fixes

Author: rijobro

deepedit/ignite/infoANDinference.ipynb

@@ -98,6 +98,7 @@
     "import numpy as np\n",
     "import torch\n",
     "from torch import jit\n",
+    "import tempfile\n",
     "\n",
     "import monai\n",
     "from monai.config import print_config\n",
@@ -121,6 +122,7 @@
     "    SqueezeDimd,\n",
     "    ToNumpyd,\n",
     "    ToTensord,\n",
+    "    FromMetaTensord,\n",
     ")\n",
     "\n",
     "print_config()"
@@ -226,18 +228,16 @@
    ],
    "source": [
     "# Download data and model\n",
+    "data_dir = tempfile.TemporaryDirectory().name\n",
     "\n",
     "resource = \"https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/_image.nii.gz\"\n",
-    "dst = \"_image.nii.gz\"\n",
-    "\n",
-    "if not os.path.exists(dst):\n",
-    "    monai.apps.download_url(resource, dst)\n",
+    "image_path = os.path.join(data_dir, \"_image.nii.gz\")\n",
+    "monai.apps.download_url(resource, image_path)\n",
     "\n",
     "resource = \"https://github.com/Project-MONAI/MONAI-extra-test-data/releases/\\\n",
     "download/0.8.1/pretrained_deepedit_dynunet-final.ts\"\n",
-    "dst = \"pretrained_deepedit_dynunet-final.ts\"\n",
-    "if not os.path.exists(dst):\n",
-    "    monai.apps.download_url(resource, dst)"
+    "model_path = os.path.join(data_dir, \"pretrained_deepedit_dynunet-final.ts\")\n",
+    "monai.apps.download_url(resource, model_path)"
    ]
   },
   {
@@ -277,11 +277,12 @@
      "output_type": "stream",
      "text": [
       "EnsureChannelFirstd => image shape: (1, 392, 392, 210)\n",
-      "Orientationd => image shape: (1, 392, 392, 210)\n",
-      "ScaleIntensityRanged => image shape: (1, 392, 392, 210)\n",
-      "AddGuidanceFromPointsDeepEditd => image shape: (1, 392, 392, 210)\n",
-      "Resized => image shape: (1, 128, 128, 128)\n",
-      "ResizeGuidanceMultipleLabelDeepEditd => image shape: (1, 128, 128, 128)\n",
+      "FromMetaTensord => image shape: torch.Size([1, 392, 392, 210])\n",
+      "Orientationd => image shape: torch.Size([1, 392, 392, 210])\n",
+      "ScaleIntensityRanged => image shape: torch.Size([1, 392, 392, 210])\n",
+      "AddGuidanceFromPointsDeepEditd => image shape: torch.Size([1, 392, 392, 210])\n",
+      "Resized => image shape: torch.Size([1, 128, 128, 128])\n",
+      "ResizeGuidanceMultipleLabelDeepEditd => image shape: torch.Size([1, 128, 128, 128])\n",
       "AddGuidanceSignalDeepEditd => image shape: (3, 128, 128, 128)\n",
       "ToTensord => image shape: torch.Size([3, 128, 128, 128])\n"
      ]
@@ -297,7 +298,7 @@
     "spatial_size = [128, 128, 128]\n",
     "\n",
     "data = {\n",
-    "    'image': '_image.nii.gz',\n",
+    "    'image': image_path,\n",
     "    'guidance': {'spleen': [[66, 180, 105], [66, 180, 145]], 'background': []},\n",
     "}\n",
     "\n",
@@ -308,6 +309,8 @@
     "    LoadImaged(keys=\"image\", reader=\"ITKReader\"),\n",
     "    # Ensure channel first\n",
     "    EnsureChannelFirstd(keys=\"image\"),\n",
+    "    # Convert away from MetaTensor\n",
+    "    FromMetaTensord(keys=\"image\"),\n",
     "    # Change image orientation\n",
     "    Orientationd(keys=\"image\", axcodes=\"RAS\"),\n",
     "    # Scaling image intensity - works well for CT images\n",
@@ -475,7 +478,6 @@
    ],
    "source": [
     "# Evaluation\n",
-    "model_path = 'pretrained_deepedit_dynunet-final.ts'\n",
     "model = jit.load(model_path)\n",
     "model.cuda()\n",
     "model.eval()\n",
@@ -512,17 +514,6 @@
     "        i, image.shape, label.shape, np.min(label), np.max(label), np.sum(label)))\n",
     "    show_image(image, label)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# remove downloaded files\n",
-    "os.remove('_image.nii.gz')\n",
-    "os.remove('pretrained_deepedit_dynunet-final.ts')"
-   ]
   }
  ],
  "metadata": {