preprocess-project-test-data.ipynb

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    "tags": []
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   "outputs": [],
   "source": [
    "!pip install --quiet git+https://github.com/ain3007-project/project-utils.git"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "53ea25c4",
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    "tags": []
   },
   "outputs": [],
   "source": [
    "import huggingface_hub as hfh\n",
    "import pandas as pd\n",
    "from project_utils.preprocessing import process\n",
    "from project_utils.plotting import plot_image_mask_by_path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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     "status": "completed"
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    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Token will not been saved to git credential helper. Pass `add_to_git_credential=True` if you want to set the git credential as well.\n",
      "Token is valid (permission: write).\n",
      "Your token has been saved to /root/.cache/huggingface/token\n",
      "Login successful\n"
     ]
    }
   ],
   "source": [
    "hfh.login(\"INSERT TOKEN HERE\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "hfh.utils.disable_progress_bars()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9011feb3",
   "metadata": {
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   "outputs": [],
   "source": [
    "external_test_repo_id = \"ain3007-project/raw-external-test-dataset\"\n",
    "internal_test_repo_id = \"ain3007-project/raw-internal-test-dataset\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e7a75a1f",
   "metadata": {
    "execution": {
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   },
   "outputs": [],
   "source": [
    "image_size = 512\n",
    "pad_images = True\n",
    "\n",
    "output_repo_id = f\"ain3007-project/test-dataset-thumbnails-{image_size}\"\n",
    "\n",
    "if pad_images:\n",
    "    output_repo_id += \"-padded\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2af99ba0",
   "metadata": {
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RepoUrl('https://huggingface.co/datasets/ain3007-project/test-dataset-thumbnails-512-padded', endpoint='https://huggingface.co', repo_type='dataset', repo_id='ain3007-project/test-dataset-thumbnails-512-padded')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hfh.create_repo(output_repo_id, private=True, repo_type=\"dataset\", exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "09fcc055",
   "metadata": {
    "execution": {
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     "exception": false,
     "start_time": "2024-01-06T22:32:46.022733",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[RepoFile(path='.gitattributes', size=5257, blob_id='9408dffb7f14703972c362793536d1d614974372', lfs=None, last_commit=None, security=None),\n",
       " RepoFile(path='breast__he__10068.ndpi', size=162377221, blob_id='6998801e706dcfd60bfecaab5fbbfb9e03255cf5', lfs={'size': 162377221, 'sha256': 'a2495145aca18cff0c70e13ae51e571f368873607ca5929eeffc5263edde5021', 'pointer_size': 134}, last_commit=None, security=None),\n",
       " RepoFile(path='breast__he__10068.xml', size=180740, blob_id='c6988351db7e295fb9db996b86815c005b068b2b', lfs=None, last_commit=None, security=None),\n",
       " RepoFile(path='breast__he__12008.svs', size=431400056, blob_id='d28fdb9fa59fb56327500576026b35235403bec2', lfs={'size': 431400056, 'sha256': 'ee210197ef65486331edf911c17a2f91c6b55cb8a47883ea352a3ca3d135363a', 'pointer_size': 134}, last_commit=None, security=None),\n",
       " RepoFile(path='breast__he__12008.xml', size=851663, blob_id='d7208080afb08d83082e1e51289af0a4bddaf13a', lfs=None, last_commit=None, security=None)]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get all the filenames\n",
    "all_files_external = list(hfh.list_files_info(repo_id=external_test_repo_id, repo_type=\"dataset\"))\n",
    "all_files_internal = list(hfh.list_files_info(repo_id=internal_test_repo_id, repo_type=\"dataset\"))\n",
    "all_files_external[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "37d667f7",
   "metadata": {
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     "exception": false,
     "start_time": "2024-01-06T22:32:46.833326",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['.gitattributes',\n",
       " 'breast__he__10068.ndpi',\n",
       " 'breast__he__10068.xml',\n",
       " 'breast__he__12008.svs',\n",
       " 'breast__he__12008.xml']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_names_external = list(map(lambda x: x.rfilename, all_files_external))\n",
    "file_names_internal = list(map(lambda x: x.rfilename, all_files_internal))\n",
    "file_names_external[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8661f0f4",
   "metadata": {
    "execution": {
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     "iopub.status.busy": "2024-01-06T22:32:46.863284Z",
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     "exception": false,
     "start_time": "2024-01-06T22:32:46.855175",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['breast__he__10068.ndpi',\n",
       " 'breast__he__10068.xml',\n",
       " 'breast__he__12008.svs',\n",
       " 'breast__he__12008.xml',\n",
       " 'breast__he__12066.svs']"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_names_external.remove(\".gitattributes\")\n",
    "file_names_internal.remove(\".gitattributes\")\n",
    "\n",
    "file_names_external[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f20c5838",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-06T22:32:46.885098Z",
     "iopub.status.busy": "2024-01-06T22:32:46.884779Z",
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     "exception": false,
     "start_time": "2024-01-06T22:32:46.877755",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['xml', 'ndpi', 'tiff', 'svs']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_extensions_external = list(set(list(map(lambda x: x.split(\".\")[-1], file_names_external))))\n",
    "file_extensions_external"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "764f0268",
