added is_3d flag to examples

Author: njl-02

notebooks/01_prediction_demo.ipynb

@@ -29,7 +29,7 @@
     "OUTPUT_DIR = '../data/test_SNI/'\n",
     "\n",
     "# generate unlabeled SNIs #\n",
-    "df = utils.generate_images(IMAGE_DIR, MASK_DIR, OUTPUT_DIR, return_df=True, num_cores=None)\n",
+    "df = utils.generate_images(IMAGE_DIR, MASK_DIR, OUTPUT_DIR, return_df=True, num_cores=None, is_3d=True)\n",
     "df"
    ]
   },
@@ -49,7 +49,7 @@
    "outputs": [],
    "source": [
     "# load pre-trained model\n",
-    "model = CellCycleNet()\n",
+    "model = CellCycleNet(is_3d=True)\n",
     "\n",
     "# create dataset #\n",
     "test = model.create_dataset(dataframe=df, split_data=False)\n",
@@ -77,7 +77,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.4"
+   "version": "3.12.2"
   }
  },
  "nbformat": 4,

notebooks/02_fine_tune_training_demo.ipynb

@@ -31,7 +31,7 @@
     "OUTPUT_DIR = '../data/test_SNI_label/'\n",
     "\n",
     "# # generate unlabeled SNIs #\n",
-    "df = utils.generate_images_labeled(IMAGE_DIR, MASK_DIR, LABEL_DIR, OUTPUT_DIR, return_df=True, num_cores=None)\n",
+    "df = utils.generate_images_labeled(IMAGE_DIR, MASK_DIR, LABEL_DIR, OUTPUT_DIR, return_df=True, num_cores=None, is_3d=True)\n",
     "df"
    ]
   },
@@ -51,7 +51,7 @@
    "outputs": [],
    "source": [
     "# load pre-trained model\n",
-    "model = CellCycleNet()\n",
+    "model = CellCycleNet(is_3d=True)\n",
     "\n",
     "# create dataset\n",
     "train, val, test = model.create_dataset(dataframe=df, split_data=True)\n",