,
                RunMode.Validation: self.source_validation_path_listbox
            },
            DatasetType.TFRecords: {
                RunMode.Trains: self.dataset_train_listbox,
                RunMode.Validation: self.dataset_validation_listbox
            }
        }

        # 开始训练 - 按钮
        self.btn_training = ttk.Button(self.parent, style='my.TButton', text='开始训练',
                                       command=lambda: self.start_training())
        self.layout_utils.widget_from_right(
            src=self.btn_training,
            target=self.label_frame_dataset,
            width=120,
            height=24,
            tiny_space=True
        )

        # 终止训练 - 按钮
        self.btn_stop = ttk.Button(self.parent, style='my.TButton', text='停止', command=lambda: self.stop_training())
        self.button_state(self.btn_stop, tk.DISABLED)
        self.layout_utils.before_widget(
            src=self.btn_stop,
            target=self.btn_training,
            width=60,
            height=24,
            tiny_space=True
        )

        # 编译模型 - 按钮
        self.btn_compile = ttk.Button(self.parent, style='my.TButton', text='编译', command=lambda: self.compile())
        self.layout_utils.before_widget(
            src=self.btn_compile,
            target=self.btn_stop,
            width=80,
            height=24,
            tiny_space=True
        )

        # 打包训练集 - 按钮
        self.btn_make_dataset = ttk.Button(self.parent, style='my.TButton', text='打包数据集',
                                           command=lambda: self.make_dataset())
        self.layout_utils.before_widget(
            src=self.btn_make_dataset,
            target=self.btn_compile,
            width=120,
            height=24,
            tiny_space=True
        )

        # 清除训练记录 - 按钮
        self.btn_reset_history = ttk.Button(
            self.parent, style='my.TButton', text='清空训练记录', command=lambda: self.reset_history()
        )
        self.layout_utils.before_widget(
            src=self.btn_reset_history,
            target=self.btn_make_dataset,
            width=120,
            height=24,
            tiny_space=True
        )

        # 预测 - 按钮
        self.btn_testing = ttk.Button(
            self.parent, style='my.TButton', text='测试', command=lambda: self.testing_model()
        )
        self.layout_utils.before_widget(
            src=self.btn_testing,
            target=self.btn_reset_history,
            width=80,
            height=24,
            tiny_space=True
        )

        self.parent.geometry(size)

    @staticmethod
    def threading_exec(func, *args) -> threading.Thread:
        th = threading.Thread(target=func, args=args)
        th.setDaemon(True)
        th.start()
        return th

    def popup_data_augmentation(self):
        if not self.current_project:
            messagebox.showerror(
                "Error!", "请先配置项目名."
            )
            return
        data_augmentation = DataAugmentationDialog()
        data_augmentation.read_conf(self.data_augmentation_entity)

    def popup_pretreatment(self):
        if not self.current_project:
            messagebox.showerror(
                "Error!", "请先配置项目名."
            )
            return
        pretreatment = PretreatmentDialog()
        pretreatment.read_conf(self.pretreatment_entity)

    @staticmethod
    def listbox_scrollbar(listbox: tk.Listbox):
        y_scrollbar = tk.Scrollbar(
            listbox, command=listbox.yview
        )
        y_scrollbar.pack(side=tk.RIGHT, fill=tk.Y)
        listbox.config(yscrollcommand=y_scrollbar.set)

    def blank_click(self, event):
        if self.current_project != self.comb_project_name.get():
            self.project_name_fill_callback(event)

    def project_name_fill_callback(self, event):
        suffix = '-{}-{}-H{}-{}-C{}'.format(
            self.comb_neu_cnn.get(),
            self.comb_recurrent.get(),
            self.units_num_spin.get(),
            self.comb_loss.get(),
            self.comb_channel.get(),
        )
        current_project_name = self.comb_project_name.get()
        if len(current_project_name) > 0 and current_project_name not in self.project_names:
            self.extract_regex = ".*?(?=_)"
            self.label_from_var.set('FileName')
            self.sample_map[DatasetType.Directory][RunMode.Trains].delete(0, tk.END)
            self.sample_map[DatasetType.Directory][RunMode.Validation].delete(0, tk.END)
            self.category_val.set("")
            if not current_project_name.endswith(suffix):
                self.comb_project_name.insert(tk.END, suffix)
            self.current_project = self.comb_project_name.get()
            self.update_dataset_files_path(mode=RunMode.Trains)
            self.update_dataset_files_path(mode=RunMode.Validation)
            self.data_augmentation_entity = DataAugmentationEntity()
            self.pretreatment_entity = PretreatmentEntity()

