Datasets/create_meta.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import sys\n",
    "import os\n",
    "sys.path.append('/ubc/ece/home/ra/grads/siyi/Research/skin_lesion_segmentation/MDViT/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2594\n"
     ]
    }
   ],
   "source": [
    "'''isic2018'''\n",
    "# Note ISIC original meta file is in this code reporsitory, MDViT/Datasets/isic2018_id.csv\n",
    "data_folder = '/bigdata/siyiplace/data/skin_lesion'\n",
    "isic2018_meta = 'isic2018_id.csv'\n",
    "df = pd.read_csv(isic2018_meta)\n",
    "print(len(df))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "diagnosis_list = []\n",
    "ID_list = []\n",
    "for i in range(len(df)):\n",
    "    diagnosis_list.append(df.iloc[i]['Class'].capitalize())\n",
    "    ID_list.append(df.iloc[i]['ID'].split('_')[1])\n",
    "df['diagnosis'] = diagnosis_list\n",
    "df['dataset'] = ['isic2018']*len(df)\n",
    "df['ID'] = ID_list\n",
    "df['diagnosis_id'] = df['diagnosis'].astype('category').cat.codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Class</th>\n",
       "      <th>Split</th>\n",
       "      <th>W</th>\n",
       "      <th>H</th>\n",
       "      <th>pigment_network</th>\n",
       "      <th>negative_network</th>\n",
       "      <th>streaks</th>\n",
       "      <th>milia_like_cyst</th>\n",
       "      <th>globules</th>\n",
       "      <th>all</th>\n",
       "      <th>diagnosis</th>\n",
       "      <th>dataset</th>\n",
       "      <th>diagnosis_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <th>0</th>\n",
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       "      <td>melanoma</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Melanoma</td>\n",
       "      <td>isic2018</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
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       "    <tr>\n",
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       "      <td>isic2018</td>\n",
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       "<p>2594 rows × 14 columns</p>\n",
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      "text/plain": [
       "           ID                 Class  Split     W     H  pigment_network  \\\n",
       "0     0000164              melanoma  train   638   959                1   \n",
       "1     0001148              melanoma  train  2304  3072                1   \n",
       "2     0013258              melanoma  train  2000  3008                1   \n",
       "3     0014189              melanoma  train  2848  4288                1   \n",
       "4     0013457              melanoma  train  2848  4288                0   \n",
       "...       ...                   ...    ...   ...   ...              ...   \n",
       "2589  0014503  seborrheic_keratosis   test  2848  4288                0   \n",
       "2590  0012358  seborrheic_keratosis   test  2000  3008                0   \n",
       "2591  0013333  seborrheic_keratosis   test  2848  4288                0   \n",
       "2592  0012693  seborrheic_keratosis   test  2000  3008                0   \n",
       "2593  0014580  seborrheic_keratosis   test  1936  2592                0   \n",
       "\n",
       "      negative_network  streaks  milia_like_cyst  globules  all  \\\n",
       "0                    0        0                0         0    1   \n",
       "1                    0        0                0         0    1   \n",
       "2                    0        0                0         0    1   \n",
       "3                    0        0                1         0    2   \n",
       "4                    0        0                1         0    1   \n",
       "...                ...      ...              ...       ...  ...   \n",
       "2589                 0        0                1         0    1   \n",
       "2590                 0        0                0         0    0   \n",
       "2591                 0        0                0         0    0   \n",
       "2592                 0        0                0         0    0   \n",
       "2593                 0        0                1         0    1   \n",
       "\n",
       "                 diagnosis   dataset  diagnosis_id  \n",
