add cat and dog pet classifier

.ipynb_checkpoints/app-checkpoint.ipynb

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+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

app.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "e49d72ea",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#|default_exp app"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "6ffe5ce8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#|export\n",
+    "# write this at the top of each cell which has to be exported to final script"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "dd7a7a33",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#|export\n",
+    "from fastai.vision.all import *"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "501504ae",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#|export\n",
+    "# this identifies the type of classifier\n",
+    "learn = load_learner('export.pkl')\n",
+    "labels = learn.dls.vocab\n",
+    "def predict(img):\n",
+    "    img = PILImage.create(img)\n",
+    "    pred,pred_idx,probs = learn.predict(img)\n",
+    "    return {labels[i]: float(probs[i]) for i in range(len(labels))}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "bbedafc3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/gilopez/mambaforge/envs/fastai/lib/python3.9/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",
+      "/home/gilopez/mambaforge/envs/fastai/lib/python3.9/site-packages/gradio/deprecation.py:40: UserWarning: `optional` parameter is deprecated, and it has no effect\n",
+      "  warnings.warn(value)\n",
+      "/home/gilopez/mambaforge/envs/fastai/lib/python3.9/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",
+      "/home/gilopez/mambaforge/envs/fastai/lib/python3.9/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",
+      "Running on public URL: https://28738.gradio.app\n",
+      "\n",
+      "This share link expires in 72 hours. For free permanent hosting, check out Spaces: https://huggingface.co/spaces\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"https://28738.gradio.app\" width=\"900\" height=\"500\" allow=\"autoplay; camera; microphone;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(<gradio.routes.App at 0x7f8dee0aaeb0>,\n",
+       " 'http://127.0.0.1:7860/',\n",
+       " 'https://28738.gradio.app')"
+      ]
+     },
+     "execution_count": 5,
+     "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"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Traceback (most recent call last):\n",
+      "  File \"/home/gilopez/mambaforge/envs/fastai/lib/python3.9/site-packages/PIL/Image.py\", line 3096, in open\n",
+      "    fp.seek(0)\n",
+      "AttributeError: 'NoneType' object has no attribute 'seek'\n",
+      "\n",
+      "During handling of the above exception, another exception occurred:\n",
+      "\n",
+      "Traceback (most recent call last):\n",
+      "  File \"/home/gilopez/mambaforge/envs/fastai/lib/python3.9/site-packages/gradio/routes.py\", line 268, in run_predict\n",
+      "    output = await app.blocks.process_api(\n",
+      "  File \"/home/gilopez/mambaforge/envs/fastai/lib/python3.9/site-packages/gradio/blocks.py\", line 748, in process_api\n",
+      "    result = await self.call_function(fn_index, inputs, iterator)\n",
+      "  File \"/home/gilopez/mambaforge/envs/fastai/lib/python3.9/site-packages/gradio/blocks.py\", line 627, in call_function\n",
+      "    prediction = await anyio.to_thread.run_sync(\n",
+      "  File \"/home/gilopez/mambaforge/envs/fastai/lib/python3.9/site-packages/anyio/to_thread.py\", line 31, in run_sync\n",
+      "    return await get_asynclib().run_sync_in_worker_thread(\n",
+      "  File \"/home/gilopez/mambaforge/envs/fastai/lib/python3.9/site-packages/anyio/_backends/_asyncio.py\", line 937, in run_sync_in_worker_thread\n",
+      "    return await future\n",
+      "  File \"/home/gilopez/mambaforge/envs/fastai/lib/python3.9/site-packages/anyio/_backends/_asyncio.py\", line 867, in run\n",
+      "    result = context.run(func, *args)\n",
+      "  File \"<ipython-input-4-7102b1720f8e>\", line 5, in predict\n",
+      "    img = PILImage.create(img)\n",
+      "  File \"/home/gilopez/mambaforge/envs/fastai/lib/python3.9/site-packages/fastai/vision/core.py\", line 123, in create\n",
+      "    return cls(load_image(fn, **merge(cls._open_args, kwargs)))\n",
+      "  File \"/home/gilopez/mambaforge/envs/fastai/lib/python3.9/site-packages/fastai/vision/core.py\", line 98, in load_image\n",
+      "    im = Image.open(fn)\n",
+      "  File \"/home/gilopez/mambaforge/envs/fastai/lib/python3.9/site-packages/PIL/Image.py\", line 3098, in open\n",
+      "    fp = io.BytesIO(fp.read())\n",
+      "AttributeError: 'NoneType' object has no attribute 'read'\n"
+     ]
+    },
+    {
+     "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"
+    },
+    {
+     "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",
+    "import gradio as gr\n",
+    "gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "321e5e2a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "eab7bd30",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "aab565a0",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1f6ef9c6",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0d8b4820",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "29bc0545",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "eec30b86",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "da262cb1",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1c886008",
+   "metadata": {},
+   "source": [
+    "## export notebook"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "e8b709a5",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ImportError",
+     "evalue": "cannot import name 'notebook2script' from 'nbdev.export' (/home/gilopez/mambaforge/envs/fastai/lib/python3.9/site-packages/nbdev/export.py)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mImportError\u001b[0m                               Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn [10], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# export notebook\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mnbdev\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mexport\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m notebook2script\n",
+      "\u001b[0;31mImportError\u001b[0m: cannot import name 'notebook2script' from 'nbdev.export' (/home/gilopez/mambaforge/envs/fastai/lib/python3.9/site-packages/nbdev/export.py)"
+     ]
+    }
+   ],
+   "source": [
+    "# export notebook\n",
+    "from nbdev.export import notebook2script"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "582eea60",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'notebook2script' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn [9], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mnotebook2script\u001b[49m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mapp.ipynb\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'notebook2script' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "notebook2script('app.ipynb')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1626b5fd",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "fastai",
+   "language": "python",
+   "name": "fastai"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

export.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8ff1e9a7925b9798c26b56763db26b7f8aabf3accd2a2aebb4902d9f0b56cf2c
+size 103045461

learning_gradio/app.py

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+# AUTOGENERATED! DO NOT EDIT! File to edit: ../app.ipynb.
+
+# %% auto 0
+__all__ = ['learn', 'labels', 'predict']
+
+# %% ../app.ipynb 1
+# write this at the top of each cell which has to be exported to final script
+
+# %% ../app.ipynb 2
+from fastai.vision.all import *
+
+# %% ../app.ipynb 3
+# this identifies the type of classifier
+learn = load_learner('export.pkl')
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+# %% ../app.ipynb 4
+import gradio as gr
+gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)