update script

app.py

@@ -7,60 +7,11 @@ __all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat'
 from fastai.vision.all import *
 import gradio as gr
 
-def is_cat(x): 
-    return x[0].isupper()
-
-# %% dog_v_cat.ipynb 2
-from fastai.vision.all import *
-import gradio as gr
-
-def is_cat(x): 
-    return x[0].isupper()
-
-# %% dog_v_cat.ipynb 4
-from fastai.vision.all import *
-import gradio as gr
-
-def is_cat(x): 
-    return x[0].isupper()
-
-# %% dog_v_cat.ipynb 6
-from fastai.vision.all import *
-import gradio as gr
-
-def is_cat(x): 
-    return x[0].isupper()
-
-# %% dog_v_cat.ipynb 7
-from fastai.vision.all import *
-import gradio as gr
-
-def is_cat(x): 
-    return x[0].isupper()
-
-# %% dog_v_cat.ipynb 8
-from fastai.vision.all import *
-import gradio as gr
-
-def is_cat(x): 
-    return x[0].isupper()
-
-# %% dog_v_cat.ipynb 9
-from fastai.vision.all import *
-import gradio as gr
-
-def is_cat(x): 
-    return x[0].isupper()
-
-# %% dog_v_cat.ipynb 10
-from fastai.vision.all import *
-import gradio as gr
-
 def is_cat(x): 
     return x[0].isupper()
 
 # %% dog_v_cat.ipynb 12
-learn = load_learner('/kaggle/input/models/model.pkl')
+learn = load_learner('model.pkl')
 
 # %% dog_v_cat.ipynb 14
 categories = ('Dog', 'Cat')
@@ -68,12 +19,6 @@ def classify_image(img):
     pred, idx, probs = learn.predict(img)
     return dict(zip(categories, map(float, probs)))
 
-# %% dog_v_cat.ipynb 16
-image = gr.inputs.Image(shape=(192,192))
-label = gr.outputs.Label()
-examples = ['/kaggle/input/dog-or-cat-test/dog.jpg','/kaggle/input/dog-or-cat-test/cat.jpg', '/kaggle/input/dog-or-cat-test/challenge.jpg']
-
-intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
 
 # %% dog_v_cat.ipynb 17
 image = gr.inputs.Image(shape=(192,192))