autogenerated app.py

app.py

@@ -1,28 +1,30 @@
-# AUTOGENERATED! DO NOT EDIT! File to edit: . (unless otherwise specified).
+# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
 
-__all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
+# %% auto 0
+__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image']
 
-# Cell
+# %% app.ipynb 2
 from fastai.vision.all import *
 from huggingface_hub import push_to_hub_fastai, from_pretrained_fastai
 import gradio as gr
 
 def is_cat(x): return x[0].isupper()
 
-# Cell
-learn = from_pretrained_fastai("fastai/cat_or_dog")
+# %% app.ipynb 7
+#learn = from_pretrained_fastai("fastai/cat_or_dog")
+learn = load_learner('model.pkl')
 
-# Cell
+# %% app.ipynb 9
 categories = ('Dog', 'Cat')
 
-def classify_image(img):
+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()
+# %% app.ipynb 11
+image = gr.Image(height=512, width=512)
+label = gr.Label()
 examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']
 
 intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
-intf.launch()
+intf.launch()