   "metadata": {
    "execution": {
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     "exception": false,
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['xml', 'ndpi', 'tif', 'svs', 'tiff', 'mrxs']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_extensions_internal = filter(lambda x: (\"/\" not in x), file_names_internal)\n",
    "file_extensions_internal = list(set(list(map(lambda x: x.split(\".\")[-1], file_extensions_internal))))\n",
    "file_extensions_internal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "652da57a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-06T22:32:46.928555Z",
     "iopub.status.busy": "2024-01-06T22:32:46.928084Z",
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     "duration": 0.015019,
     "end_time": "2024-01-06T22:32:46.935826",
     "exception": false,
     "start_time": "2024-01-06T22:32:46.920807",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "file_extensions_external.remove(\"xml\")\n",
    "file_extensions_internal.remove(\"xml\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3e2cad67",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-06T22:32:46.948994Z",
     "iopub.status.busy": "2024-01-06T22:32:46.948656Z",
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     "exception": false,
     "start_time": "2024-01-06T22:32:46.941755",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "!mkdir -p images masks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "09cb0b53",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-06T22:32:47.280752Z",
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     "exception": false,
     "start_time": "2024-01-06T22:32:47.272840",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def get_allow_list(file_id, file_extension):\n",
    "    if file_extension == \"mrxs\":\n",
    "        return (file_id+\"/*\", file_id+\".*\"), file_id+\".mrxs\", file_id+\".xml\"\n",
    "    else:\n",
    "        return (file_id+\"*\", file_id+f\".{file_extension}\", file_id+\".xml\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d92788fe",
   "metadata": {
    "execution": {
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     "exception": false,
     "start_time": "2024-01-06T22:32:47.295105",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('breast__he__10068*', 'breast__he__10068.ndpi', 'breast__he__10068.xml'),\n",
       " ('breast__he__13131*', 'breast__he__13131.ndpi', 'breast__he__13131.xml'),\n",
       " ('breast__he__13997*', 'breast__he__13997.ndpi', 'breast__he__13997.xml'),\n",
       " ('breast__he__14128*', 'breast__he__14128.ndpi', 'breast__he__14128.xml'),\n",
       " ('breast__he__14327*', 'breast__he__14327.ndpi', 'breast__he__14327.xml')]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# generate allow patterns for processing\n",
    "external_file_list = []\n",
    "for file_extension in file_extensions_external:\n",
    "    external_unique_ids = [f.replace(f\".{file_extension}\", \"\") for f in file_names_external if f.endswith(f\".{file_extension}\")]\n",
    "    external_file_list.extend([get_allow_list(file_id, file_extension) for file_id in external_unique_ids])\n",
    "external_file_list[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "adf6f529",
   "metadata": {
    "execution": {
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     "start_time": "2024-01-06T22:32:47.317808",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('breast__ihc__10030*', 'breast__ihc__10030.ndpi', 'breast__ihc__10030.xml'),\n",
       " ('breast__ihc__10860*', 'breast__ihc__10860.ndpi', 'breast__ihc__10860.xml'),\n",
       " ('breast__ihc__11290*', 'breast__ihc__11290.ndpi', 'breast__ihc__11290.xml'),\n",
       " ('breast__ihc__12314*', 'breast__ihc__12314.ndpi', 'breast__ihc__12314.xml'),\n",
       " ('breast__ihc__14460*', 'breast__ihc__14460.ndpi', 'breast__ihc__14460.xml')]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "internal_file_list = []\n",
    "for file_extension in file_extensions_internal:\n",
    "    internal_unique_ids = [f.replace(f\".{file_extension}\", \"\") for f in file_names_internal if f.endswith(f\".{file_extension}\")]\n",
    "    internal_file_list.extend([get_allow_list(file_id, file_extension) for file_id in internal_unique_ids])\n",
    "internal_file_list[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5f3170d5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-06T22:32:47.351175Z",
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     "shell.execute_reply": "2024-01-06T22:32:47.372149Z"
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     "status": "completed"
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   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>image_id</th>\n",
       "      <th>file_name</th>\n",
       "      <th>source_dataset</th>\n",
       "      <th>image-dimension_x</th>\n",
       "      <th>image-dimension_y</th>\n",
       "      <th>image-levels</th>\n",
       "      <th>image-format</th>\n",
       "      <th>mask_shrink_factor</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [image_id, file_name, source_dataset, image-dimension_x, image-dimension_y, image-levels, image-format, mask_shrink_factor]\n",
       "Index: []"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# now lest make empty metadata dataframe\n",
    "metadata_df = pd.DataFrame(columns=[\"image_id\", \"file_name\", \"source_dataset\", \"image-dimension_x\", \"image-dimension_y\", \"image-levels\", \"image-format\", \"mask_shrink_factor\"])\n",
    "metadata_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "665ca910",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-06T22:32:47.390378Z",
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hfh.utils.are_progress_bars_disabled()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "f50b79a3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-06T22:32:47.415153Z",
     "iopub.status.busy": "2024-01-06T22:32:47.414756Z",
     "iopub.status.idle": "2024-01-06T22:35:23.315808Z",
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     "start_time": "2024-01-06T22:32:47.407064",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "finished 0 image of external\n",