    @property
    def project_path(self):
        if not self.current_project:
            return None
        project_path = "{}/{}".format(self.project_root_path, self.current_project)
        if not os.path.exists(project_path):
            os.makedirs(project_path)
        return project_path

    def update_dataset_files_path(self, mode: RunMode):
        dataset_name = "dataset/{}.0.tfrecords".format(mode.value)
        dataset_path = os.path.join(self.project_path, dataset_name)
        dataset_path = dataset_path.replace("\\", '/')
        self.sample_map[DatasetType.TFRecords][mode].delete(0, tk.END)
        self.sample_map[DatasetType.TFRecords][mode].insert(tk.END, dataset_path)
        self.save_conf()

    def attach_dataset(self):
        if self.is_task_running:
            messagebox.showerror(
                "Error!", "请先结束当前训练或者等待训练完成."
            )
            return
        if not self.current_project:
            messagebox.showerror(
                "Error!", "请先配置项目名."
            )
            return
        filename = filedialog.askdirectory()
        if not filename:
            return
        model_conf = ModelConfig(self.current_project)

        if not self.check_dataset(model_conf):
            return

        self.attach_dataset_val.set(filename)
        self.sample_map[DatasetType.Directory][RunMode.Trains].insert(tk.END, filename)
        self.button_state(self.btn_attach_dataset, tk.DISABLED)

        for mode in [RunMode.Trains, RunMode.Validation]:
            attached_dataset_name = model_conf.dataset_increasing_name(mode)
            attached_dataset_name = "dataset/{}".format(attached_dataset_name)
            attached_dataset_path = os.path.join(self.project_path, attached_dataset_name)
            attached_dataset_path = attached_dataset_path.replace("\\", '/')
            if mode == RunMode.Validation and self.validation_num_val.get() == 0:
                continue
            self.sample_map[DatasetType.TFRecords][mode].insert(tk.END, attached_dataset_path)
        self.save_conf()
        model_conf = ModelConfig(self.current_project)
        self.threading_exec(
            lambda: DataSets(model_conf).make_dataset(
                trains_path=filename,
                is_add=True,
                callback=lambda: self.button_state(self.btn_attach_dataset, tk.NORMAL),
                msg=lambda x: tk.messagebox.showinfo('附加数据状态', x)
            )
        )
        pass

    @staticmethod
    def button_state(btn: ttk.Button, state: str):
        btn['state'] = state

    def delete_project(self):
        if not self.current_project:
            messagebox.showerror(
                "Error!", "请选择一个项目删除."
            )
            return
        if self.is_task_running:
            messagebox.showerror(
                "Error!", "请先结束当前训练或者等待训练完成."
            )
            return
        project_path = "./projects/{}".format(self.current_project)
        try:
            shutil.rmtree(project_path)
        except Exception as e:
            messagebox.showerror(
                "Error!", json.dumps(e.args, ensure_ascii=False)
            )
        messagebox.showinfo(
            "Error!", "删除成功!"
        )
        self.comb_project_name.delete(0, tk.END)

    def reset_history(self):
        if not self.current_project:
            messagebox.showerror(
                "Error!", "请先选择一个项目."
            )
            return
        if self.is_task_running:
            messagebox.showerror(
                "Error!", "请先结束当前训练或者等待训练完成."
            )
            return
        project_history_path = "./projects/{}/model".format(self.current_project)
        try:
            shutil.rmtree(project_history_path)
        except Exception as e:
            messagebox.showerror(
                "Error!", json.dumps(e.args, ensure_ascii=False)
            )
        messagebox.showinfo(
            "消息", "清空训练历史成功!"
        )