       "0                 Melanoma  isic2018             0  \n",
       "1                 Melanoma  isic2018             0  \n",
       "2                 Melanoma  isic2018             0  \n",
       "3                 Melanoma  isic2018             0  \n",
       "4                 Melanoma  isic2018             0  \n",
       "...                    ...       ...           ...  \n",
       "2589  Seborrheic_keratosis  isic2018             2  \n",
       "2590  Seborrheic_keratosis  isic2018             2  \n",
       "2591  Seborrheic_keratosis  isic2018             2  \n",
       "2592  Seborrheic_keratosis  isic2018             2  \n",
       "2593  Seborrheic_keratosis  isic2018             2  \n",
       "\n",
       "[2594 rows x 14 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(data_folder+'/isic2018/meta_isic2018.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "200\n"
     ]
    }
   ],
   "source": [
    "'''PH2'''\n",
    "data_folder = '/bigdata/siyiplace/data/skin_lesion'\n",
    "PH2_meta = data_folder+'/PH2_rawdata/PH2Dataset/PH2_dataset.xlsx'\n",
    "df = pd.read_excel(PH2_meta, skiprows=range(12))\n",
    "print(len(df))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "diagnosis_list = []\n",
    "for i in range(len(df)):\n",
    "    row = df.iloc[i]\n",
    "    for diag_name in ['Common Nevus', 'Atypical Nevus', 'Melanoma']:\n",
    "        if row[diag_name] == 'X':\n",
    "            diagnosis_list.append(diag_name)\n",
    "            break\n",
    "    else:\n",
    "        print(i)\n",
    "df['diagnosis'] = diagnosis_list\n",
    "df['dataset'] = ['PH2']*len(df)\n",
    "df['ID']=df['Image Name']\n",
    "df['diagnosis_id'] = df['diagnosis'].astype('category').cat.codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
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       "      <th>Histological Diagnosis</th>\n",
       "      <th>Common Nevus</th>\n",
       "      <th>Atypical Nevus</th>\n",
       "      <th>Melanoma</th>\n",
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       "      <td>X</td>\n",
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       "      <td>Common Nevus</td>\n",
       "      <td>PH2</td>\n",
       "      <td>IMD016</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>IMD022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>Common Nevus</td>\n",
       "      <td>PH2</td>\n",
       "      <td>IMD024</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>IMD424</td>\n",
       "      <td>Melanoma</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X</td>\n",
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       "      <td>A</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X</td>\n",
       "      <td>X</td>\n",
       "      <td>X</td>\n",
       "      <td>X</td>\n",
       "      <td>Melanoma</td>\n",
       "      <td>PH2</td>\n",
       "      <td>IMD424</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>IMD425</td>\n",
       "      <td>Melanoma</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X</td>\n",
       "      <td>2</td>\n",
       "      <td>AT</td>\n",
       "      <td>AT</td>\n",
       "      <td>A</td>\n",
       "      <td>P</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X</td>\n",
       "      <td>X</td>\n",
       "      <td>X</td>\n",
       "      <td>X</td>\n",
       "      <td>Melanoma</td>\n",
       "      <td>PH2</td>\n",
       "      <td>IMD425</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>IMD426</td>\n",
       "      <td>Melanoma</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X</td>\n",
       "      <td>2</td>\n",
       "      <td>AT</td>\n",
       "      <td>A</td>\n",
       "      <td>A</td>\n",
       "      <td>P</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X</td>\n",
       "      <td>X</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Melanoma</td>\n",
       "      <td>PH2</td>\n",
       "      <td>IMD426</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>IMD429</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X</td>\n",
       "      <td>0</td>\n",
       "      <td>AT</td>\n",
       "      <td>A</td>\n",
       "      <td>P</td>\n",
