adjust examples

app.py

@@ -26,7 +26,8 @@ iface = gr.Interface(
     outputs=gr.Label(num_top_classes=10),
     title="Sentinel Image Classifier",
     description="Upload a satellite image and the classifier will predict the type of land cover or feature.",
-    examples=["images/forest.jpg", "images/highway.jpg", "images/industrial.jpg", "images/residential.jpg", "images/river.jpg"]
+    examples = ["images/annualcrop.jpg", "images/forest.jpg", "images/herbaceousvegetation.jpg", "images/highway.jpg", "images/industrial.jpg", "images/pasture.jpg", "images/permanentcrop.jpg", "images/residential.jpg", "images/river.jpg", "images/sealake.jpg"]
+
 )
 
 iface.launch()

main.ipynb

@@ -2,14 +2,14 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Running on local URL:  http://127.0.0.1:7880\n",
+      "Running on local URL:  http://127.0.0.1:7881\n",
       "\n",
       "To create a public link, set `share=True` in `launch()`.\n"
      ]
@@ -17,7 +17,7 @@
     {
      "data": {
       "text/html": [
-       "<div><iframe src=\"http://127.0.0.1:7880/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+       "<div><iframe src=\"http://127.0.0.1:7881/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -30,18 +30,9 @@
      "data": {
       "text/plain": []
      },
-     "execution_count": 29,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 916ms/step\n",
-      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 15ms/step\n",
-      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 14ms/step\n"
-     ]
     }
    ],
    "source": [
@@ -73,7 +64,7 @@
     "    outputs=gr.Label(num_top_classes=10),\n",
     "    title=\"Sentinel Image Classifier\",\n",
     "    description=\"Upload a satellite image and the classifier will predict the type of land cover or feature.\",\n",
-    "    examples=[\"images/forest.jpg\", \"images/highway.jpg\", \"images/industrial.jpg\", \"images/residential.jpg\", \"images/river.jpg\"]\n",
+    "    examples = [\"images/annualcrop.jpg\", \"images/forest.jpg\", \"images/herbaceousvegetation.jpg\", \"images/highway.jpg\", \"images/industrial.jpg\", \"images/pasture.jpg\", \"images/permanentcrop.jpg\", \"images/residential.jpg\", \"images/river.jpg\", \"images/sealake.jpg\"]\n",
     ")\n",
     "# Launch the interface\n",
     "iface.launch(share=False)\n"