update from pets repo

app.py

@@ -1,29 +1,25 @@
+__all__ = ['learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
+
+# Cell
 from fastai.vision.all import *
 import gradio as gr
+import timm
 
-def is_cat(x): return x[0].isupper()
-
-# im = PILIMage.create('dog.jpg')
-# im.thumbnail((192,192))
-# im
-
+# Cell
 learn = load_learner('model.pkl')
-# learn.predict(im)
 
-categories = ('Dog', 'Cat')
+# Cell
+categories = learn.dls.vocab
+
 def classify_image(img):
     pred,idx,probs = learn.predict(img)
-    return dict(zip(categories, map(float, probs)))
-
-# def greet(name):
-#     return "Hello " + name + "!!"
-
-# iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-# iface.launch()
+    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']
+examples = ['dog.jpg']
 
-iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
-iface.launch(inline=False)
+# Cell
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch()

requirements.txt

@@ -1,5 +1,5 @@
-fastai
-torch==1.12.1
-gradio
-numpy
-pandas <2.0.0
+fastai==2.7.12
+gradio==3.34.0
+timm==0.9.2
+torch==2.0.1
+torchvision==0.15.2