8 files test

.gitattributes

@@ -33,3 +33,4 @@ 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
+cat.jpg filter=lfs diff=lfs merge=lfs -text

app.ipynb

@@ -0,0 +1,163 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from fastai.vision.all import *\n",
+    "import gradio as gr\n",
+    "import pathlib\n",
+    "temp = pathlib.PosixPath\n",
+    "pathlib.PosixPath = pathlib.WindowsPath\n",
+    "\n",
+    "def is_cat(x): return x[0].isupper()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn = load_learner('model.pkl')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "categories = ('Dog', 'Cat')\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": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\Lenovo\\AppData\\Local\\Temp\\ipykernel_16112\\1698676069.py:1: GradioDeprecationWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n",
+      "  image = gr.inputs.Image(shape=(192, 192))\n",
+      "C:\\Users\\Lenovo\\AppData\\Local\\Temp\\ipykernel_16112\\1698676069.py:1: GradioDeprecationWarning: `optional` parameter is deprecated, and it has no effect\n",
+      "  image = gr.inputs.Image(shape=(192, 192))\n",
+      "C:\\Users\\Lenovo\\AppData\\Local\\Temp\\ipykernel_16112\\1698676069.py:2: GradioDeprecationWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n",
+      "  label = gr.outputs.Label()\n",
+      "C:\\Users\\Lenovo\\AppData\\Local\\Temp\\ipykernel_16112\\1698676069.py:2: GradioUnusedKwargWarning: You have unused kwarg parameters in Label, please remove them: {'type': 'auto'}\n",
+      "  label = gr.outputs.Label()\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": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "image = gr.inputs.Image(shape=(192, 192))\n",
+    "label = gr.outputs.Label()\n",
+    "examples = ['dog.jpg', 'cat.jpg', 'dunno.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": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import nbdev\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\Lenovo\\Desktop\\fastaiTesting\\testai\n"
+     ]
+    }
+   ],
+   "source": [
+    "import os\n",
+    "print(os.getcwd())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "nbdev.export.nb_export('app.ipynb', r'C:\\Users\\Lenovo\\Desktop\\fastaiTesting\\testai')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\Lenovo\\miniconda3\\envs\\pytorch\\python.exe\n"
+     ]
+    }
+   ],
+   "source": [
+    "import sys\n",
+    "\n",
+    "print(sys.executable)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.8.17"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

app.py

@@ -0,0 +1,27 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: . (unless otherwise specified).
+
+__all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
+
+# Cell
+from fastai.vision.all import *
+import gradio as gr
+
+def is_cat(x): return x[0].isupper()
+
+# Cell
+learn = load_learner('model.pkl')
+
+# Cell
+categories = ('Dog', 'Cat')
+
+def classify_image(img):
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories, map(float,probs)))
+
+# Cell
+image = gr.inputs.Image(shape=(192, 192))
+label = gr.outputs.Label()
+examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:46eee60a5eac1402f8402ce1915230e6ca75d8d05c35c4e9500eadf2e39c525a
+size 47062827

requirements.txt

@@ -0,0 +1,2 @@
+fastai
+