[Fix] for working in windows sys

Bearify_nb.ipynb

@@ -35,7 +35,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 3,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -53,7 +53,7 @@
        "PILImage mode=RGB size=192x128"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -66,10 +66,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
+    "#|export\n",
     "import pathlib\n",
     "temp = pathlib.PosixPath\n",
     "pathlib.PosixPath = pathlib.WindowsPath"
@@ -77,7 +78,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {
     "id": "Ko1vxtuzACNo"
    },
@@ -87,6 +88,16 @@
     "learn = load_learner('bear_model.pkl')"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#|export\n",
+    "pathlib.PosixPath = temp"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 7,
@@ -128,7 +139,14 @@
     },
     {
      "data": {
-      "text/html": [],
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='0' class='' max='1' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      0.00% [0/1 00:00&lt;?]\n",
+       "    </div>\n",
+       "    "
+      ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
       ]
@@ -139,7 +157,7 @@
     {
      "data": {
       "text/plain": [
-       "('teddy', tensor(2), tensor([1.0445e-04, 5.7532e-07, 9.9989e-01]))"
+       "('black', tensor(0), tensor([9.9997e-01, 2.5549e-05, 4.9422e-07]))"
       ]
      },
      "execution_count": 7,
@@ -153,7 +171,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 8,
    "metadata": {
     "id": "k8MzL29fm5wO"
    },
@@ -169,7 +187,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 9,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -224,7 +242,7 @@
        " 'Teddy': 4.94215839808021e-07}"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -235,7 +253,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": null,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/",
@@ -249,7 +267,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Running on local URL:  http://127.0.0.1:7865\n",
+      "Running on local URL:  http://127.0.0.1:7860\n",
       "\n",
       "To create a public link, set `share=True` in `launch()`.\n"
      ]
@@ -258,7 +276,7 @@
      "data": {
       "text/plain": []
      },
-     "execution_count": 31,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -321,7 +339,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -351,9 +369,9 @@
    "provenance": []
   },
   "kernelspec": {
-   "display_name": "bear_env",
+   "display_name": "bear_gh_env",
    "language": "python",
-   "name": "bear_env"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -365,7 +383,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

app.py

@@ -1,23 +1,31 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../Bearify_nb.ipynb.
 
 # %% auto 0
-__all__ = ['learn', 'categories', 'image', 'labels', 'examples', 'intf', 'classify_image']
+__all__ = ['temp', 'learn', 'categories', 'image', 'labels', 'examples', 'intf', 'classify_image']
 
 # %% ../Bearify_nb.ipynb 2
 from fastai.vision.all import *
 import gradio as gr
 
+# %% ../Bearify_nb.ipynb 4
+import pathlib
+temp = pathlib.PosixPath
+pathlib.PosixPath = pathlib.WindowsPath
+
 # %% ../Bearify_nb.ipynb 5
 learn = load_learner('bear_model.pkl')
 
-# %% ../Bearify_nb.ipynb 7
+# %% ../Bearify_nb.ipynb 6
+pathlib.PosixPath = temp
+
+# %% ../Bearify_nb.ipynb 8
 categories = ('Black', 'Grizzly', 'Teddy')
 
 def classify_image(img):
   pred, idx, probs = learn.predict(img)
   return dict(zip(categories, map(float, probs)))
 
-# %% ../Bearify_nb.ipynb 9
+# %% ../Bearify_nb.ipynb 10
 image = gr.Image()
 labels = gr.Label()
 examples = ['Images/teddy.jpg', 'Images/grizzly.jpg', 'Images/black.jpeg']