vww.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2f6ddc86-2410-4f92-b718-9fc526892df3",
   "metadata": {},
   "source": [
    "# Import Section\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3a6655ef-d4d1-4f1b-aa15-a82358c0cd4d",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import regex as re\n",
    "import shutil\n",
    "import os\n",
    "from subprocess import Popen\n",
    "import subprocess\n",
    "\n",
    "\n",
    "import ipywidgets as widgets\n",
    "from ipywidgets import interact, interact_manual, interactive\n",
    "from ipywidgets import AppLayout, Button, Layout, Box, FloatText, Textarea, Dropdown, Label, IntSlider\n",
    "from IPython.display import display, HTML\n",
    "from IPython.display import clear_output\n",
    "from ipyfilechooser import FileChooser"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47fdfc08-2ec2-446f-9d5b-9dcf05dbf869",
   "metadata": {},
   "source": [
    "# Widgets Control Section\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ce8b6cd0-2e45-4997-bc77-4aa67ffcba62",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "class train_config_and_cmds_widgets():\n",
    "    \n",
    "#------------------#\n",
    "# init all the\n",
    "#------------------#        \n",
    "    def __init__(self):\n",
    "        \n",
    "        self.tflite_file_loc = \"\"\n",
    "        \n",
    "        form_item_layout = Layout(\n",
    "        display='flex',\n",
    "        flex_flow='row',\n",
    "        justify_content='space-between',\n",
    "        )\n",
    "    \n",
    "        ### data prepare ###\n",
    "        self.A_dp = widgets.Textarea(value=r'C:\\Users\\USER\\image_classification\\ML_tf2_object_detection_nu\\image_dataset\\coco-2017\\train\\data', \n",
    "                                     placeholder='Type something', disabled=False, layout={'height': '40pt'})\n",
    "        self.B_dp = widgets.Textarea(value=r'C:\\Users\\USER\\image_classification\\ML_tf2_object_detection_nu\\image_dataset\\coco-2017\\validation\\data', \n",
    "                                     placeholder='Type something', disabled=False, layout={'height': '40pt'})\n",
    "        self.C_dp = widgets.Textarea(value=r'C:\\Users\\USER\\image_classification\\ML_tf2_object_detection_nu\\image_dataset\\coco-2017\\raw\\instances_train2017.json', \n",
    "                                     placeholder='Type something', disabled=False, layout={'height': '40pt'})\n",
    "        self.D_dp = widgets.Textarea(value=r'C:\\Users\\USER\\image_classification\\ML_tf2_object_detection_nu\\image_dataset\\coco-2017\\raw\\instances_val2017.json', \n",
    "                                     placeholder='Type something', disabled=False, layout={'height': '40pt'})\n",
    "        self.E_dp = widgets.Text(value=r'dataset\\datasets\\coco_person', placeholder='Type something', disabled=False)\n",
    "        self.F_dp = widgets.Text(value='person', placeholder='Type something', disabled=False)\n",
    "        self.G_dp = widgets.Button(description='Run', layout=Layout(width='30%', height='30px'), button_style='success')\n",
    "        \n",
    "        form_data_prepare_items = [\n",
    "            Box([Label(value = 'Train Image Dir'),        self.A_dp], layout=form_item_layout),\n",
    "            Box([Label(value = 'Val Image Dir'),          self.B_dp], layout=form_item_layout),\n",
    "            Box([Label(value = 'Train Annotations File'), self.C_dp], layout=form_item_layout),\n",
    "            Box([Label(value = 'Val Annotations File'),   self.D_dp], layout=form_item_layout),\n",
    "            Box([Label(value = 'Output Dir'),             self.E_dp], layout=form_item_layout),\n",
    "            Box([Label(value = 'Object Name'),            self.F_dp], layout=form_item_layout),\n",
    "            Box([Label(value = 'Start to Execute'),       self.G_dp], layout=form_item_layout),\n",
    "        ]\n",
    "        \n",
    "        self.form_data_prepare_cmd = Box(form_data_prepare_items, layout=Layout(\n",
    "            display='flex',\n",
    "            flex_flow='column',\n",
    "            border='solid 1px lightblue',\n",
    "            align_items='stretch',\n",
    "            width='100%',\n",
    "        ))\n",
    "        \n",
    "        ### train ###\n",