      "finished 1 image of external\n",
      "finished 2 image of external\n",
      "finished 3 image of external\n",
      "finished 4 image of external\n",
      "finished 5 image of external\n",
      "finished 6 image of external\n",
      "finished 7 image of external\n",
      "Annotation label must be either tissue or bg but found: None\n",
      "finished 8 image of external\n",
      "finished 9 image of external\n",
      "finished 10 image of external\n",
      "finished 11 image of external\n",
      "finished 12 image of external\n",
      "finished 13 image of external\n",
      "finished 14 image of external\n",
      "finished 15 image of external\n",
      "finished 16 image of external\n",
      "finished 17 image of external\n",
      "finished 18 image of external\n",
      "finished 19 image of external\n",
      "finished 20 image of external\n",
      "finished 21 image of external\n",
      "finished 22 image of external\n",
      "finished 23 image of external\n",
      "finished 24 image of external\n",
      "finished 25 image of external\n",
      "Annotation label must be either tissue or bg but found: None\n",
      "finished 26 image of external\n",
      "finished 27 image of external\n",
      "finished 28 image of external\n",
      "finished 29 image of external\n",
      "finished 30 image of external\n",
      "finished 31 image of external\n",
      "finished 32 image of external\n",
      "finished 33 image of external\n",
      "finished 34 image of external\n",
      "finished 35 image of external\n",
      "finished 36 image of external\n",
      "finished 37 image of external\n",
      "finished 38 image of external\n",
      "finished 39 image of external\n",
      "finished 40 image of external\n",
      "finished 41 image of external\n",
      "finished 42 image of external\n",
      "finished 43 image of external\n",
      "finished 44 image of external\n",
      "finished 45 image of external\n",
      "finished 46 image of external\n",
      "finished 47 image of external\n",
      "finished 48 image of external\n",
      "finished 49 image of external\n",
      "finished 50 image of external\n",
      "finished 51 image of external\n",
      "finished 52 image of external\n",
      "finished 53 image of external\n",
      "finished 54 image of external\n",
      "finished 55 image of external\n",
      "finished 56 image of external\n",
      "finished 57 image of external\n",
      "finished 58 image of external\n",
      "finished 59 image of external\n"
     ]
    }
   ],
   "source": [
    "# process and save things to a folder\n",
    "image_idx = 0\n",
    "image_idx, metadata_df = process(\n",
    "    external_file_list,\n",
    "    image_idx,\n",
    "    metadata_df,\n",
    "    thumbnail_size=(image_size, image_size),\n",
    "    source_folder_name=\"external\",\n",
    "    raw_repo_id=external_test_repo_id,\n",
    "    pad_images=pad_images\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8773b6bd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-06T22:35:23.338439Z",
     "iopub.status.busy": "2024-01-06T22:35:23.338134Z",
     "iopub.status.idle": "2024-01-06T22:35:23.361666Z",
     "shell.execute_reply": "2024-01-06T22:35:23.360674Z"
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     "start_time": "2024-01-06T22:35:23.327533",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\n",
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       "\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>image_id</th>\n",
       "      <th>file_name</th>\n",
       "      <th>source_dataset</th>\n",
       "      <th>image-dimension_x</th>\n",
       "      <th>image-dimension_y</th>\n",
       "      <th>image-levels</th>\n",
       "      <th>image-format</th>\n",
       "      <th>mask_shrink_factor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>breast__he__10068.ndpi</td>\n",
       "      <td>external</td>\n",
       "      <td>65536</td>\n",
       "      <td>46080</td>\n",
       "      <td>10</td>\n",
       "      <td>hamamatsu</td>\n",
       "      <td>0.007812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>breast__he__13131.ndpi</td>\n",
       "      <td>external</td>\n",
       "      <td>45056</td>\n",
       "      <td>44544</td>\n",
       "      <td>10</td>\n",
       "      <td>hamamatsu</td>\n",
       "      <td>0.011360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>breast__he__13997.ndpi</td>\n",
       "      <td>external</td>\n",
       "      <td>49152</td>\n",
       "      <td>55808</td>\n",
       "      <td>10</td>\n",
       "      <td>hamamatsu</td>\n",
       "      <td>0.009176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>breast__he__14128.ndpi</td>\n",
       "      <td>external</td>\n",
       "      <td>53248</td>\n",
       "      <td>45568</td>\n",
       "      <td>10</td>\n",
       "      <td>hamamatsu</td>\n",
       "      <td>0.009612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>breast__he__14327.ndpi</td>\n",
       "      <td>external</td>\n",
       "      <td>40960</td>\n",
       "      <td>80128</td>\n",
       "      <td>9</td>\n",
       "      <td>hamamatsu</td>\n",
       "      <td>0.006396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>breast__he__15344.ndpi</td>\n",
       "      <td>external</td>\n",
       "      <td>57344</td>\n",
       "      <td>56064</td>\n",
       "      <td>9</td>\n",
       "      <td>hamamatsu</td>\n",
       "      <td>0.008936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>breast__he__17472.ndpi</td>\n",
       "      <td>external</td>\n",
       "      <td>57344</td>\n",
       "      <td>52480</td>\n",
       "      <td>9</td>\n",
       "      <td>hamamatsu</td>\n",
       "      <td>0.008937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>breast__he__18267.ndpi</td>\n",
       "      <td>external</td>\n",
       "      <td>57344</td>\n",
       "      <td>42496</td>\n",
       "      <td>10</td>\n",
       "      <td>hamamatsu</td>\n",
       "      <td>0.008918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>breast__he__19546.ndpi</td>\n",
