updated changes

app.ipynb

@@ -20,7 +20,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 50,
    "id": "844c3071-836e-46c5-b30e-2b8d96a8e369",
    "metadata": {},
    "outputs": [],
@@ -33,7 +33,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 51,
    "id": "ded0d929-67f6-4a69-b223-dee3ad189139",
    "metadata": {},
    "outputs": [],
@@ -43,7 +43,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 52,
    "id": "6b7aeaaa-8260-45fa-9178-e064b0132c36",
    "metadata": {},
    "outputs": [],
@@ -55,7 +55,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 53,
    "id": "a0dfbe70-b826-4903-95cf-ae59c498a3b6",
    "metadata": {},
    "outputs": [],
@@ -68,7 +68,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 54,
    "id": "a5aaeeb6-6a93-4de8-be39-36c4b5d90ee4",
    "metadata": {},
    "outputs": [],
@@ -78,7 +78,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 55,
    "id": "7fcc53f8-0326-49d0-a110-1140148d6301",
    "metadata": {},
    "outputs": [],
@@ -88,7 +88,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 56,
    "id": "6173ae0f-fa63-4a94-b9f6-e0f9534ff8d9",
    "metadata": {},
    "outputs": [],
@@ -98,7 +98,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 57,
    "id": "490af644-cb3c-4f8c-9e12-1a7cf9c18fc0",
    "metadata": {},
    "outputs": [],
@@ -111,7 +111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 58,
    "id": "e3618d64-5db3-4659-b30f-f917939f509a",
    "metadata": {},
    "outputs": [],
@@ -122,7 +122,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 59,
    "id": "b2475bb3-b820-4a9d-b3b7-488e9e2971bc",
    "metadata": {},
    "outputs": [],
@@ -133,7 +133,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 60,
    "id": "1cdad192-403a-44d4-b006-661afebe18da",
    "metadata": {},
    "outputs": [],
@@ -145,14 +145,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 61,
    "id": "c72e52ad-30b5-4c06-83d4-35095e43d419",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "fe84c3bbef9d49beb17489c0cb53294a",
+       "model_id": "dc5c7e68735b44fb942ce0f4c923259b",
        "version_major": 2,
        "version_minor": 0
       },
@@ -160,7 +160,7 @@
        "Button(description='Classify', style=ButtonStyle())"
       ]
      },
-     "execution_count": 43,
+     "execution_count": 61,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -173,45 +173,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
-   "id": "ae0492e9-9981-4fa9-b97c-76d65d4a0206",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#|export\n",
-    "from PIL import Image\n",
-    "import ipywidgets as widgets\n",
-    "\n",
-    "# Optional: Import display only if in an IPython environment\n",
-    "try:\n",
-    "    from IPython.display import display\n",
-    "    can_display = True\n",
-    "except ImportError:\n",
-    "    can_display = False\n",
-    "\n",
-    "def on_click_classify(img_array):\n",
-    "    # Convert numpy array to PIL Image\n",
-    "    img = Image.fromarray(img_array.astype('uint8'), 'RGB')\n",
-    "    \n",
-    "    out_pl = widgets.Output()\n",
-    "    out_pl.clear_output()\n",
-    "    if can_display:\n",
-    "        # Use display if available\n",
-    "        with out_pl:\n",
-    "            display(img.to_thumb(128, 128))\n",
-    "    else:\n",
-    "        # Save to a file if display is not available\n",
-    "        img.to_thumb(128, 128).save('output_thumbnail.png')\n",
-    "        print(\"Thumbnail saved to 'output_thumbnail.png'.\")\n",
-    "    \n",
-    "    # Assuming learn_inf is already defined and loaded elsewhere in your code\n",
-    "    pred, pred_idx, probs = learn_inf.predict(img)\n",
-    "    return f'Prediction: {pred}; Probability: {probs[pred_idx]:.04f}'"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 62,
    "id": "936e0aa5-4344-4b86-9e7d-b21adbd6b5ab",
    "metadata": {},
    "outputs": [],
@@ -229,7 +191,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 63,
    "id": "3bb8c7a0-3fb4-4fbb-9361-c62095a541a8",
    "metadata": {},
    "outputs": [],
@@ -239,15 +201,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
-   "id": "a6e2a398-f6c8-4444-b0f2-e538a1b36da2",
+   "execution_count": 64,
+   "id": "ae0492e9-9981-4fa9-b97c-76d65d4a0206",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Running on local URL:  http://127.0.0.1:7866\n",
+      "Running on local URL:  http://127.0.0.1:7867\n",
       "\n",
       "To create a public link, set `share=True` in `launch()`.\n"
      ]
@@ -256,13 +218,79 @@
      "data": {
       "text/plain": []
      },
-     "execution_count": 48,
+     "execution_count": 64,
      "metadata": {},
      "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
+       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
     "#|export\n",
+    "from PIL import Image\n",
+    "import ipywidgets as widgets\n",
+    "\n",
+    "# Optional: Import display only if in an IPython environment\n",
+    "try:\n",
+    "    from IPython.display import display\n",
+    "    can_display = True\n",
+    "except ImportError:\n",
+    "    can_display = False\n",
+    "\n",
+    "def on_click_classify(img_array):\n",
+    "    # Convert numpy array to PIL Image\n",
+    "    img = Image.fromarray(img_array.astype('uint8'), 'RGB')\n",
+    "    \n",
+    "    out_pl = widgets.Output()\n",
+    "    out_pl.clear_output()\n",
+    "    if can_display:\n",
+    "        # Use display if available\n",
+    "        with out_pl:\n",
+    "            display(img.to_thumb(128, 128))\n",
+    "    else:\n",
+    "        # Save to a file if display is not available\n",
+    "        img.to_thumb(128, 128).save('output_thumbnail.png')\n",
+    "        print(\"Thumbnail saved to 'output_thumbnail.png'.\")\n",
+    "    \n",
+    "    # Assuming learn_inf is already defined and loaded elsewhere in your code\n",
+    "    pred, pred_idx, probs = learn_inf.predict(img)\n",
+    "    return f'Prediction: {pred}; Probability: {probs[pred_idx]:.04f}'\n",
+    "\n",
     "image = gr.Image()\n",
     "label = gr.Label()\n",
     "examples = ['Adi_trainers.jpg', 'Nike_trainers.jpg', 'Puma_trainers.jpg', 'Adidas_trainers.jpg']\n",
@@ -281,7 +309,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 65,
    "id": "f5c57105-41fe-4d79-a2b0-d52ed75ea6cb",
    "metadata": {},
    "outputs": [