Add gradio interface

app.ipynb

@@ -22,9 +22,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#|export\n",
+    "# |export\n",
     "from fastai.vision.all import *\n",
-    "import gradio as gr"
+    "import gradio as gr\n"
    ]
   },
   {
@@ -33,8 +33,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#|export\n",
-    "learn = load_learner('model.pkl')"
+    "# |export\n",
+    "learn = load_learner('model.pkl')\n"
    ]
   },
   {
@@ -56,8 +56,8 @@
    ],
    "source": [
     "im = PILImage.create('images/ash.jpg')\n",
-    "im.thumbnail((224,224))\n",
-    "im"
+    "im.thumbnail((224, 224))\n",
+    "im\n"
    ]
   },
   {
@@ -122,7 +122,7 @@
     }
    ],
    "source": [
-    "%time learn.predict(im)"
+    "%time learn.predict(im)\n"
    ]
   },
   {
@@ -142,7 +142,7 @@
     }
    ],
    "source": [
-    "learn.dls.vocab"
+    "learn.dls.vocab\n"
    ]
   },
   {
@@ -151,14 +151,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#|export\n",
-    "# NOTE: Put in alphabetical order\n",
+    "# |export\n",
+    "\n",
     "categories = ('ash', 'chestnut', 'ginkgo biloba', 'silver maple', 'willow oak')\n",
     "\n",
+    "\n",
     "def classify_image(img):\n",
     "  pred, idx, probs = learn.predict(img)\n",
     "  # Change each probability to a float, since Gradio doesn't support Tensors or NumPy\n",
-    "  return dict(zip(categories, map(float, probs)))"
+    "  return dict(zip(categories, map(float, probs)))\n"
    ]
   },
   {
@@ -222,6 +223,63 @@
     "classify_image(im)"
    ]
   },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# gradio interface"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/briansigafoos/mambaforge/lib/python3.10/site-packages/gradio/inputs.py:256: UserWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n",
+      "  warnings.warn(\n",
+      "/Users/briansigafoos/mambaforge/lib/python3.10/site-packages/gradio/deprecation.py:40: UserWarning: `optional` parameter is deprecated, and it has no effect\n",
+      "  warnings.warn(value)\n",
+      "/Users/briansigafoos/mambaforge/lib/python3.10/site-packages/gradio/outputs.py:196: UserWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n",
+      "  warnings.warn(\n",
+      "/Users/briansigafoos/mambaforge/lib/python3.10/site-packages/gradio/deprecation.py:40: UserWarning: The 'type' parameter has been deprecated. Use the Number component instead.\n",
+      "  warnings.warn(value)\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7860\n",
+      "\n",
+      "To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# |export\n",
+    "image = gr.inputs.Image(shape=(192, 192))\n",
+    "label = gr.outputs.Label()\n",
+    "examples = ['images/ash.jpg', 'images/chestnut.jpg', 'images/ginkgo_biloba.jpg',\n",
+    "            'images/silver_maple.jpg', 'images/willow_oak.jpg']\n",
+    "\n",
+    "interface = gr.Interface(fn=classify_image, inputs=image,\n",
+    "                         outputs=label, examples=examples)\n",
+    "interface.launch(inline=False)\n"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -231,7 +289,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [
     {
@@ -246,7 +304,7 @@
     "from nbdev.export import nb_export\n",
     "\n",
     "nb_export('app.ipynb', './')\n",
-    "print('Export successful')"
+    "print('Export successful')\n"
    ]
   },
   {

app.py

@@ -1,20 +1,34 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
 
 # %% auto 0
-__all__ = ['learn', 'categories', 'classify_image']
+__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'interface', 'classify_image']
 
 # %% app.ipynb 2
 from fastai.vision.all import *
 import gradio as gr
 
+
 # %% app.ipynb 3
 learn = load_learner('model.pkl')
 
+
 # %% app.ipynb 7
-# NOTE: Put in alphabetical order
 categories = ('ash', 'chestnut', 'ginkgo biloba', 'silver maple', 'willow oak')
 
+
 def classify_image(img):
   pred, idx, probs = learn.predict(img)
   # Change each probability to a float, since Gradio doesn't support Tensors or NumPy
   return dict(zip(categories, map(float, probs)))
+
+
+# %% app.ipynb 10
+image = gr.inputs.Image(shape=(192, 192))
+label = gr.outputs.Label()
+examples = ['images/ash.jpg', 'images/chestnut.jpg', 'images/ginkgo_biloba.jpg',
+            'images/silver_maple.jpg', 'images/willow_oak.jpg']
+
+interface = gr.Interface(fn=classify_image, inputs=image,
+                         outputs=label, examples=examples)
+interface.launch(inline=False)
+