feat: included app

app/app.py

@@ -0,0 +1,28 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../broken_windows.ipynb.
+
+# %% auto 0
+__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_broken', 'classify_image']
+
+# %% ../broken_windows.ipynb 19
+from fastai.vision.all import *
+import gradio as gr
+
+def is_broken(x): return x[0].isupper()
+
+# %% ../broken_windows.ipynb 20
+learn = load_learner('model.pkl')
+
+# %% ../broken_windows.ipynb 21
+categories = ('Broken window', 'Not broken window')
+
+def classify_image(img):
+    pred, idx, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+# %% ../broken_windows.ipynb 22
+image = gr.Image()
+label = gr.Label()
+examples = ['window.jpg', 'broken_window.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)

broken_windows.ipynb

@@ -12,10 +12,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 18,
    "id": "a744c5f1-de6e-474a-9605-058b0bfdb6e3",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'ndev'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
+      "Cell \u001b[1;32mIn[18], line 4\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtime\u001b[39;00m\n\u001b[0;32m      3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtimm\u001b[39;00m\n\u001b[1;32m----> 4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mndev\u001b[39;00m\n\u001b[0;32m      6\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msearch_images\u001b[39m(term, max_images \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m250\u001b[39m):\n\u001b[0;32m      7\u001b[0m     url \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhttps://duckduckgo.com/\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
+      "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'ndev'"
+     ]
+    }
+   ],
    "source": [
     "from fastcore.all import *\n",
     "import time\n",
@@ -761,6 +773,137 @@
    "source": [
     "learn.export(\"model.pkl\")"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "83e6d420-50a9-440f-a176-62ae5c84c9e2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#|export\n",
+    "from fastai.vision.all import *\n",
+    "import gradio as gr\n",
+    "\n",
+    "def is_broken(x): return x[0].isupper()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "c8348e8a-596f-4048-963d-5e9a22f7b8c8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#|export\n",
+    "learn = load_learner('model.pkl')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "226796e5-f291-43e6-959b-33f5f1576f9e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#|export\n",
+    "categories = ('Broken window', 'Not broken window')\n",
+    "\n",
+    "def classify_image(img):\n",
+    "    pred, idx, probs = learn.predict(img)\n",
+    "    return dict(zip(categories, map(float, probs)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "bf76799e-8eaa-4842-b0aa-128cfd0f2e5a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7864\n",
+      "\n",
+      "To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 34,
+     "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",
+    "image = gr.Image()\n",
+    "label = gr.Label()\n",
+    "examples = ['odd_broken_window.jpg', 'broken_window.jpg', \"window_error.jpg\"]\n",
+    "\n",
+    "intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
+    "intf.launch(inline=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "12bfec97-5699-4fe8-ba7b-3a73fb09737f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import nbdev"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "2bdbc123-fda4-4311-9056-f72924770cdc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "nbdev.export.nb_export('broken_windows.ipynb', 'app')"
+   ]
   }
  ],
  "metadata": {