Diff of /No1-boxplot.ipynb [000000] .. [70e190]

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{
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 "cells": [
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  {
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   "cell_type": "code",
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   "execution_count": 1,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "import plotly.express as px\n",
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    "import matplotlib.pyplot as plt\n",
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    "import pandas as pd"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 4,
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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "def boxplot(output_name, network, y_min=None, y_max=None):\n",
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    "    df_dice = pd.read_csv(f\"outputs/{network}/{output_name}/infer_dice_class.csv\")\n",
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    "    df_iou  = pd.read_csv(f\"outputs/{network}/{output_name}/infer_iou_class.csv\")\n",
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    "\n",
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    "    df_dice['type'] = 'dice'\n",
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    "    df_iou['type'] = 'iou'\n",
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    "\n",
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    "    df_combined = pd.concat([df_dice, df_iou])\n",
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    "    df_combined.reset_index(drop=True, inplace=True)\n",
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    "    df_final = pd.melt(df_combined, id_vars=['type'], var_name='classes', value_name='scores')\n",
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    "    df_final.sort_values(['type', 'classes'], inplace=True)\n",
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    "    df_final.reset_index(drop=True, inplace=True)\n",
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    "\n",
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    "    fig = px.box(df_final, x=\"classes\", y=\"scores\", color=\"type\")\n",
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    "    fig.update_traces(quartilemethod=\"exclusive\")\n",
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    "    fig.update_layout(\n",
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    "        width=1000, \n",
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    "        height=500,\n",
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    "        font=dict(\n",
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    "            size=18 \n",
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    "        )\n",
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    "    )\n",
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    "    if y_min is not None and y_max is not None:\n",
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    "        fig.update_yaxes(range=[y_min, y_max])\n",
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    "    fig.show()"
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   ]
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  },
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  {
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   "cell_type": "markdown",
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   "metadata": {},
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   "source": [
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    "### VHSCDD $(256 \\times 256)$"
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   ]
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  },
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  {
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   "cell_type": "code",
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   "execution_count": 8,
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    "### ImageCHD $(256 \\times 256)$"
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   "cell_type": "code",
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