Update app.py

app.py

@@ -1,46 +1,27 @@
-#import subprocess
-#import sys
+# AUTOGENERATED! DO NOT EDIT! File to edit: . (unless otherwise specified).
 
-#def install(package):
-#    subprocess.check_call([sys.executable, "-m", "pip", "install", package])
-
-#install('fastbook')
-
-
-import pathlib 
-import platform
-plt = platform.system()
-if plt == 'Windows':
-    pathlib.WindowsPath = pathlib.PosixPath
-    
-# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
-
-# %% auto 0
-__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'interface', 'classify_image']
-
-# %% app.ipynb 1
-#from fastbook import *
+__all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
 
+# Cell
 from fastai.vision.all import *
-from fastai.vision.widgets import ImageClassifierCleaner
-
 import gradio as gr
 
-# %% app.ipynb 2
-learn = load_learner('./model.pkl')
+def is_cat(x): return x[0].isupper()
 
-# %% app.ipynb 3
-categories=('bird','forest')
+# Cell
+learn = load_learner('model.pkl')
 
-def classify_image(img):
-    pred,indx,probs=learn.predict(img)
-    return dict(zip(categories,map(float,probs)))
+# Cell
+categories = ('Dog', 'Cat')
 
+def classify_image(img):
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories, map(float,probs)))
 
-# %% app.ipynb 4
-image=gr.inputs.Image(shape=(192,192))
-label=gr.outputs.Label()
-examples=['a.jpg', 'b.jpg','c.jpg','d.jpg']
+# Cell
+image = gr.inputs.Image(shape=(192, 192))
+label = gr.outputs.Label()
+examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']
 
-interface=gr.Interface(fn=classify_image, inputs=image ,outputs=label,examples=examples)
-interface.launch(inline=False)
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)