use nbdev2, working now

app.py

@@ -1,20 +1,30 @@
-#!/usr/bin/env python3
+# AUTOGENERATED! DO NOT EDIT! File to edit: photo-checker.ipynb.
 
+# %% auto 0
+__all__ = ['learn', 'labels', 'iface', 'classify_image']
+
+# %% photo-checker.ipynb 5
 from fastai.vision.all import *
-import gradio as gr
 
+# %% photo-checker.ipynb 36
 learn = load_learner('photos.pkl')
+
+# %% photo-checker.ipynb 58
 labels = learn.dls.vocab
 
-def predict(img):
+# %% photo-checker.ipynb 60
+def classify_image(img):
 	img = PILImage.create(img)
-	pred, pred_idx, probs = learn.predict(img)
+	pred,idx,probs = learn.predict(img)
 	return dict(zip(labels, map(float, probs)))
 
+# %% photo-checker.ipynb 61
+import gradio as gr
+
 iface = gr.Interface(
 	title = "Photo Checker",
 	description = """This project checks which of our family photos are "good" or "bad". We have nearly 80,000 photos, so it's not practical to sort them out by hand. I want to exclude screenshots, photos of computer screens, photos of papers, images with lots of text, and very blurry images. I used this to separate the good photos to use for a random slide show on our TV. The trained model achieves around 99% accuracy on the validation set.""",
-	fn = predict,
+	fn = classify_image,
 	inputs = gr.inputs.Image(shape = (512,512)),
 	outputs = gr.outputs.Label(num_top_classes = 3),
 	examples = list(map(str, get_image_files('eg'))),

photo-checker.ipynb

@@ -36,7 +36,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 9,
    "metadata": {
     "tags": []
    },
@@ -48,7 +48,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -58,7 +58,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 11,
    "metadata": {
     "tags": []
    },
@@ -1293,28 +1293,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 12,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/usr/local/lib/python3.10/dist-packages/nbdev/export.py:54: UserWarning: Notebook 'photo-checker.ipynb' uses `#|export` without `#|default_exp` cell.\n",
-      "Note nbdev2 no longer supports nbdev1 syntax. Run `nbdev_migrate` to upgrade.\n",
-      "See https://nbdev.fast.ai/getting_started.html for more information.\n",
-      "  warn(f\"Notebook '{nbname}' uses `#|export` without `#|default_exp` cell.\\n\"\n"
-     ]
-    }
-   ],
+   "outputs": [],
+   "source": [
+    "#| default_exp app"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "from nbdev.export import nb_export\n",
-    "nb_export('photo-checker.ipynb')"
+    "nb_export('photo-checker.ipynb', '.')"
    ]
   },
   {
-   "cell_type": "raw",
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
+   "outputs": [],
    "source": []
   }
  ],