    def testing_model(self):
        filename = filedialog.askdirectory()
        if not filename:
            return
        filename = filename.replace("\\", "/")
        predict = Predict(project_name=self.current_project)
        predict.testing(image_dir=filename, limit=self.validation_batch_size)

    def clear_dataset(self):
        if not self.current_project:
            messagebox.showerror(
                "Error!", "请先选择一个项目."
            )
            return
        if self.is_task_running:
            messagebox.showerror(
                "Error!", "请先结束当前训练或者等待训练完成."
            )
            return
        project_history_path = "./projects/{}/dataset".format(self.current_project)
        try:
            shutil.rmtree(project_history_path)
            self.dataset_train_listbox.delete(1, tk.END)
            self.dataset_validation_listbox.delete(1, tk.END)
        except Exception as e:
            messagebox.showerror(
                "Error!", json.dumps(e.args, ensure_ascii=False)
            )
        messagebox.showinfo(
            "消息", "清空数据集成功!"
        )

    @staticmethod
    def popup_about():
        messagebox.showinfo("关于",
                            "Eve-深度训练 核心版本({})\n\n作者邮箱: kerlomz@gmail.com\n\nQQ 群: 857149419".format(
                                get_version()))

    def auto_loss(self, event):
        if self.comb_recurrent.get() == 'NoRecurrent':
            self.comb_loss.set("CrossEntropy")

    @staticmethod
    def get_param(src: dict, key, default=None):
        result = src.get(key)
        return result if result else default

    def read_conf(self):
        print('Reading configuration...')
        selected = self.comb_project_name.get()
        self.current_project = selected
        model_conf = ModelConfig(selected)
        self.edit_var.set(model_conf.memory_usage)
        self.size_val.set("[{}, {}]".format(model_conf.image_width, model_conf.image_height))
        self.resize_val.set(json.dumps(model_conf.resize))
        self.source_train_path_listbox.delete(0, tk.END)
        self.source_validation_path_listbox.delete(0, tk.END)
        self.dataset_validation_listbox.delete(0, tk.END)
        self.dataset_train_listbox.delete(0, tk.END)
        for source_train in self.get_param(model_conf.trains_path, DatasetType.Directory, default=[]):
            self.source_train_path_listbox.insert(tk.END, source_train)
        for source_validation in self.get_param(model_conf.validation_path, DatasetType.Directory, default=[]):
            self.source_validation_path_listbox.insert(tk.END, source_validation)
        self.label_num_spin.set(model_conf.max_label_num)
        self.comb_channel.set(model_conf.image_channel)
        self.comb_neu_cnn.set(model_conf.neu_cnn_param)
        self.comb_recurrent.set(model_conf.neu_recurrent_param)
        self.units_num_spin.set(model_conf.units_num)
        self.comb_loss.set(model_conf.loss_func_param)

        self.extract_regex = model_conf.extract_regex
        self.label_split = model_conf.label_split
        self.label_from_var.set(model_conf.label_from.value)

        self.comb_optimizer.set(model_conf.neu_optimizer_param)
        self.learning_rate_spin.set(model_conf.trains_learning_rate)
        self.end_acc_val.set(model_conf.trains_end_acc)
        self.end_cost_val.set(model_conf.trains_end_cost)
        self.end_epochs_spin.set(model_conf.trains_end_epochs)
        self.batch_size_val.set(model_conf.batch_size)
        self.validation_batch_size_val.set(model_conf.validation_batch_size)
        self.validation_num_val.set(model_conf.validation_set_num)

        self.data_augmentation_entity.binaryzation = model_conf.da_binaryzation
        self.data_augmentation_entity.median_blur = model_conf.da_median_blur
        self.data_augmentation_entity.gaussian_blur = model_conf.da_gaussian_blur
        self.data_augmentation_entity.equalize_hist = model_conf.da_equalize_hist
        self.data_augmentation_entity.laplace = model_conf.da_laplace
        self.data_augmentation_entity.warp_perspective = model_conf.da_warp_perspective
        self.data_augmentation_entity.rotate = model_conf.da_rotate
        self.data_augmentation_entity.sp_noise = model_conf.da_sp_noise
        self.data_augmentation_entity.brightness = model_conf.da_brightness
        self.data_augmentation_entity.hue = model_conf.da_hue
        self.data_augmentation_entity.saturation = model_conf.da_saturation
        self.data_augmentation_entity.gamma = model_conf.da_gamma
        self.data_augmentation_entity.channel_swap = model_conf.da_channel_swap
        self.data_augmentation_entity.random_blank = model_conf.da_random_blank
        self.data_augmentation_entity.random_transition = model_conf.da_random_transition
        self.data_augmentation_entity.random_captcha = model_conf.da_random_captcha