       "      <td>external</td>\n",
       "      <td>36864</td>\n",
       "      <td>39424</td>\n",
       "      <td>10</td>\n",
       "      <td>hamamatsu</td>\n",
       "      <td>0.012994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>breast__he__19951.ndpi</td>\n",
       "      <td>external</td>\n",
       "      <td>49152</td>\n",
       "      <td>46592</td>\n",
       "      <td>10</td>\n",
       "      <td>hamamatsu</td>\n",
       "      <td>0.010410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>prostate__he__10080.tiff</td>\n",
       "      <td>external</td>\n",
       "      <td>11776</td>\n",
       "      <td>32768</td>\n",
       "      <td>3</td>\n",
       "      <td>generic-tiff</td>\n",
       "      <td>0.015625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>prostate__he__11421.tiff</td>\n",
       "      <td>external</td>\n",
       "      <td>4864</td>\n",
       "      <td>24576</td>\n",
       "      <td>3</td>\n",
       "      <td>generic-tiff</td>\n",
       "      <td>0.020765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>prostate__he__11937.tiff</td>\n",
       "      <td>external</td>\n",
       "      <td>6912</td>\n",
       "      <td>30720</td>\n",
       "      <td>3</td>\n",
       "      <td>generic-tiff</td>\n",
       "      <td>0.016638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>prostate__he__12089.tiff</td>\n",
       "      <td>external</td>\n",
       "      <td>14336</td>\n",
       "      <td>5120</td>\n",
       "      <td>3</td>\n",
       "      <td>generic-tiff</td>\n",
       "      <td>0.035742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>prostate__he__14358.tiff</td>\n",
       "      <td>external</td>\n",
       "      <td>18432</td>\n",
       "      <td>19456</td>\n",
       "      <td>3</td>\n",
       "      <td>generic-tiff</td>\n",
       "      <td>0.026313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>prostate__he__15309.tiff</td>\n",
       "      <td>external</td>\n",
       "      <td>26624</td>\n",
       "      <td>10752</td>\n",
       "      <td>3</td>\n",
       "      <td>generic-tiff</td>\n",
       "      <td>0.019252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>prostate__he__15690.tiff</td>\n",
       "      <td>external</td>\n",
       "      <td>7680</td>\n",
       "      <td>30720</td>\n",
       "      <td>3</td>\n",
       "      <td>generic-tiff</td>\n",
       "      <td>0.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>prostate__he__16351.tiff</td>\n",
       "      <td>external</td>\n",
       "      <td>9984</td>\n",
       "      <td>28672</td>\n",
       "      <td>3</td>\n",
       "      <td>generic-tiff</td>\n",
       "      <td>0.017829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18</td>\n",
       "      <td>prostate__he__17630.tiff</td>\n",
       "      <td>external</td>\n",
       "      <td>13568</td>\n",
       "      <td>4608</td>\n",
       "      <td>3</td>\n",
       "      <td>generic-tiff</td>\n",
       "      <td>0.037760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19</td>\n",
       "      <td>prostate__he__18583.tiff</td>\n",
       "      <td>external</td>\n",
       "      <td>4352</td>\n",
       "      <td>5120</td>\n",
       "      <td>3</td>\n",
       "      <td>generic-tiff</td>\n",
       "      <td>0.099954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>breast__he__12008.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>37405</td>\n",
       "      <td>140264</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.003636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21</td>\n",
       "      <td>breast__he__12066.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>57271</td>\n",
       "      <td>129159</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.003964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22</td>\n",
       "      <td>breast__he__12116.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>63944</td>\n",
       "      <td>107024</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.004785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23</td>\n",
       "      <td>breast__he__14253.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>63809</td>\n",
       "      <td>171563</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.002978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>24</td>\n",
       "      <td>breast__he__16074.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>52913</td>\n",
       "      <td>116270</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.004403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25</td>\n",
       "      <td>breast__he__16216.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>48491</td>\n",
       "      <td>158713</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.003217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26</td>\n",
       "      <td>breast__he__17801.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>55030</td>\n",
       "      <td>147605</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.003471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>27</td>\n",
       "      <td>breast__he__18298.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>39799</td>\n",
       "      <td>51744</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.009900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>28</td>\n",
       "      <td>breast__he__18910.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>52870</td>\n",
       "      <td>132862</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.003859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>29</td>\n",
       "      <td>breast__he__19123.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>57217</td>\n",
       "      <td>158666</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.003233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>30</td>\n",
       "      <td>breast__ihc__10381.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>46463</td>\n",
       "      <td>31452</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.011033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>31</td>\n",