    "        self.A_ta = widgets.Text(value='vww_v2_96_035', placeholder='Type something', disabled=False)\n",
    "        self.E_ta = Dropdown(options=['mobilenetv2', 'mobilenetv1', 'mobilenetv3'])\n",
    "        self.F_ta = Dropdown(options=['rgb', 'grayscale'])\n",
    "        self.B_ta = widgets.IntSlider(value=256, min=4, max=512, step=4)\n",
    "        self.C_ta = widgets.IntSlider(value=96, min=64, max=192, step=32)\n",
    "        self.D_ta = widgets.FloatSlider(value=0.35, min=0.1, max=1.5, step=0.05)\n",
    "        \n",
    "        self.H_ta = widgets.BoundedIntText(value=5, min=1, max=500, step=1)\n",
    "        self.I_ta = widgets.Text(value='0.0001', placeholder='Type something', disabled=False)\n",
    "\n",
    "        self.J_ta = Dropdown(value='1: Train model & Convert to tflite', \n",
    "                             options=['0: Show the data pictures only', '1: Train model & Convert to tflite', \n",
    "                                      '2: Convert to tflite'])\n",
    "        self.L_ta = widgets.Button(description='Run', layout=Layout(width='30%', height='30px'), button_style='success')\n",
    "        \n",
    "        self.K_ta = widgets.BoundedIntText(value=50, min=0, max=300, step=1, disabled=False)\n",
    "        self.fine_tune_LA = Label(value = 'Freezing Layers of Fine-Tuning')        \n",
    "        self.K_ta_box = Box([self.fine_tune_LA, self.K_ta], layout=form_item_layout)\n",
    "        \n",
    "        self.M_ta = widgets.BoundedIntText(value=50, min=1, max=1000, step=1)\n",
    "        self.fine_tune_LB = Label(value = 'Epochs of Fine-Tuning')        \n",
    "        self.M_ta_box = Box([self.fine_tune_LB, self.M_ta], layout=form_item_layout)\n",
    "        \n",
    "        self.N_ta = widgets.Text(value='0.00001', placeholder='Type something', disabled=False)\n",
    "        self.fine_tune_LC = Label(value = 'Learning Rate of Fine-Tuning')        \n",
    "        self.N_ta_box = Box([self.fine_tune_LC, self.N_ta], layout=form_item_layout)\n",
    "        \n",
    "        \n",
    "        form_train_items = [\n",
    "            Box([Label(value = 'Project Name'),                          self.A_ta], layout=form_item_layout),\n",
    "            Box([Label(value = 'Model Type'),                            self.E_ta], layout=form_item_layout),\n",
    "            Box([Label(value = 'Color Mode'),                            self.F_ta], layout=form_item_layout),\n",
    "            Box([Label(value = 'Batch Size'),                            self.B_ta], layout=form_item_layout),\n",
    "            Box([Label(value = 'Image Size'),                            self.C_ta], layout=form_item_layout),\n",
    "            Box([Label(value = 'Alpha'),                                 self.D_ta], layout=form_item_layout),\n",
    "           \n",
    "            Box([Label(value = 'Epochs'),                                self.H_ta], layout=form_item_layout),\n",
    "            Box([Label(value = 'Learning Rate'),                         self.I_ta], layout=form_item_layout),\n",
    "            Box([Label(value = 'Switch Mode'),                           self.J_ta], layout=form_item_layout),\n",
    "            self.K_ta_box,\n",
    "            self.M_ta_box,\n",
    "            self.N_ta_box,\n",
    "            Box([Label(value = 'Start to Execute'),                      self.L_ta], layout=form_item_layout),\n",
    "        ]\n",
    "        \n",
    "        self.form_output_train_cmd = Box(form_train_items, layout=Layout(\n",
    "            display='flex',\n",
    "            flex_flow='column',\n",
    "            border='solid 1px lightblue',\n",
    "            align_items='stretch',\n",
    "            width='100%',\n",
    "        ))\n",
    "        \n",
    "        ### test ###\n",
    "        self.A_tt = widgets.Button(description='Setting', layout=Layout(width='30%', height='30px'), button_style='success')\n",
    "        self.C_tt = widgets.Button(description='Run', layout=Layout(width='30%', height='30px'), button_style='success')\n",
    "      \n",
    "        form_test_items = [ \n",
    "            Box([Label(value = 'The tflite test setting is derivative from train setting.')], layout=form_item_layout),\n",
    "            Box([Label(value = 'Choose the tflite file'), self.A_tt], layout=form_item_layout),\n",
