densenet training download data (#685)

Co-authored-by: Wenqi Li <831580+wyli@users.noreply.github.com>

Author: rijobro

3d_classification/densenet_training_array.ipynb

@@ -131,40 +131,17 @@
     }
    ],
    "source": [
-    "# set this in your environment or previous cell to wherever IXI is downloaded and extracted\n",
+    "# Set data directory\n",
     "directory = os.environ.get(\"MONAI_DATA_DIRECTORY\")\n",
-    "\n",
-    "if directory is None:\n",
-    "    resource = \"http://biomedic.doc.ic.ac.uk/brain-development/downloads/IXI/IXI-T1.tar\"\n",
-    "    md5 = \"34901a0593b41dd19c1a1f746eac2d58\"\n",
-    "\n",
-    "    root_dir = tempfile.mkdtemp()\n",
-    "\n",
-    "    dataset_dir = os.path.join(root_dir, \"ixi\")\n",
-    "    tarfile_name = f\"{dataset_dir}.tar\"\n",
-    "\n",
-    "    download_and_extract(resource, tarfile_name, dataset_dir, md5)\n",
-    "else:\n",
-    "    root_dir = directory\n",
-    "\n",
+    "root_dir = tempfile.mkdtemp() if directory is None else directory\n",
     "print(root_dir)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'torch.Tensor'> torch.Size([3, 1, 96, 96, 96]) tensor([[1., 0.],\n",
-      "        [1., 0.],\n",
-      "        [1., 0.]]) torch.Size([3, 2])\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# IXI dataset as a demo, downloadable from https://brain-development.org/ixi-dataset/\n",
     "images = [\n",
@@ -195,8 +172,58 @@
     "\n",
     "# Represent labels in one-hot format for binary classifier training,\n",
     "# BCEWithLogitsLoss requires target to have same shape as input\n",
-    "labels = torch.nn.functional.one_hot(torch.as_tensor(labels)).float()\n",
+    "labels = torch.nn.functional.one_hot(torch.as_tensor(labels)).float()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "ixi.tar: 100%|██████████| 4.51G/4.51G [08:19<00:00, 9.70MB/s]   \n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-05-04 12:23:06,530 - INFO - Downloaded: /mnt/data/rbrown/Documents/Data/MONAI/ixi.tar\n",
+      "2022-05-04 12:23:13,734 - INFO - Verified 'ixi.tar', md5: 34901a0593b41dd19c1a1f746eac2d58.\n",
+      "2022-05-04 12:23:13,735 - INFO - Writing into directory: /mnt/data/rbrown/Documents/Data/MONAI/ixi.\n"
+     ]
+    }
+   ],
+   "source": [
+    "if not os.path.isfile(images[0]):\n",
+    "    resource = \"http://biomedic.doc.ic.ac.uk/brain-development/downloads/IXI/IXI-T1.tar\"\n",
+    "    md5 = \"34901a0593b41dd19c1a1f746eac2d58\"\n",
     "\n",
+    "    dataset_dir = os.path.join(root_dir, \"ixi\")\n",
+    "    tarfile_name = f\"{dataset_dir}.tar\"\n",
+    "\n",
+    "    download_and_extract(resource, tarfile_name, dataset_dir, md5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'torch.Tensor'> torch.Size([3, 1, 96, 96, 96]) tensor([[1., 0.],\n",
+      "        [1., 0.],\n",
+      "        [1., 0.]]) torch.Size([3, 2])\n"
+     ]
+    }
+   ],
+   "source": [
     "# Define transforms\n",
     "train_transforms = Compose([ScaleIntensity(), AddChannel(), Resize((96, 96, 96)), RandRotate90(), EnsureType()])\n",
     "\n",
@@ -220,7 +247,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -367,7 +394,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -395,7 +422,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -405,7 +432,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 10,
    "metadata": {
     "scrolled": true,
     "tags": []
@@ -462,7 +489,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [