diff --git a/01_materials/labs/lab_4.ipynb b/01_materials/labs/lab_4.ipynb
index 90bd4fffb..49316d21a 100644
--- a/01_materials/labs/lab_4.ipynb
+++ b/01_materials/labs/lab_4.ipynb
@@ -603,7 +603,17 @@
    "outputs": [],
    "source": [
     "from keras.applications.resnet50 import preprocess_input, decode_predictions\n",
-    "\n"
+    "\n",
+    "# Resize the image\n",
+    "input_image = resize(image, (224, 224, 3), mode='reflect', anti_aliasing=True)\n",
+    "\n",
+    "# Scale to [0, 255] range (resize returns [0, 1])\n",
+    "input_image = input_image * 255\n",
+    "\n",
+    "# Prepare for model (add batch dimension)\n",
+    "input_image = np.expand_dims(input_image, axis=0)\n",
+    "\n",
+    "# Now use preprocess_input and predict to classify the image\n"
    ]
   },
   {
@@ -680,7 +690,20 @@
     "id": "b1pXoFQgI_fk"
    },
    "outputs": [],
-   "source": []
+   "source": [
+    "# Apply the same preprocessing as before and classify the webcam image\n",
+    "\n",
+    "# Resize the image\n",
+    "input_image = resize(image, (224, 224, 3), mode='reflect', anti_aliasing=True)\n",
+    "\n",
+    "# Scale to [0, 255] range (resize returns [0, 1])\n",
+    "input_image = input_image * 255\n",
+    "\n",
+    "# Prepare for model (add batch dimension)\n",
+    "input_image = np.expand_dims(input_image, axis=0)\n",
+    "\n",
+    "# Now use preprocess_input and predict to classify the image\n"
+   ]
   },
   {
    "cell_type": "code",