       "      <td>breast__ihc__10385.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>39812</td>\n",
       "      <td>51753</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.009897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>32</td>\n",
       "      <td>breast__ihc__10750.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>42007</td>\n",
       "      <td>53589</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.009546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>33</td>\n",
       "      <td>breast__ihc__10772.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>59654</td>\n",
       "      <td>46173</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.008576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>34</td>\n",
       "      <td>breast__ihc__12351.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>48630</td>\n",
       "      <td>51737</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.009891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>35</td>\n",
       "      <td>breast__ihc__12656.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>50809</td>\n",
       "      <td>60948</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.008384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>36</td>\n",
       "      <td>breast__ihc__12885.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>59614</td>\n",
       "      <td>68308</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.007498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>37</td>\n",
       "      <td>breast__ihc__13423.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>30961</td>\n",
       "      <td>66522</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.007687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>38</td>\n",
       "      <td>breast__ihc__13819.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>44239</td>\n",
       "      <td>42525</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.011570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>39</td>\n",
       "      <td>breast__ihc__14500.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>35389</td>\n",
       "      <td>59139</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.008647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>40</td>\n",
       "      <td>breast__ihc__14551.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>35418</td>\n",
       "      <td>42540</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.012028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>41</td>\n",
       "      <td>breast__ihc__15170.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>57401</td>\n",
       "      <td>70152</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.007300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>42</td>\n",
       "      <td>breast__ihc__15173.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>59634</td>\n",
       "      <td>59089</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.008597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>43</td>\n",
       "      <td>breast__ihc__16289.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>24377</td>\n",
       "      <td>53628</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.009558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>44</td>\n",
       "      <td>breast__ihc__16324.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>55243</td>\n",
       "      <td>48027</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.009266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>45</td>\n",
       "      <td>breast__ihc__17029.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>50806</td>\n",
       "      <td>59097</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.008660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>46</td>\n",
       "      <td>breast__ihc__17083.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>50780</td>\n",
       "      <td>73854</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.006932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>47</td>\n",
       "      <td>breast__ihc__17276.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>33213</td>\n",
       "      <td>46237</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.011080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>48</td>\n",
       "      <td>breast__ihc__18099.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>46449</td>\n",
       "      <td>38829</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.011023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>49</td>\n",
       "      <td>breast__ihc__19960.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>48639</td>\n",
       "      <td>46203</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.010519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>50</td>\n",
       "      <td>prostate__he__10802.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>88199</td>\n",
       "      <td>44175</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.005795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>51</td>\n",
       "      <td>prostate__he__10925.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>63273</td>\n",
       "      <td>40126</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.008099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>52</td>\n",
       "      <td>prostate__he__11898.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>51769</td>\n",
       "      <td>26776</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.009897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>53</td>\n",
       "      <td>prostate__he__13204.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>73818</td>\n",
       "      <td>30833</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.006941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>54</td>\n",
       "      <td>prostate__he__16527.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>46017</td>\n",
       "      <td>26536</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.011117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>55</td>\n",