        self.pretreatment_entity.binaryzation = model_conf.pre_binaryzation
        self.pretreatment_entity.replace_transparent = model_conf.pre_replace_transparent
        self.pretreatment_entity.horizontal_stitching = model_conf.pre_horizontal_stitching
        self.pretreatment_entity.concat_frames = model_conf.pre_concat_frames
        self.pretreatment_entity.blend_frames = model_conf.pre_blend_frames
        self.pretreatment_entity.exec_map = model_conf.pre_exec_map

        for dataset_validation in self.get_param(model_conf.validation_path, DatasetType.TFRecords, default=[]):
            self.dataset_validation_listbox.insert(tk.END, dataset_validation)
        for dataset_train in self.get_param(model_conf.trains_path, DatasetType.TFRecords, default=[]):
            self.dataset_train_listbox.insert(tk.END, dataset_train)

        # print('Loading category configuration...')
        if isinstance(model_conf.category_param, list):
            self.category_entry['state'] = tk.DISABLED
            self.comb_category.set('CUSTOMIZED')
            if len(model_conf.category_param) > 1000:
                self.category_val.set(NOT_EDITABLE_MSG)
            else:
                self.category_val.set(model_conf.category_param_text)
                self.category_entry['state'] = tk.NORMAL
        else:
            self.category_val.set("")
            self.category_entry['state'] = tk.DISABLED
            self.comb_category.set(model_conf.category_param)
        # print('Loading configuration is completed.')
        self.model_conf = model_conf
        return self.model_conf

    @property
    def validation_batch_size(self):
        # if self.dataset_validation_listbox.size() > 1:
        return self.validation_batch_size_val.get()
        # else:
        #     return min(self.validation_batch_size_val.get(), self.validation_num_val.get())

    @property
    def device_usage(self):
        return self.edit_var.get()

