Move app.py to root

app.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 112,
+   "execution_count": 124,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 113,
+   "execution_count": 125,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -30,7 +30,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 114,
+   "execution_count": 126,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -41,7 +41,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 115,
+   "execution_count": 127,
    "metadata": {},
    "outputs": [
     {
@@ -52,7 +52,7 @@
        "PILImage mode=RGB size=192x128"
       ]
      },
-     "execution_count": 115,
+     "execution_count": 127,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -65,7 +65,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 116,
+   "execution_count": 128,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -75,7 +75,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 117,
+   "execution_count": 129,
    "metadata": {},
    "outputs": [
     {
@@ -121,7 +121,7 @@
        "('gym', tensor(0), tensor([1.0000e+00, 6.7478e-07]))"
       ]
      },
-     "execution_count": 117,
+     "execution_count": 129,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -132,7 +132,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 118,
+   "execution_count": 130,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -146,7 +146,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 119,
+   "execution_count": 131,
    "metadata": {},
    "outputs": [
     {
@@ -192,7 +192,7 @@
        "{'Gym Ryan': 0.9999992847442627, 'Jim Ryan': 6.747773682036495e-07}"
       ]
      },
-     "execution_count": 119,
+     "execution_count": 131,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -203,7 +203,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 120,
+   "execution_count": 132,
    "metadata": {},
    "outputs": [
     {
@@ -224,7 +224,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Running on local URL:  http://127.0.0.1:7864\n",
+      "Running on local URL:  http://127.0.0.1:7865\n",
       "\n",
       "To create a public link, set `share=True` in `launch()`.\n"
      ]
@@ -233,7 +233,7 @@
      "data": {
       "text/plain": []
      },
-     "execution_count": 120,
+     "execution_count": 132,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -257,21 +257,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 121,
+   "execution_count": 133,
    "metadata": {},
    "outputs": [],
    "source": [
     "# run pip install nbdev on local venv before running this\n",
     "import nbdev\n",
-    "nbdev.export.nb_export('app.ipynb', 'app')"
+    "nbdev.export.nb_export('app.ipynb', '.')"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {

app/app.py → app.py

@@ -1,23 +1,23 @@
-# AUTOGENERATED! DO NOT EDIT! File to edit: ../app.ipynb.
+# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
 
 # %% auto 0
 __all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'classify_image']
 
-# %% ../app.ipynb 1
+# %% app.ipynb 1
 from fastai.vision.all import *
 import gradio as gr
 
-# %% ../app.ipynb 5
+# %% app.ipynb 5
 learn = load_learner('model.pkl')
 
-# %% ../app.ipynb 7
+# %% app.ipynb 7
 categories = ('Gym Ryan', 'Jim Ryan')
 
 def classify_image(img):
     pred,idx,probs = learn.predict(img)
     return dict(zip(categories, map(float,probs)))
 
-# %% ../app.ipynb 9
+# %% app.ipynb 9
 image = gr.inputs.Image(shape=(192,192))
 label = gr.outputs.Label()
 examples = ['images/jim1.jpg',