       "      <td>prostate__he__16597.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>73818</td>\n",
       "      <td>48074</td>\n",
       "      <td>4</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.006927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>56</td>\n",
       "      <td>prostate__he__16713.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>51769</td>\n",
       "      <td>35012</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.009882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>57</td>\n",
       "      <td>prostate__he__18388.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>60397</td>\n",
       "      <td>35244</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.008484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>58</td>\n",
       "      <td>prostate__he__19372.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>62314</td>\n",
       "      <td>29578</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.008216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>59</td>\n",
       "      <td>prostate__he__19783.svs</td>\n",
       "      <td>external</td>\n",
       "      <td>56562</td>\n",
       "      <td>32166</td>\n",
       "      <td>3</td>\n",
       "      <td>aperio</td>\n",
       "      <td>0.009047</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    image_id                 file_name source_dataset  image-dimension_x  \\\n",
       "0          0    breast__he__10068.ndpi       external              65536   \n",
       "1          1    breast__he__13131.ndpi       external              45056   \n",
       "2          2    breast__he__13997.ndpi       external              49152   \n",
       "3          3    breast__he__14128.ndpi       external              53248   \n",
       "4          4    breast__he__14327.ndpi       external              40960   \n",
       "5          5    breast__he__15344.ndpi       external              57344   \n",
       "6          6    breast__he__17472.ndpi       external              57344   \n",
       "7          7    breast__he__18267.ndpi       external              57344   \n",
       "8          8    breast__he__19546.ndpi       external              36864   \n",
       "9          9    breast__he__19951.ndpi       external              49152   \n",
       "10        10  prostate__he__10080.tiff       external              11776   \n",
       "11        11  prostate__he__11421.tiff       external               4864   \n",
       "12        12  prostate__he__11937.tiff       external               6912   \n",
       "13        13  prostate__he__12089.tiff       external              14336   \n",
       "14        14  prostate__he__14358.tiff       external              18432   \n",
       "15        15  prostate__he__15309.tiff       external              26624   \n",
       "16        16  prostate__he__15690.tiff       external               7680   \n",
       "17        17  prostate__he__16351.tiff       external               9984   \n",
       "18        18  prostate__he__17630.tiff       external              13568   \n",
       "19        19  prostate__he__18583.tiff       external               4352   \n",
       "20        20     breast__he__12008.svs       external              37405   \n",
       "21        21     breast__he__12066.svs       external              57271   \n",
       "22        22     breast__he__12116.svs       external              63944   \n",
       "23        23     breast__he__14253.svs       external              63809   \n",
       "24        24     breast__he__16074.svs       external              52913   \n",
       "25        25     breast__he__16216.svs       external              48491   \n",
       "26        26     breast__he__17801.svs       external              55030   \n",
       "27        27     breast__he__18298.svs       external              39799   \n",
       "28        28     breast__he__18910.svs       external              52870   \n",
       "29        29     breast__he__19123.svs       external              57217   \n",
       "30        30    breast__ihc__10381.svs       external              46463   \n",
       "31        31    breast__ihc__10385.svs       external              39812   \n",
       "32        32    breast__ihc__10750.svs       external              42007   \n",
       "33        33    breast__ihc__10772.svs       external              59654   \n",
       "34        34    breast__ihc__12351.svs       external              48630   \n",
       "35        35    breast__ihc__12656.svs       external              50809   \n",
       "36        36    breast__ihc__12885.svs       external              59614   \n",
       "37        37    breast__ihc__13423.svs       external              30961   \n",
       "38        38    breast__ihc__13819.svs       external              44239   \n",
       "39        39    breast__ihc__14500.svs       external              35389   \n",
       "40        40    breast__ihc__14551.svs       external              35418   \n",
       "41        41    breast__ihc__15170.svs       external              57401   \n",
       "42        42    breast__ihc__15173.svs       external              59634   \n",
       "43        43    breast__ihc__16289.svs       external              24377   \n",
       "44        44    breast__ihc__16324.svs       external              55243   \n",
       "45        45    breast__ihc__17029.svs       external              50806   \n",
       "46        46    breast__ihc__17083.svs       external              50780   \n",
       "47        47    breast__ihc__17276.svs       external              33213   \n",
       "48        48    breast__ihc__18099.svs       external              46449   \n",
       "49        49    breast__ihc__19960.svs       external              48639   \n",
       "50        50   prostate__he__10802.svs       external              88199   \n",
       "51        51   prostate__he__10925.svs       external              63273   \n",
       "52        52   prostate__he__11898.svs       external              51769   \n",
       "53        53   prostate__he__13204.svs       external              73818   \n",