    def save_conf(self):
        if not self.current_project:
            messagebox.showerror(
                "Error!", "请先配置项目名."
            )
            return
        model_conf = ModelConfig(
            project_name=self.current_project,
            MemoryUsage=self.device_usage,
            CNNNetwork=self.neu_cnn,
            RecurrentNetwork=self.neu_recurrent,
            UnitsNum=self.units_num_spin.get(),
            Optimizer=self.optimizer,
            LossFunction=self.loss_func,
            Decoder=self.comb_loss.get(),
            ModelName=self.current_project,
            ModelField=ModelField.Image.value,
            ModelScene=ModelScene.Classification.value,
            Category=self.category,
            Resize=self.resize,
            ImageChannel=self.comb_channel.get(),
            ImageWidth=self.image_width,
            ImageHeight=self.image_height,
            MaxLabelNum=self.label_num_spin.get(),
            AutoPadding=True,
            ReplaceTransparent=False,
            HorizontalStitching=False,
            OutputSplit='',
            LabelFrom=self.label_from_var.get(),
            ExtractRegex=self.extract_regex,
            LabelSplit=self.label_split,
            DatasetTrainsPath=self.dataset_value(
                dataset_type=DatasetType.TFRecords, mode=RunMode.Trains
            ),
            DatasetValidationPath=self.dataset_value(
                dataset_type=DatasetType.TFRecords, mode=RunMode.Validation
            ),
            SourceTrainPath=self.dataset_value(
                dataset_type=DatasetType.Directory, mode=RunMode.Trains
            ),
            SourceValidationPath=self.dataset_value(
                dataset_type=DatasetType.Directory, mode=RunMode.Validation
            ),
            ValidationSetNum=self.validation_num_val.get(),
            SavedSteps=100,
            ValidationSteps=500,
            EndAcc=self.end_acc_val.get(),
            EndCost=self.end_cost_val.get(),
            EndEpochs=self.end_epochs_spin.get(),
            BatchSize=self.batch_size_val.get(),
            ValidationBatchSize=self.validation_batch_size,
            LearningRate=self.learning_rate_spin.get(),
            DA_Binaryzation=self.data_augmentation_entity.binaryzation,
            DA_MedianBlur=self.data_augmentation_entity.median_blur,
            DA_GaussianBlur=self.data_augmentation_entity.gaussian_blur,
            DA_EqualizeHist=self.data_augmentation_entity.equalize_hist,
            DA_Laplace=self.data_augmentation_entity.laplace,
            DA_WarpPerspective=self.data_augmentation_entity.warp_perspective,
            DA_Rotate=self.data_augmentation_entity.rotate,
            DA_PepperNoise=self.data_augmentation_entity.sp_noise,
            DA_Brightness=self.data_augmentation_entity.brightness,
            DA_Saturation=self.data_augmentation_entity.saturation,
            DA_Hue=self.data_augmentation_entity.hue,
            DA_Gamma=self.data_augmentation_entity.gamma,
            DA_ChannelSwap=self.data_augmentation_entity.channel_swap,
            DA_RandomBlank=self.data_augmentation_entity.random_blank,
            DA_RandomTransition=self.data_augmentation_entity.random_transition,
            DA_RandomCaptcha=self.data_augmentation_entity.random_captcha,
            Pre_Binaryzation=self.pretreatment_entity.binaryzation,
            Pre_ReplaceTransparent=self.pretreatment_entity.replace_transparent,
            Pre_HorizontalStitching=self.pretreatment_entity.horizontal_stitching,
            Pre_ConcatFrames=self.pretreatment_entity.concat_frames,
            Pre_BlendFrames=self.pretreatment_entity.blend_frames,
            Pre_ExecuteMap=self.pretreatment_entity.exec_map
        )
        model_conf.update()
        return model_conf

    def make_dataset(self):
        if not self.current_project:
            messagebox.showerror(
                "Error!", "请先配置项目名."
            )
            return
        if self.is_task_running:
            messagebox.showerror(
                "Error!", "请先结束当前训练或者等待训练完成."
            )
            return
        self.save_conf()
        self.button_state(self.btn_make_dataset, tk.DISABLED)
        model_conf = ModelConfig(self.current_project)
        train_path = self.dataset_value(DatasetType.Directory, RunMode.Trains)
        validation_path = self.dataset_value(DatasetType.Directory, RunMode.Validation)
        if len(train_path) < 1:
            messagebox.showerror(
                "错误!", "{} 样本尚未被添加.".format(RunMode.Trains.value)
            )
            self.button_state(self.btn_make_dataset, tk.NORMAL)
            return
        self.threading_exec(
            lambda: DataSets(model_conf).make_dataset(
                trains_path=train_path,
                validation_path=validation_path,
                is_add=False,
                callback=lambda: self.button_state(self.btn_make_dataset, tk.NORMAL),
                msg=lambda x: tk.messagebox.showinfo('打包数据集状态', x)
            )
        )

    @property
    def size(self):
        return self.json_filter(self.size_val.get(), int)

    @property
    def image_height(self):
        return self.size[1]

    @property
    def image_width(self):
        return self.size[0]

    @property
    def resize(self):
        return self.json_filter(self.resize_val.get(), int)

    @property
    def neu_cnn(self):
        return self.comb_neu_cnn.get()

    @property
    def neu_recurrent(self):
        return self.comb_recurrent.get()

    @property
    def loss_func(self):
        return self.comb_loss.get()

    @property
    def optimizer(self):
        return self.comb_optimizer.get()

    @staticmethod
    def json_filter(content, item_type):
        if not content:
            messagebox.showerror(
                "Error!", "您选择了自定义分类，必须手动指定分类集."
            )
            return None
        try:
            content = json.loads(content)
        except ValueError as e:
            messagebox.showerror(
                "Error!", "输入格式必须符合JSON."
            )
            return None
        content = [item_type(i) for i in content]
        return content