    "            Box([Label(value = 'Start to Test'),          self.C_tt], layout=form_item_layout),\n",
    "        ]\n",
    "        \n",
    "        self.form_output_test_cmd = Box(form_test_items, layout=Layout(\n",
    "            display='flex',\n",
    "            flex_flow='column',\n",
    "            border='solid 3px lightgreen',\n",
    "            align_items='stretch',\n",
    "            width='50%',\n",
    "        ))\n",
    "        \n",
    "        ### convert model cpp ###\n",
    "        self.A_cm = widgets.Text(value='..\\workspace\\\\vww_v2_96_035\\\\tflite_model', placeholder='Type something', disabled=False)\n",
    "        self.B_cm = widgets.Text(value='vww_mobilenetv2_0.35_96_96_int8quant.tflite', placeholder='Type something', disabled=False)\n",
    "        self.C_cm = widgets.Text(value='..\\workspace\\\\vww_v2_96_035\\\\tflite_model\\\\c', placeholder='Type something', disabled=False)\n",
    "        self.E_cm = widgets.Button(description='Setting', layout=Layout(width='30%', height='30px'), button_style='success')\n",
    "        self.D_cm = widgets.Button(description='Run', layout=Layout(width='30%', height='30px'), button_style='success')\n",
    "        self.G_cm = widgets.Checkbox(value=False, disabled=False, indent=False)\n",
    "      \n",
    "        form_convert_items_paths =  [\n",
    "            Box([Label(value = 'Vela Compiler'),          self.G_cm], layout=form_item_layout),\n",
    "            Box([Label(value = 'Choose the tflite file'), self.E_cm], layout=form_item_layout),\n",
    "            Box([Label(value = 'Model Src Dir'),          self.A_cm], layout=form_item_layout),\n",
    "            Box([Label(value = 'Model Src File'),         self.B_cm], layout=form_item_layout),\n",
    "            Box([Label(value = 'Gen Src Dir'),            self.C_cm], layout=form_item_layout)\n",
    "        ]\n",
    "        \n",
    "        form_convert_items = [\n",
    "            Box(form_convert_items_paths, layout=Layout(\n",
    "            display='flex',\n",
    "            flex_flow='column',\n",
    "            justify_content ='center',    \n",
    "            border='dotted 3px lightblue',\n",
    "            align_items='stretch',\n",
    "            width='70%')),\n",
    "            Box([Label(value = 'Convert to cpp & Vela'), self.D_cm], layout=form_item_layout),\n",
    "        ]\n",
    "        \n",
    "        self.form_output_convert_cmd = Box(form_convert_items, layout=Layout(\n",
    "            display='flex',\n",
    "            flex_flow='column',\n",
    "            justify_content ='center',\n",
    "            border='solid 3px lightgreen',\n",
    "            align_items='stretch',\n",
    "            width='70%',\n",
    "        ))\n",
    "\n",
    "#------------------#\n",
    "# help functions section\n",
    "#------------------#            \n",
    "    def move_allfiles(self, src_folder, dst_folder):\n",
    "        copy_num = 0\n",
    "        \n",
    "        files = os.listdir(src_folder)\n",
    "        for f in files:\n",
    "            fullpath = os.path.join(src_folder, f)\n",
    "            if os.path.isdir(fullpath):  #copy whole folder\n",
    "                shutil.move(fullpath, dst_folder)\n",
    "                print(\"Copy finish: {}\".format(f))\n",
    "    \n",
    "    def show_headline(self, output):\n",
    "        html0= widgets.HTML(value = f\"<b><font color='lightblue'><font size=4>{output}</b>\")\n",
    "        display(html0)\n",
    "        \n",
    "#------------------#\n",
    "# Show main widgets which combine all widgets.\n",
    "#------------------#    \n",
    "    def show_main(self):   \n",
    "        \n",
    "        intro_text = 'Please Choose the setting of data prepare & train'\n",
    "        htmlWidget = widgets.HTML(value = f\"<b><font color='lightgreen'><font size=6>{intro_text}</b>\")\n",
    "        display(htmlWidget)\n",
    "        \n",
    "        #Create an accordion and put the 2 boxes\n",
    "        accordion = widgets.Accordion(children=[self.form_data_prepare_cmd,\n",
    "                                                self.form_output_train_cmd,\n",
    "                                                ]).add_class(\"parentstyle\")\n",