       "54        54   prostate__he__16527.svs       external              46017   \n",
       "55        55   prostate__he__16597.svs       external              73818   \n",
       "56        56   prostate__he__16713.svs       external              51769   \n",
       "57        57   prostate__he__18388.svs       external              60397   \n",
       "58        58   prostate__he__19372.svs       external              62314   \n",
       "59        59   prostate__he__19783.svs       external              56562   \n",
       "\n",
       "    image-dimension_y  image-levels  image-format  mask_shrink_factor  \n",
       "0               46080            10     hamamatsu            0.007812  \n",
       "1               44544            10     hamamatsu            0.011360  \n",
       "2               55808            10     hamamatsu            0.009176  \n",
       "3               45568            10     hamamatsu            0.009612  \n",
       "4               80128             9     hamamatsu            0.006396  \n",
       "5               56064             9     hamamatsu            0.008936  \n",
       "6               52480             9     hamamatsu            0.008937  \n",
       "7               42496            10     hamamatsu            0.008918  \n",
       "8               39424            10     hamamatsu            0.012994  \n",
       "9               46592            10     hamamatsu            0.010410  \n",
       "10              32768             3  generic-tiff            0.015625  \n",
       "11              24576             3  generic-tiff            0.020765  \n",
       "12              30720             3  generic-tiff            0.016638  \n",
       "13               5120             3  generic-tiff            0.035742  \n",
       "14              19456             3  generic-tiff            0.026313  \n",
       "15              10752             3  generic-tiff            0.019252  \n",
       "16              30720             3  generic-tiff            0.016667  \n",
       "17              28672             3  generic-tiff            0.017829  \n",
       "18               4608             3  generic-tiff            0.037760  \n",
       "19               5120             3  generic-tiff            0.099954  \n",
       "20             140264             4        aperio            0.003636  \n",
       "21             129159             4        aperio            0.003964  \n",
       "22             107024             4        aperio            0.004785  \n",
       "23             171563             4        aperio            0.002978  \n",
       "24             116270             4        aperio            0.004403  \n",
       "25             158713             4        aperio            0.003217  \n",
       "26             147605             4        aperio            0.003471  \n",
       "27              51744             3        aperio            0.009900  \n",
       "28             132862             4        aperio            0.003859  \n",
       "29             158666             4        aperio            0.003233  \n",
       "30              31452             3        aperio            0.011033  \n",
       "31              51753             3        aperio            0.009897  \n",
       "32              53589             3        aperio            0.009546  \n",
       "33              46173             3        aperio            0.008576  \n",
       "34              51737             3        aperio            0.009891  \n",
       "35              60948             4        aperio            0.008384  \n",
       "36              68308             4        aperio            0.007498  \n",
       "37              66522             3        aperio            0.007687  \n",
       "38              42525             3        aperio            0.011570  \n",
       "39              59139             3        aperio            0.008647  \n",
       "40              42540             3        aperio            0.012028  \n",
       "41              70152             4        aperio            0.007300  \n",
       "42              59089             4        aperio            0.008597  \n",
       "43              53628             3        aperio            0.009558  \n",
       "44              48027             3        aperio            0.009266  \n",
       "45              59097             4        aperio            0.008660  \n",
       "46              73854             4        aperio            0.006932  \n",
       "47              46237             3        aperio            0.011080  \n",
       "48              38829             3        aperio            0.011023  \n",
       "49              46203             3        aperio            0.010519  \n",
       "50              44175             4        aperio            0.005795  \n",
       "51              40126             3        aperio            0.008099  \n",
       "52              26776             3        aperio            0.009897  \n",
       "53              30833             4        aperio            0.006941  \n",
       "54              26536             3        aperio            0.011117  \n",
       "55              48074             4        aperio            0.006927  \n",
       "56              35012             3        aperio            0.009882  \n",
       "57              35244             3        aperio            0.008484  \n",
       "58              29578             3        aperio            0.008216  \n",
       "59              32166             3        aperio            0.009047  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metadata_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "9c8a0a01",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-06T22:35:23.388197Z",
     "iopub.status.busy": "2024-01-06T22:35:23.387744Z",
     "iopub.status.idle": "2024-01-06T22:46:50.921326Z",
     "shell.execute_reply": "2024-01-06T22:46:50.919447Z"
    },
    "papermill": {
     "duration": 687.561078,
     "end_time": "2024-01-06T22:46:50.936465",
     "exception": false,
     "start_time": "2024-01-06T22:35:23.375387",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "finished 60 image of internal\n",