       "      <td>A</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X</td>\n",
       "      <td>X</td>\n",
       "      <td>X</td>\n",
       "      <td>X</td>\n",
       "      <td>Melanoma</td>\n",
       "      <td>PH2</td>\n",
       "      <td>IMD429</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>IMD435</td>\n",
       "      <td>Lentigo Maligna</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X</td>\n",
       "      <td>2</td>\n",
       "      <td>AT</td>\n",
       "      <td>A</td>\n",
       "      <td>A</td>\n",
       "      <td>A</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>X</td>\n",
       "      <td>X</td>\n",
       "      <td>X</td>\n",
       "      <td>X</td>\n",
       "      <td>Melanoma</td>\n",
       "      <td>PH2</td>\n",
       "      <td>IMD435</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Image Name Histological Diagnosis Common Nevus Atypical Nevus Melanoma  \\\n",
       "0       IMD003                    NaN            X            NaN      NaN   \n",
       "1       IMD009                    NaN            X            NaN      NaN   \n",
       "2       IMD016                    NaN            X            NaN      NaN   \n",
       "3       IMD022                    NaN            X            NaN      NaN   \n",
       "4       IMD024                    NaN            X            NaN      NaN   \n",
       "..         ...                    ...          ...            ...      ...   \n",
       "195     IMD424               Melanoma          NaN            NaN        X   \n",
       "196     IMD425               Melanoma          NaN            NaN        X   \n",
       "197     IMD426               Melanoma          NaN            NaN        X   \n",
       "198     IMD429                    NaN          NaN            NaN        X   \n",
       "199     IMD435        Lentigo Maligna          NaN            NaN        X   \n",
       "\n",
       "     Asymmetry\\n(0/1/2) Pigment Network\\n(AT/T) Dots/Globules\\n(A/AT/T)  \\\n",
       "0                     0                       T                       A   \n",
       "1                     0                       T                       A   \n",
       "2                     0                       T                       T   \n",
       "3                     0                       T                       A   \n",
       "4                     0                       T                       A   \n",
       "..                  ...                     ...                     ...   \n",
       "195                   2                      AT                      AT   \n",
       "196                   2                      AT                      AT   \n",
       "197                   2                      AT                       A   \n",
       "198                   0                      AT                       A   \n",
       "199                   2                      AT                       A   \n",
       "\n",
       "    Streaks\\n(A/P) Regression Areas\\n(A/P)  ... White  Red Light-Brown  \\\n",
       "0                A                       A  ...   NaN  NaN         NaN   \n",
       "1                A                       A  ...   NaN  NaN           X   \n",
       "2                A                       A  ...   NaN  NaN           X   \n",
       "3                A                       A  ...   NaN  NaN           X   \n",
       "4                A                       A  ...   NaN  NaN           X   \n",
       "..             ...                     ...  ...   ...  ...         ...   \n",
       "195              P                       A  ...   NaN  NaN           X   \n",
       "196              A                       P  ...   NaN  NaN           X   \n",
       "197              A                       P  ...   NaN  NaN           X   \n",
       "198              P                       A  ...   NaN  NaN           X   \n",
       "199              A                       A  ...   NaN  NaN           X   \n",
       "\n",
       "    Dark-Brown Blue-Gray Black     diagnosis dataset      ID diagnosis_id  \n",
       "0            X       NaN   NaN  Common Nevus     PH2  IMD003            1  \n",
       "1          NaN       NaN   NaN  Common Nevus     PH2  IMD009            1  \n",