    "        display(HTML(\"<style>.parentstyle > .p-Accordion-child > .p-Collapse-header{background-color:green}</style>\"))\n",
    "        accordion.set_title(0, 'COCO Dataset Prepare')\n",
    "        accordion.set_title(1, 'Configure the Training')\n",
    "        \n",
    "        # Create a box combining with 2 elements\n",
    "        box_data_train = Box([accordion], layout=Layout(\n",
    "            display='flex',\n",
    "            flex_flow='column',\n",
    "            border='solid 3px lightgreen',\n",
    "            align_items='stretch',\n",
    "            width='50%',\n",
    "        ))\n",
    "        \n",
    "        #Create a tab and put the 2 boxes\n",
    "        tab = widgets.Tab(children=[box_data_train, self.form_output_test_cmd, self.form_output_convert_cmd]).add_class(\"parentstyle\")\n",
    "        tab_contents = ['Train', 'Test', 'Deployment']\n",
    "        tab.titles = tab_contents\n",
    "       \n",
    "        \n",
    "        #Add a custom style tag to the notebook, you can use dev tool to inspect the class names\n",
    "        #display(HTML(\"<style>.parentstyle > .p-Accordion-child > .p-Collapse-header{background-color:green}</style>\"))\n",
    "        #accordion.set_title(0, 'Configure the Training')\n",
    "        \n",
    "        output_widgets = widgets.Output(layout=Layout(border = '1px solid green'))\n",
    "        \n",
    "        def act_para(A_dp, B_dp, C_dp, D_dp, E_dp, F_dp,\n",
    "                     A_ta, B_ta, C_ta, D_ta, E_ta, F_ta, \n",
    "                     H_ta, I_ta, J_ta, K_ta, M_ta, N_ta,\n",
    "                     A_cm, B_cm, C_cm, G_cm):\n",
    "            \n",
    "            # If any value is changed, clear the widgets\n",
    "            with output_widgets:\n",
    "                output_widgets.clear_output()\n",
    "                \n",
    "            if F_ta.count('rgb'):\n",
    "                self.K_ta.layout.visibility = 'visible'\n",
    "                self.fine_tune_LA.layout.visibility = 'visible'\n",
    "                self.M_ta.layout.visibility = 'visible'\n",
    "                self.fine_tune_LB.layout.visibility = 'visible'\n",
    "                self.N_ta.layout.visibility = 'visible'\n",
    "                self.fine_tune_LC.layout.visibility = 'visible'\n",
    "            else:\n",
    "                self.K_ta.layout.visibility = 'hidden'\n",
    "                self.fine_tune_LA.layout.visibility = 'hidden'\n",
    "                self.M_ta.layout.visibility = 'hidden'\n",
    "                self.fine_tune_LB.layout.visibility = 'hidden'\n",
    "                self.N_ta.layout.visibility = 'hidden'\n",
    "                self.fine_tune_LC.layout.visibility = 'hidden'\n",
    "        \n",
    "#------------------#\n",
    "# widgets.Accordion's interactive input with action function `act_para()`\n",
    "#------------------#\n",
    "        out_inter = widgets.interactive_output(act_para, {'A_dp': self.A_dp, 'B_dp': self.B_dp, 'C_dp': self.C_dp,\n",
    "                                                          'D_dp': self.D_dp, 'E_dp': self.E_dp, 'F_dp': self.F_dp,\n",
    "                                                          'A_ta': self.A_ta, 'B_ta': self.B_ta, 'C_ta': self.C_ta,\n",
    "                                                          'D_ta': self.D_ta, 'E_ta': self.E_ta, 'F_ta': self.F_ta,\n",
    "                                                          'H_ta': self.H_ta, 'I_ta': self.I_ta,\n",
    "                                                          'J_ta': self.J_ta, 'K_ta': self.K_ta, 'M_ta': self.M_ta,\n",
    "                                                          'N_ta': self.N_ta,\n",
    "                                                          'A_cm': self.A_cm, 'B_cm': self.B_cm, 'C_cm': self.C_cm,\n",
    "                                                          'G_cm': self.G_cm\n",
    "                                                          })\n",
    "        display(tab, out_inter)\n",
    "        display(output_widgets)\n",
    "        \n",
    "#------------------#\n",
    "# buttoms interactive sections\n",
    "#------------------#\n",
    "\n",
    "\n",
    "        def on_button_clicked_dataprepare(b):\n",
    "                with output_widgets:\n",
