autofixes

Signed-off-by: Wenqi Li <[email protected]>

Author: wyli

model_zoo/TCIA_PROSTATEx_Prostate_MRI_Anatomy_Model.ipynb

@@ -16,8 +16,7 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "N92pMd7ig0ZS",
-    "jp-MarkdownHeadingCollapsed": true,
+    "incorrectly_encoded_metadata": "id=\"N92pMd7ig0ZS\" jp-MarkdownHeadingCollapsed=true",
     "tags": []
    },
    "source": [
@@ -76,7 +75,6 @@
    "outputs": [],
    "source": [
     "import os\n",
-    "import sys\n",
     "\n",
     "# Upgrade pip, just in case.\n",
     "!{sys.executable} -m pip install --upgrade -q pip"
@@ -210,10 +208,10 @@
     "# Download a \"Shared Cart\" containing 6 scans from PROSTATEx\n",
     "#    that has been previously created via the TCIA website \n",
     "#    (https://nbia.cancerimagingarchive.net).\n",
-    "cartName = \"nbia-17571668146714049\"\n",
+    "cart_name = \"nbia-17571668146714049\"\n",
     "\n",
     "# retrieve cart metadata\n",
-    "cart_data = nbia.getSharedCart(cartName)\n",
+    "cart_data = nbia.getSharedCart(cart_name)\n",
     "\n",
     "# download the series_uids list and return dataframe of metadata\n",
     "df = nbia.downloadSeries(cart_data)\n",
@@ -318,11 +316,12 @@
     "#   Ideally this would have been accomplished using MONAI's transforms\n",
     "#   for data pre-processing / augmentation instead of using a separate\n",
     "#   function.\n",
-    "def prostate_crop( img ):\n",
-    "    boundary = [int(crop_size*0.2) for crop_size in img.GetLargestPossibleRegion().GetSize()]\n",
+    "def prostate_crop(img):\n",
+    "    boundary = [int(crop_size * 0.2) for crop_size in img.GetLargestPossibleRegion().GetSize()]\n",
     "    new_image = itk.CropImageFilter(Input=img, BoundaryCropSize=boundary)\n",
     "    return new_image\n",
     "\n",
+    "\n",
     "mr_image_prep = prostate_crop(mr_image)\n",
     "seg_image_prep = prostate_crop(seg_image)\n",
     "\n",
@@ -456,7 +455,8 @@
    "outputs": [],
    "source": [
     "# Read the result image that was written into the output_dir.\n",
-    "result_image = itk.imread(os.path.join( output_dir, os.path.split(mr_dir)[1], os.path.split(mr_dir)[1] + \"_trans.nii.gz\"))"
+    "result_image = itk.imread(os.path.join(output_dir, os.path.split(mr_dir)[\n",
+    "                          1], os.path.split(mr_dir)[1] + \"_trans.nii.gz\"))"
    ]
   },
   {
@@ -473,9 +473,9 @@
     "#    image to match the physical properties of the original input data.\n",
     "interpolator = itk.NearestNeighborInterpolateImageFunction.New(seg_image)\n",
     "result_image_resampled = itk.resample_image_filter(Input=result_image,\n",
-    "                                            Interpolator=interpolator,\n",
-    "                                            reference_image=seg_image_prep, \n",
-    "                                            use_reference_image=True)"
+    "                                                   Interpolator=interpolator,\n",
+    "                                                   reference_image=seg_image_prep, \n",
+    "                                                   use_reference_image=True)"
    ]
   },
   {
@@ -488,7 +488,7 @@
    "outputs": [],
    "source": [
     "# View the image with results overlaid in an interactive 2D slice viewer.\n",
-    "viewerB = view(image=mr_image_prep, label_image=result_image_resampled)"
+    "viewer_b = view(image=mr_image_prep, label_image=result_image_resampled)"
    ]
   },
   {
@@ -501,11 +501,11 @@
    },
    "outputs": [],
    "source": [
-    "viewerB.set_image_color_map(\"Grayscale\")\n",
-    "viewerB.set_label_image_blend(0.5)\n",
-    "viewerB.set_image_color_range([100,500])\n",
-    "viewerB.set_view_mode('ZPlane')\n",
-    "viewerB.set_ui_collapsed(False)"
+    "viewer_b.set_image_color_map(\"Grayscale\")\n",
+    "viewer_b.set_label_image_blend(0.5)\n",
+    "viewer_b.set_image_color_range([100, 500])\n",
+    "viewer_b.set_view_mode('ZPlane')\n",
+    "viewer_b.set_ui_collapsed(False)"
    ]
   },
   {
@@ -528,11 +528,11 @@
     "#    1 = ideal prostate, but model called non-prostate (red)\n",
     "#    2 = model called prostate, but ideal called non-prostate (purple)\n",
     "#    3 = modeal and ideal agreed (green)\n",
-    "compare_model_expert = np.where(result_array!=1,0,2) + np.where(expert_array!=2,0,1)\n",
+    "compare_model_expert = np.where(result_array != 1, 0, 2) + np.where(expert_array != 2, 0, 1)\n",
     "compare_image = itk.GetImageFromArray(compare_model_expert.astype(np.float32))\n",
     "compare_image.CopyInformation(seg_image_prep)\n",
     "\n",
-    "viewerC = view(image=mr_image_prep, label_image=compare_image)"
+    "viewer_c = view(image=mr_image_prep, label_image=compare_image)"
    ]
   },
   {
@@ -544,11 +544,11 @@
    "outputs": [],
    "source": [
     "# Switch to an interactive slice view so that labels are more easily seen.\n",
-    "viewerC.set_label_image_blend(0.6)\n",
-    "viewerC.set_image_color_map(\"Grayscale\")\n",
-    "viewerC.set_view_mode(\"ZPlane\")\n",
-    "viewerC.set_image_color_range([100,500])\n",
-    "viewerC.set_ui_collapsed(False)"
+    "viewer_c.set_label_image_blend(0.6)\n",
+    "viewer_c.set_image_color_map(\"Grayscale\")\n",
+    "viewer_c.set_view_mode(\"ZPlane\")\n",
+    "viewer_c.set_image_color_range([100, 500])\n",
+    "viewer_c.set_ui_collapsed(False)"
    ]
   },
   {
@@ -590,9 +590,9 @@
    "provenance": []
   },
   "kernelspec": {
-   "display_name": "medical-image-ai:Python",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "conda-env-medical-image-ai-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -604,7 +604,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.15"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,