       "2            X       NaN   NaN  Common Nevus     PH2  IMD016            1  \n",
       "3          NaN       NaN   NaN  Common Nevus     PH2  IMD022            1  \n",
       "4            X       NaN   NaN  Common Nevus     PH2  IMD024            1  \n",
       "..         ...       ...   ...           ...     ...     ...          ...  \n",
       "195          X         X     X      Melanoma     PH2  IMD424            2  \n",
       "196          X         X     X      Melanoma     PH2  IMD425            2  \n",
       "197          X       NaN   NaN      Melanoma     PH2  IMD426            2  \n",
       "198          X         X     X      Melanoma     PH2  IMD429            2  \n",
       "199          X         X     X      Melanoma     PH2  IMD435            2  \n",
       "\n",
       "[200 rows x 21 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(data_folder+'/PH2/meta_PH2.csv',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1212\n"
     ]
    }
   ],
   "source": [
    "'''DMF'''\n",
    "data_folder = '/bigdata/siyiplace/data/skin_lesion'\n",
    "DMF_meta = data_folder+'/DMF_origin/meta.csv'\n",
    "df = pd.read_csv(DMF_meta)\n",
    "print(len(df))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>path</th>\n",
       "      <th>lesion_id</th>\n",
       "      <th>ori_dx</th>\n",
       "      <th>dx</th>\n",
       "      <th>dx_idx</th>\n",
       "      <th>dom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>images/D204a/D204a.png</td>\n",
       "      <td>1</td>\n",
       "      <td>BCC</td>\n",
       "      <td>Basal cell carcinoma</td>\n",
       "      <td>2</td>\n",
       "      <td>dmf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>images/D226b/D226b.png</td>\n",
       "      <td>3</td>\n",
       "      <td>ML</td>\n",
       "      <td>Melanocytic nevi</td>\n",
       "      <td>1</td>\n",
       "      <td>dmf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>images/D226c/D226c.png</td>\n",
       "      <td>4</td>\n",
       "      <td>ML</td>\n",
       "      <td>Melanocytic nevi</td>\n",
       "      <td>1</td>\n",
       "      <td>dmf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>images/D227/D227.png</td>\n",
       "      <td>5</td>\n",
       "      <td>ML</td>\n",
       "      <td>Melanocytic nevi</td>\n",
       "      <td>1</td>\n",
       "      <td>dmf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>images/D231/D231.png</td>\n",
       "      <td>6</td>\n",
       "      <td>AK</td>\n",
       "      <td>Actinic keratoses</td>\n",
       "      <td>3</td>\n",
       "      <td>dmf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1207</th>\n",
       "      <td>images/D649a/D649a.png</td>\n",
       "      <td>1296</td>\n",
       "      <td>IEC</td>\n",
       "      <td>Actinic keratoses</td>\n",
       "      <td>3</td>\n",
       "      <td>dmf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1208</th>\n",
       "      <td>images/G40a/G40a.png</td>\n",
       "      <td>1297</td>\n",
       "      <td>IEC</td>\n",
       "      <td>Actinic keratoses</td>\n",
       "      <td>3</td>\n",
       "      <td>dmf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1209</th>\n",
       "      <td>images/P100/P100.png</td>\n",
       "      <td>1298</td>\n",
       "      <td>IEC</td>\n",
       "      <td>Actinic keratoses</td>\n",
       "      <td>3</td>\n",
       "      <td>dmf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1210</th>\n",
       "      <td>images/T239/T239.png</td>\n",
       "      <td>1299</td>\n",
       "      <td>IEC</td>\n",
       "      <td>Actinic keratoses</td>\n",
       "      <td>3</td>\n",
       "      <td>dmf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1211</th>\n",
       "      <td>images/T39/T39.png</td>\n",
       "      <td>1300</td>\n",
       "      <td>IEC</td>\n",
       "      <td>Actinic keratoses</td>\n",
       "      <td>3</td>\n",
       "      <td>dmf</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1212 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        path  lesion_id ori_dx                    dx  dx_idx  \\\n",