    "                    clear_output()\n",
    "                    print(\"Coco VWW dataprepare. . .\")\n",
    "                    self.run_coco_dataprepare()       \n",
    "        self.G_dp.on_click(on_button_clicked_dataprepare)\n",
    "\n",
    "        def on_button_clicked_train(b):\n",
    "                with output_widgets:\n",
    "                    clear_output()\n",
    "                    print(\"Train. . .\")\n",
    "                    self.run_train()       \n",
    "        self.L_ta.on_click(on_button_clicked_train)\n",
    "        \n",
    "        def on_button_clicked_choose_tflite(b):\n",
    "                with output_widgets:\n",
    "                    clear_output()\n",
    "                    self.choose_tflite()       \n",
    "        self.E_cm.on_click(on_button_clicked_choose_tflite)\n",
    "        \n",
    "        def on_button_clicked_cpp(b):\n",
    "                with output_widgets:\n",
    "                    clear_output()\n",
    "                    print(\"Convert to cpp & Vela. . .\")\n",
    "                    self.convert_tflu()       \n",
    "        self.D_cm.on_click(on_button_clicked_cpp)\n",
    "        \n",
    "        def on_button_clicked_choose_tflite_test(b):\n",
    "                with output_widgets:\n",
    "                    clear_output()\n",
    "                    self.choose_tflite()       \n",
    "        self.A_tt.on_click(on_button_clicked_choose_tflite_test)\n",
    "        \n",
    "        def on_button_clicked_test(b):\n",
    "            with output_widgets:\n",
    "                clear_output()\n",
    "                self.run_test_tflite()           \n",
    "        self.C_tt.on_click(on_button_clicked_test)\n",
    "\n",
    "#------------------#\n",
    "# execute functions sections, handle all the interactive events\n",
    "#------------------#        \n",
    "    def run_coco_dataprepare(self):\n",
    "        \n",
    "        %run create_coco_vww_tf_record.py --train_image_dir $self.A_dp.value --val_image_dir $self.B_dp.value \\\n",
    "        --train_annotations_file $self.C_dp.value --val_annotations_file $self.D_dp.value \\\n",
    "        --object_name $self.F_dp.value --output_dir $self.E_dp.value \n",
    "\n",
    "    def choose_tflite(self):\n",
    "        \n",
    "        path_ftflite = os.path.join(os.getcwd(), \"workspace\")\n",
    "        f_tflite = FileChooser(path_ftflite)\n",
    "        # Restrict navigation to /Users\n",
    "        f_tflite.sandbox_path = os.getcwd()\n",
    "        f_tflite.filter_pattern = ['*.tflite']\n",
    "        f_tflite.title = f\"<b><font color='lightblue'><font size=4>Choose the Tflite for Converting.</b>\"\n",
    "        display(f_tflite)\n",
    "        \n",
    "        def act_test():\n",
    "            self.tflite_file_loc = f_tflite.selected\n",
    "            work_dir_name = os.getcwd().split(\"\\\\\")[-1]\n",
    "            m_src_dir = r\"..\" + f_tflite.selected_path.split(work_dir_name)[-1]\n",
    "            m_src_tflite  = f_tflite.selected.split(\"\\\\\")[-1]\n",
    "            print(\"The chosen dir: {}\".format(m_src_dir))\n",
    "            print(\"The chosen tflite: {}\".format(m_src_tflite))\n",
    "            self.A_cm.value = m_src_dir\n",
    "            self.B_cm.value = m_src_tflite\n",
    "            if self.G_cm.value:\n",
    "                self.C_cm.value = os.path.join(m_src_dir, \"vela\")\n",
    "            else:\n",
    "                self.C_cm.value = os.path.join(m_src_dir, \"c\")\n",
    "            \n",
    "            \n",
    "            print(\"Finish!\")\n",
    "        evt = interact_manual(act_test)\n",
    "        evt.widget.children[0].description = 'Set this file'  #because there are 3 parameter of the evt\n",
    "        evt.widget.children[0].button_style = 'primary'\n",
    "        \n",
    "    def run_train(self):\n",
    "        sw_num = int(self.J_ta.value.split(\":\")[0])\n",
    "        dataset_name = self.E_dp.value.split(\"\\\\\")[-1]\n",
    "        \n",
    "        %run train_vww.py --proj_name $self.A_ta.value --dataset $dataset_name \\\n",
    "        --model-prefix $self.E_ta.value --COLOR_MODE $self.F_ta.value --batch-size $self.B_ta.value \\\n",
    "        --input-height $self.C_ta.value --input-width $self.C_ta.value --alpha $self.D_ta.value \\\n",