    @property
    def category(self):
        comb_selected = self.comb_category.get()
        if not comb_selected:
            messagebox.showerror(
                "Error!", "请选择内置分类或自定义分类"
            )
            return None
        if comb_selected == 'CUSTOMIZED':
            category_value = self.category_entry.get()
            if category_value == NOT_EDITABLE_MSG:
                return self.model_conf.category_param_text
            category_value = category_value.replace("'", '"') if "'" in category_value else category_value
            category_value = self.json_filter(category_value, str)
        else:
            category_value = comb_selected
        return category_value

    def dataset_value(self, dataset_type: DatasetType, mode: RunMode):
        listbox = self.sample_map[dataset_type][mode]
        value = list(listbox.get(0, listbox.size() - 1))
        return value

    def compile_task(self):
        if not self.current_project:
            messagebox.showerror(
                "Error!", "请先配置项目名."
            )
            return
        model_conf = ModelConfig(project_name=self.current_project)
        if not os.path.exists(model_conf.model_root_path):
            messagebox.showerror(
                "Error", "模型存储路径不存在."
            )
            return
        if len(os.listdir(model_conf.model_root_path)) < 3:
            messagebox.showerror(
                "Error", "当前无训练记录，请先训练再编译."
            )
            return
        try:
            if not self.current_task:
                self.current_task = Trains(model_conf)

            self.current_task.compile_graph(0)
            status = '编译完成'
        except Exception as e:
            messagebox.showerror(
                e.__class__.__name__, json.dumps(e.args, ensure_ascii=False)
            )
            status = '编译失败'
        tk.messagebox.showinfo('编译状态', status)

    def compile(self):
        self.job = self.threading_exec(
            lambda: self.compile_task()
        )

    def training_task(self):
        model_conf = ModelConfig(project_name=self.current_project)

        self.current_task = Trains(model_conf)
        try:
            self.button_state(self.btn_training, tk.DISABLED)
            self.button_state(self.btn_stop, tk.NORMAL)
            self.is_task_running = True
            self.current_task.train_process()
            status = '训练完成'
        except Exception as e:
            traceback.print_exc()
            messagebox.showerror(
                e.__class__.__name__, json.dumps(e.args, ensure_ascii=False)
            )
            status = '训练失败'
        self.button_state(self.btn_training, tk.NORMAL)
        self.button_state(self.btn_stop, tk.DISABLED)
        self.comb_project_name['state'] = tk.NORMAL
        self.is_task_running = False
        tk.messagebox.showinfo('训练状态', status)

    @staticmethod
    def check_dataset(model_conf):
        trains_path = model_conf.trains_path[DatasetType.TFRecords]
        validation_path = model_conf.validation_path[DatasetType.TFRecords]
        if not trains_path or not validation_path:
            messagebox.showerror(
                "Error!", "训练集或验证集未定义."
            )
            return False
        for tp in trains_path:
            if not os.path.exists(tp):
                messagebox.showerror(
                    "Error!", "训练集集路径不存在，请先打包样本."
                )
                return False
        for vp in validation_path:
            if not os.path.exists(vp):
                messagebox.showerror(
                    "Error!", "验证集路径不存在，请先打包样本"
                )
                return False
        return True

    def start_training(self):
        if not self.check_resize():
            return
        if not self.current_project:
            messagebox.showerror(
                "Error!", "请先配置项目名."
            )
            return
        model_conf = self.save_conf()
        if not self.check_dataset(model_conf):
            return
        self.comb_project_name['state'] = tk.DISABLED
        self.job = self.threading_exec(
            lambda: self.training_task()
        )

    def stop_training(self):
        self.current_task.stop_flag = True

    @property
    def project_names(self):
        return [i.name for i in os.scandir(self.project_root_path) if i.is_dir()]

    def fetch_projects(self):
        self.comb_project_name['values'] = self.project_names