      "finished 61 image of internal\n",
      "finished 62 image of internal\n",
      "finished 63 image of internal\n",
      "finished 64 image of internal\n",
      "finished 65 image of internal\n",
      "finished 66 image of internal\n",
      "finished 67 image of internal\n",
      "finished 68 image of internal\n",
      "finished 69 image of internal\n",
      "Annotation label must be either tissue or bg but found: roi\n",
      "finished 70 image of internal\n",
      "Annotation label must be either tissue or bg but found: roi\n",
      "finished 71 image of internal\n",
      "Annotation label must be either tissue or bg but found: roi\n",
      "finished 72 image of internal\n",
      "Annotation label must be either tissue or bg but found: roi\n",
      "finished 73 image of internal\n",
      "Annotation label must be either tissue or bg but found: roi\n",
      "finished 74 image of internal\n",
      "Annotation label must be either tissue or bg but found: roi\n",
      "finished 75 image of internal\n",
      "Annotation label must be either tissue or bg but found: roi\n",
      "finished 76 image of internal\n",
      "Annotation label must be either tissue or bg but found: roi\n",
      "finished 77 image of internal\n",
      "Annotation label must be either tissue or bg but found: roi\n",
      "finished 78 image of internal\n",
      "Annotation label must be either tissue or bg but found: roi\n",
      "finished 79 image of internal\n",
      "finished 80 image of internal\n",
      "finished 81 image of internal\n",
      "finished 82 image of internal\n",
      "finished 83 image of internal\n",
      "finished 84 image of internal\n",
      "finished 85 image of internal\n",
      "finished 86 image of internal\n",
      "finished 87 image of internal\n",
      "finished 88 image of internal\n",
      "finished 89 image of internal\n",
      "finished 90 image of internal\n",
      "finished 91 image of internal\n",
      "Annotation label must be either tissue or bg but found: None\n",
      "finished 92 image of internal\n",
      "finished 93 image of internal\n",
      "finished 94 image of internal\n",
      "finished 95 image of internal\n",
      "finished 96 image of internal\n",
      "finished 97 image of internal\n",
      "finished 98 image of internal\n",
      "finished 99 image of internal\n",
      "finished 100 image of internal\n",
      "finished 101 image of internal\n",
      "finished 102 image of internal\n",
      "finished 103 image of internal\n",
      "finished 104 image of internal\n",
      "finished 105 image of internal\n",
      "finished 106 image of internal\n",
      "finished 107 image of internal\n",
      "finished 108 image of internal\n",
      "finished 109 image of internal\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "110"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_idx, metadata_df = process(\n",
    "    internal_file_list,\n",
    "    image_idx,\n",
    "    metadata_df,\n",
    "    thumbnail_size=(image_size, image_size),\n",
    "    source_folder_name=\"internal\",\n",
    "    raw_repo_id=internal_test_repo_id,\n",
    "    pad_images=pad_images\n",
    ")\n",
    "image_idx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "08fe3aa5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-06T22:46:50.971809Z",
     "iopub.status.busy": "2024-01-06T22:46:50.971334Z",
     "iopub.status.idle": "2024-01-06T22:46:51.445791Z",
     "shell.execute_reply": "2024-01-06T22:46:51.444116Z"
    },
    "papermill": {
     "duration": 0.497246,
     "end_time": "2024-01-06T22:46:51.448320",
     "exception": false,
     "start_time": "2024-01-06T22:46:50.951074",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_image_mask_by_path(\"images/1.png\", \"masks/1.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b6b3b301",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-06T22:46:51.485918Z",
     "iopub.status.busy": "2024-01-06T22:46:51.484508Z",
     "iopub.status.idle": "2024-01-06T22:46:51.505031Z",
     "shell.execute_reply": "2024-01-06T22:46:51.503678Z"
    },
    "papermill": {
     "duration": 0.04322,
     "end_time": "2024-01-06T22:46:51.507941",
     "exception": false,
     "start_time": "2024-01-06T22:46:51.464721",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "metadata_df.to_csv(\"metadata.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "3b9f747e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-06T22:46:51.544218Z",
     "iopub.status.busy": "2024-01-06T22:46:51.543455Z",
     "iopub.status.idle": "2024-01-06T22:46:55.677363Z",
     "shell.execute_reply": "2024-01-06T22:46:55.676269Z"
    },
    "papermill": {
     "duration": 4.154145,
     "end_time": "2024-01-06T22:46:55.679414",
     "exception": false,
     "start_time": "2024-01-06T22:46:51.525269",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  adding: images/ (stored 0%)\r\n",
      "  adding: images/24.png (deflated 2%)\r\n",
      "  adding: images/44.png (deflated 0%)\r\n",
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     ]
    },
    {
     "data": {
      "text/plain": [
       "'https://huggingface.co/datasets/ain3007-project/test-dataset-thumbnails-512-padded/blob/main/metadata.csv'"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "api = hfh.HfApi()\n",
    "\n",
    "# upload zipped folder\n",
    "!zip -r images.zip images\n",
    "!zip -r masks.zip masks\n",
    "\n",
    "api.upload_file(\n",
    "    path_or_fileobj=\"images.zip\",\n",
    "    path_in_repo=\"images.zip\",\n",
    "    repo_id=output_repo_id,\n",
    "    repo_type=\"dataset\",\n",
    ")\n",
    "\n",
    "api.upload_file(\n",
    "    path_or_fileobj=\"masks.zip\",\n",
    "    path_in_repo=\"masks.zip\",\n",
    "    repo_id=output_repo_id,\n",
    "    repo_type=\"dataset\",\n",
    ")\n",
    "\n",
    "api.upload_file(\n",
    "    path_or_fileobj=\"metadata.csv\",\n",
    "    path_in_repo=\"metadata.csv\",\n",
    "    repo_id=output_repo_id,\n",
    "    repo_type=\"dataset\",\n",
    ")"
   ]
  }
 ],
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