       "0     images/D204a/D204a.png          1    BCC  Basal cell carcinoma       2   \n",
       "1     images/D226b/D226b.png          3     ML      Melanocytic nevi       1   \n",
       "2     images/D226c/D226c.png          4     ML      Melanocytic nevi       1   \n",
       "3       images/D227/D227.png          5     ML      Melanocytic nevi       1   \n",
       "4       images/D231/D231.png          6     AK     Actinic keratoses       3   \n",
       "...                      ...        ...    ...                   ...     ...   \n",
       "1207  images/D649a/D649a.png       1296    IEC     Actinic keratoses       3   \n",
       "1208    images/G40a/G40a.png       1297    IEC     Actinic keratoses       3   \n",
       "1209    images/P100/P100.png       1298    IEC     Actinic keratoses       3   \n",
       "1210    images/T239/T239.png       1299    IEC     Actinic keratoses       3   \n",
       "1211      images/T39/T39.png       1300    IEC     Actinic keratoses       3   \n",
       "\n",
       "      dom  \n",
       "0     dmf  \n",
       "1     dmf  \n",
       "2     dmf  \n",
       "3     dmf  \n",
       "4     dmf  \n",
       "...   ...  \n",
       "1207  dmf  \n",
       "1208  dmf  \n",
       "1209  dmf  \n",
       "1210  dmf  \n",
       "1211  dmf  \n",
       "\n",
       "[1212 rows x 6 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['dataset']=['DMF']*len(df)\n",
    "diagnosis_list = []\n",
    "ID_list = []\n",
    "for i in range(len(df)):\n",
    "    path = df.iloc[i]['path']\n",
    "    ID_list.append(path.split('/')[1])\n",
    "    diagnosis_list.append(df.iloc[i]['dx'].title())\n",
    "df['ID']=ID_list\n",
    "df['diagnosis'] = diagnosis_list\n",
    "df['diagnosis_id'] = df['diagnosis'].astype('category').cat.codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>path</th>\n",
       "      <th>lesion_id</th>\n",
       "      <th>ori_dx</th>\n",
       "      <th>dx</th>\n",
       "      <th>dx_idx</th>\n",
       "      <th>dom</th>\n",
       "      <th>dataset</th>\n",
       "      <th>ID</th>\n",
       "      <th>diagnosis</th>\n",
       "      <th>diagnosis_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>images/D204a/D204a.png</td>\n",
       "      <td>1</td>\n",
       "      <td>BCC</td>\n",
       "      <td>Basal cell carcinoma</td>\n",
       "      <td>2</td>\n",
       "      <td>dmf</td>\n",
       "      <td>DMF</td>\n",
       "      <td>D204a</td>\n",
       "      <td>Basal Cell Carcinoma</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>images/D226b/D226b.png</td>\n",
       "      <td>3</td>\n",
       "      <td>ML</td>\n",
       "      <td>Melanocytic nevi</td>\n",
       "      <td>1</td>\n",
       "      <td>dmf</td>\n",
       "      <td>DMF</td>\n",
       "      <td>D226b</td>\n",
       "      <td>Melanocytic Nevi</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>images/D226c/D226c.png</td>\n",
       "      <td>4</td>\n",
       "      <td>ML</td>\n",
       "      <td>Melanocytic nevi</td>\n",
       "      <td>1</td>\n",
       "      <td>dmf</td>\n",
       "      <td>DMF</td>\n",
       "      <td>D226c</td>\n",
       "      <td>Melanocytic Nevi</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>images/D227/D227.png</td>\n",
       "      <td>5</td>\n",
       "      <td>ML</td>\n",
       "      <td>Melanocytic nevi</td>\n",
       "      <td>1</td>\n",
       "      <td>dmf</td>\n",
       "      <td>DMF</td>\n",
       "      <td>D227</td>\n",
       "      <td>Melanocytic Nevi</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>images/D231/D231.png</td>\n",
       "      <td>6</td>\n",
       "      <td>AK</td>\n",
       "      <td>Actinic keratoses</td>\n",
       "      <td>3</td>\n",
       "      <td>dmf</td>\n",
       "      <td>DMF</td>\n",
       "      <td>D231</td>\n",
       "      <td>Actinic Keratoses</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1207</th>\n",
       "      <td>images/D649a/D649a.png</td>\n",
       "      <td>1296</td>\n",
       "      <td>IEC</td>\n",
       "      <td>Actinic keratoses</td>\n",
       "      <td>3</td>\n",
       "      <td>dmf</td>\n",
       "      <td>DMF</td>\n",
       "      <td>D649a</td>\n",