    "        --epochs $self.H_ta.value --learning-rate $self.I_ta.value --switch_mode $sw_num\\\n",
    "        --fine_tune_at $self.K_ta.value  --epochs_fine $self.M_ta.value --learning-rate_fine $self.N_ta.value\n",
    "        \n",
    "        # Save the cmd's record.\n",
    "        path_CMDrecord = os.path.join(os.getcwd(), \"workspace\", self.A_ta.value, \"train_cmd_record.txt\")\n",
    "        with open(path_CMDrecord, \"w\") as file1:\n",
    "            open_dir = \"cd {} \\n\".format(os.getcwd())\n",
    "            cmd = \"python train_vww.py --proj_name {} --dataset {} --model-prefix {} --COLOR_MODE {} --batch-size {} \\\n",
    "--input-height {} --input-width {} --alpha {} --epochs {} --learning-rate {} --switch_mode {} \\\n",
    "--fine_tune_at {} --epochs_fine {} --learning-rate_fine {}\".format(self.A_ta.value, dataset_name, self.E_ta.value,\n",
    "                    self.F_ta.value, self.B_ta.value, self.C_ta.value, self.C_ta.value, self.D_ta.value,\n",
    "                    self.H_ta.value, self.I_ta.value, sw_num, self.K_ta.value, self.M_ta.value, self.N_ta.value)\n",
    "            file1.writelines([open_dir, cmd])\n",
    "        \n",
    "        print(\"Finish Train!!\")\n",
    "        \n",
    "    def run_test_tflite(self):\n",
    "        dataset_name = self.E_dp.value.split(\"\\\\\")[-1]\n",
    "        print(\"The tflite file: {} The testing validation dataset: {}\".format(self.tflite_file_loc, self.E_dp.value))\n",
    "        \n",
    "        %run train_vww.py --proj_name $self.A_ta.value --dataset $dataset_name \\\n",
    "        --model-prefix $self.E_ta.value --COLOR_MODE $self.F_ta.value --batch-size $self.B_ta.value \\\n",
    "        --input-height $self.C_ta.value --input-width $self.C_ta.value --alpha $self.D_ta.value \\\n",
    "        --epochs $self.H_ta.value --learning-rate $self.I_ta.value --switch_mode $3\\\n",
    "        --fine_tune_at $self.K_ta.value  --epochs_fine $self.M_ta.value --learning-rate_fine $self.N_ta.value\\\n",
    "        --TFLITE_F $self.tflite_file_loc\n",
    "        \n",
    "        print(\"Finish !!\")\n",
    "        \n",
    "    def convert_tflu(self):\n",
    "       \n",
    "        print(\"Create\")\n",
    "        %run exebat.py --SRC_DIR $self.A_cm.value --SRC_FILE $self.B_cm.value --GEN_DIR $self.C_cm.value --VELA_EN $self.G_cm.value\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc619de2-0d01-4133-a64c-168041666d5e",
   "metadata": {},
   "source": [
    "# Run Section\n",
    "---\n",
    "- The detail description of all the parameters and each step meaning is here [meaning](#id-train_evl_monitor)\n",
    "- In this notebook step, you have alreay finish the dataset prepared. If not, please go to `image_dataset\\create_data.ipynb`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c6b58cfe-a753-4869-a3fb-8a3cc9b76bcb",
   "metadata": {},
   "outputs": [
    {
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       "model_id": "7eb235061e2948a0b025b5b0d8c4becd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HTML(value=\"<b><font color='lightgreen'><font size=6>Please Choose the setting of data prepare & train</b>\")"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>.parentstyle > .p-Accordion-child > .p-Collapse-header{background-color:green}</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "773dea2d60da4d98b782a7d2db0c40a4",
       "version_major": 2,
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      },
      "text/plain": [
       "Tab(children=(Box(children=(Accordion(children=(Box(children=(Box(children=(Label(value='Train Image Dir'), Te…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "19eeb29521c3496eb7839afe7f684c82",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
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      },
      "text/plain": [
       "Output(layout=Layout(border_bottom='1px solid green', border_left='1px solid green', border_right='1px solid g…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "act = train_config_and_cmds_widgets()\n",
    "act.show_main()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef3b258a-68cf-4c58-829f-ad94ed040cf2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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