    def browse_dataset(self, dataset_type: DatasetType, mode: RunMode):
        if not self.current_project:
            messagebox.showerror(
                "Error!", "请先配置项目名."
            )
            return
        filename = filedialog.askdirectory()
        if not filename:
            return
        is_sub = False
        for i, item in enumerate(os.scandir(filename)):
            if item.is_dir():
                path = item.path.replace("\\", "/")
                if self.sample_map[dataset_type][mode].size() == 0:
                    self.fetch_sample([path])
                self.sample_map[dataset_type][mode].insert(tk.END, path)
                if i > 0:
                    continue
                is_sub = True
            else:
                break
        if not is_sub:
            filename = filename.replace("\\", "/")
            if self.sample_map[dataset_type][mode].size() == 0:
                self.fetch_sample([filename])
            self.sample_map[dataset_type][mode].insert(tk.END, filename)

    @staticmethod
    def closest_category(category):
        category = set(category)
        category_group = dict()
        for key in SIMPLE_CATEGORY_MODEL.keys():
            category_set = set(category_extract(key))
            if category <= category_set:
                category_group[key] = len(category_set) - len(category)
        if not category_group:
            return None
        min_index = min(category_group.values())
        for k, v in category_group.items():
            if v == min_index:
                return k

    def fetch_category(self):
        if self.model_conf.label_from == LabelFrom.TXT or self.label_from_var.get() == LabelFrom.TXT.value:
            messagebox.showerror(
                "Error!", "当前标签源不支持."
            )
            return
        self.save_conf()
        category_list = fetch_category_list(self.model_conf, is_json=True)
        if not category_list:
            return
        self.comb_category.current(0)
        if len(category_list) > 1000:
            self.category_entry['state'] = tk.DISABLED
            self.category_val.set(NOT_EDITABLE_MSG)
            self.model_conf.category_param_text = category_list
        else:
            self.category_entry['state'] = tk.NORMAL
            self.category_val.set(category_list)
        self.save_conf()

    def fetch_sample(self, dataset_path):
        file_names = os.listdir(dataset_path[0])[0:100]
        category = list()
        len_label = -1

        for file_name in file_names:
            if "_" in file_name:
                label = file_name.split("_")[0]
                label = [i for i in label]
                len_label = len(label)
                category.extend(label)

        size = PilImage.open(os.path.join(dataset_path[0], file_names[0])).size
        self.size_val.set(json.dumps(size))
        self.resize_val.set(json.dumps(size))
        self.label_num_spin.set(len_label)
        if not self.category_val.get() or self.category_val.get() != NOT_EDITABLE_MSG:
            category_pram = self.closest_category(category)
            if not category_pram:
                return
            self.comb_category.set(category_pram)

    def listbox_delete_item_callback(self, event, listbox: tk.Listbox):
        try:
            i = listbox.curselection()[0]
            listbox.delete(i)
            self.save_conf()
        except IndexError as e:
            print(e)

    def comb_category_callback(self, event):
        comb_selected = self.comb_category.get()
        if comb_selected == 'CUSTOMIZED':
            self.category_entry['state'] = tk.NORMAL
        else:
            self.category_entry.delete(0, tk.END)
            self.category_entry['state'] = tk.DISABLED

    def check_resize(self):
        if self.loss_func == 'CTC':
            return True
        param = OUTPUT_SHAPE1_MAP[NETWORK_MAP[self.neu_cnn]]
        shape1w = math.ceil(1.0 * self.resize[0] / param[0])
        shape1h = math.ceil(1.0 * self.resize[1] / param[0])
        input_s1 = shape1w * shape1h * param[1]
        label_num = int(self.label_num_spin.get())
        if input_s1 % label_num != 0:
            messagebox.showerror(
                "Error!", "Shape[1] = {} 必须被 label_num = {} 整除.".format(input_s1, label_num)
            )
            return False
        return True

    @staticmethod
    def resource_path(relative_path):
        try:
            # PyInstaller creates a temp folder and stores path in _MEIPASS
            base_path = sys._MEIPASS
        except AttributeError:
            base_path = os.path.abspath(".")
        return os.path.join(base_path, relative_path)


if __name__ == '__main__':
    root = tk.Tk()
    app = Wizard(root)
    root.mainloop()