       "      <td>Actinic Keratoses</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1208</th>\n",
       "      <td>images/G40a/G40a.png</td>\n",
       "      <td>1297</td>\n",
       "      <td>IEC</td>\n",
       "      <td>Actinic keratoses</td>\n",
       "      <td>3</td>\n",
       "      <td>dmf</td>\n",
       "      <td>DMF</td>\n",
       "      <td>G40a</td>\n",
       "      <td>Actinic Keratoses</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1209</th>\n",
       "      <td>images/P100/P100.png</td>\n",
       "      <td>1298</td>\n",
       "      <td>IEC</td>\n",
       "      <td>Actinic keratoses</td>\n",
       "      <td>3</td>\n",
       "      <td>dmf</td>\n",
       "      <td>DMF</td>\n",
       "      <td>P100</td>\n",
       "      <td>Actinic Keratoses</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1210</th>\n",
       "      <td>images/T239/T239.png</td>\n",
       "      <td>1299</td>\n",
       "      <td>IEC</td>\n",
       "      <td>Actinic keratoses</td>\n",
       "      <td>3</td>\n",
       "      <td>dmf</td>\n",
       "      <td>DMF</td>\n",
       "      <td>T239</td>\n",
       "      <td>Actinic Keratoses</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1211</th>\n",
       "      <td>images/T39/T39.png</td>\n",
       "      <td>1300</td>\n",
       "      <td>IEC</td>\n",
       "      <td>Actinic keratoses</td>\n",
       "      <td>3</td>\n",
       "      <td>dmf</td>\n",
       "      <td>DMF</td>\n",
       "      <td>T39</td>\n",
       "      <td>Actinic Keratoses</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1212 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        path  lesion_id ori_dx                    dx  dx_idx  \\\n",
       "0     images/D204a/D204a.png          1    BCC  Basal cell carcinoma       2   \n",
       "1     images/D226b/D226b.png          3     ML      Melanocytic nevi       1   \n",
       "2     images/D226c/D226c.png          4     ML      Melanocytic nevi       1   \n",
       "3       images/D227/D227.png          5     ML      Melanocytic nevi       1   \n",
       "4       images/D231/D231.png          6     AK     Actinic keratoses       3   \n",
       "...                      ...        ...    ...                   ...     ...   \n",
       "1207  images/D649a/D649a.png       1296    IEC     Actinic keratoses       3   \n",
       "1208    images/G40a/G40a.png       1297    IEC     Actinic keratoses       3   \n",
       "1209    images/P100/P100.png       1298    IEC     Actinic keratoses       3   \n",
       "1210    images/T239/T239.png       1299    IEC     Actinic keratoses       3   \n",
       "1211      images/T39/T39.png       1300    IEC     Actinic keratoses       3   \n",
       "\n",
       "      dom dataset     ID             diagnosis  diagnosis_id  \n",
       "0     dmf     DMF  D204a  Basal Cell Carcinoma             1  \n",
       "1     dmf     DMF  D226b      Melanocytic Nevi             4  \n",
       "2     dmf     DMF  D226c      Melanocytic Nevi             4  \n",
       "3     dmf     DMF   D227      Melanocytic Nevi             4  \n",
       "4     dmf     DMF   D231     Actinic Keratoses             0  \n",
       "...   ...     ...    ...                   ...           ...  \n",
       "1207  dmf     DMF  D649a     Actinic Keratoses             0  \n",
       "1208  dmf     DMF   G40a     Actinic Keratoses             0  \n",
       "1209  dmf     DMF   P100     Actinic Keratoses             0  \n",
       "1210  dmf     DMF   T239     Actinic Keratoses             0  \n",
       "1211  dmf     DMF    T39     Actinic Keratoses             0  \n",
       "\n",
       "[1212 rows x 10 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(data_folder+'/DMF/meta_DMF.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''SKD\n",
    "create meta file'''\n",
    "data_folder = '/bigdata/siyiplace/data/skin_lesion'\n",
    "melanoma_folder = data_folder+'/skin_cancer_detection_origin/skin_image_data_set-1/Skin Image Data Set-1/skin_data/melanoma'\n",
    "benign_folder = data_folder+'/skin_cancer_detection_origin/skin_image_data_set-2/Skin Image Data Set-2/skin_data/notmelanoma'\n",
    "image_name_list = []\n",
    "diagnosis_list = []\n",
    "\n",
