Update app.py

app.py

@@ -1,31 +1,45 @@
-# AUTOGENERATED! DO NOT EDIT! File to edit: . (unless otherwise specified).
-
-__all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
 import platform
 import pathlib
 plt = platform.system()
 pathlib.WindowsPath = pathlib.PosixPath
-    
-# Cell
+
+#import subprocess
+#import sys
+
+#def install(package):
+#    subprocess.check_call([sys.executable, "-m", "pip", "install", package])
+
+#install('fastbook')
+
+
+# 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 *
+
 from fastai.vision.all import *
-import gradio as gr
+from fastai.vision.widgets import ImageClassifierCleaner
 
-def is_cat(x): return x[0].isupper()
+import gradio as gr
 
-# Cell
-learn = load_learner('model.pkl')
+# %% app.ipynb 2
+learn = load_learner('./model.pkl')
 
-# Cell
-categories = ('Dog', 'