- test deploy 1

.gitattributes

@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+giant_0.jpg filter=lfs diff=lfs merge=lfs -text
+giant_1.jpg filter=lfs diff=lfs merge=lfs -text
+red_0.jpg filter=lfs diff=lfs merge=lfs -text
+red_1.jpg filter=lfs diff=lfs merge=lfs -text

app.ipynb

@@ -0,0 +1,134 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#| default_exp app"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "d:\\miniconda3\\envs\\fai\\Lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "#| export\n",
+    "from fastai.vision.all import *\n",
+    "import gradio as gr\n",
+    "\n",
+    "# def is_giant_panda(x): return x[0].isupper()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "im = PILImage.create('giant_0.jpg')\n",
+    "im = im.to_thumb(192)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#| export\n",
+    "learn = load_learner('model.pkl')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn.predict(im)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#| export\n",
+    "categories = 'Giant panda', 'Red panda'\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": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "classify_image(im)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#| export\n",
+    "image = gr.inputs.Image(shape=(192, 192))\n",
+    "label = gr.outputs.Label()\n",
+    "\n",
+    "examples = ['giant_0.jpg', 'red_0.jpg', 'giant_1.jpg', 'red_1.jpg']\n",
+    "interface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
+    "interface.launch(inline=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from nbdev.export import notebook2script\n",
+    "\n",
+    "notebook2script('app.ipynb')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "fai",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

app.py

@@ -1,7 +1,17 @@
+from fastai.vision.all import *
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+categories = 'Giant panda', 'Red panda'
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+def classify_image(img):
+    pred, idx, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+learn = load_learner('model.pkl')
+
+image = gr.inputs.Image(shape=(192, 192))
+label = gr.outputs.Label()
+
+examples = ['giant_0.jpg', 'red_0.jpg', 'giant_1.jpg', 'red_1.jpg']
+interface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+interface.launch(inline=False)

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d4baab030dd958a944a65758fc8848880ce0d0a96dbad1661ec9a17592ebc2ac
+size 46964486