    "for dataset_name in ['dermis', 'dermquest']:\n",
    "    path_list = os.listdir('{}/{}'.format(melanoma_folder, dataset_name))\n",
    "    for path in path_list:\n",
    "        if path[-4:] == '.jpg':\n",
    "            image_name = dataset_name+'_'+path[:-4]\n",
    "            image_name_list.append(image_name)\n",
    "\n",
    "diagnosis_list.extend(['Melanoma']*len(image_name_list))\n",
    "\n",
    "count = 0\n",
    "for dataset_name in ['dermis', 'dermquest']:\n",
    "    path_list = os.listdir('{}/{}'.format(benign_folder, dataset_name))\n",
    "\n",
    "    for path in path_list:\n",
    "        if path[-4:] == '.jpg':\n",
    "            image_name = dataset_name+'_'+path[:-4]\n",
    "            image_name_list.append(image_name)\n",
    "            count += 1\n",
    "\n",
    "diagnosis_list.extend(['Benign']*count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "206\n",
      "206\n"
     ]
    }
   ],
   "source": [
    "print(len(diagnosis_list))\n",
    "print(len(image_name_list))\n",
    "SKD_meta_path = data_folder+'/SKD/meta_SKD.csv'\n",
    "df = pd.DataFrame({\n",
    "    'dataset': ['SKD']*len(diagnosis_list),\n",
    "    'ID': image_name_list,\n",
    "    'diagnosis': diagnosis_list,\n",
    "})\n",
    "df.to_csv(SKD_meta_path, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "SKD_meta_path = data_folder+'/SKD/meta_SKD.csv'\n",
    "SKD_meta = pd.read_csv(SKD_meta_path)\n",
    "# SKD_meta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['diagnosis_id'] = df['diagnosis'].astype('category').cat.codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dataset</th>\n",
       "      <th>ID</th>\n",
       "      <th>diagnosis</th>\n",
       "      <th>diagnosis_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SKD</td>\n",
       "      <td>dermis_AMM1_orig</td>\n",
       "      <td>Melanoma</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SKD</td>\n",
       "      <td>dermis_LMM1_orig</td>\n",
       "      <td>Melanoma</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SKD</td>\n",
       "      <td>dermis_LMM2_orig</td>\n",
       "      <td>Melanoma</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SKD</td>\n",
       "      <td>dermis_LMM4_orig</td>\n",
       "      <td>Melanoma</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SKD</td>\n",
       "      <td>dermis_LMM5_orig</td>\n",
       "      <td>Melanoma</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>SKD</td>\n",
       "      <td>dermquest_D6_orig</td>\n",
       "      <td>Benign</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>SKD</td>\n",
       "      <td>dermquest_D8_2_orig</td>\n",
       "      <td>Benign</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>SKD</td>\n",
       "      <td>dermquest_D8_orig</td>\n",
       "      <td>Benign</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>SKD</td>\n",
       "      <td>dermquest_D9_2_orig</td>\n",
       "      <td>Benign</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>SKD</td>\n",
       "      <td>dermquest_D9_orig</td>\n",
       "      <td>Benign</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>206 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    dataset                   ID diagnosis  diagnosis_id\n",
       "0       SKD     dermis_AMM1_orig  Melanoma             1\n",
       "1       SKD     dermis_LMM1_orig  Melanoma             1\n",
       "2       SKD     dermis_LMM2_orig  Melanoma             1\n",
       "3       SKD     dermis_LMM4_orig  Melanoma             1\n",
       "4       SKD     dermis_LMM5_orig  Melanoma             1\n",
       "..      ...                  ...       ...           ...\n",
       "201     SKD    dermquest_D6_orig    Benign             0\n",
       "202     SKD  dermquest_D8_2_orig    Benign             0\n",
       "203     SKD    dermquest_D8_orig    Benign             0\n",
       "204     SKD  dermquest_D9_2_orig    Benign             0\n",
       "205     SKD    dermquest_D9_orig    Benign             0\n",
       "\n",
       "[206 rows x 4 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(SKD_meta_path, index=False)"
   ]
  }
 ],
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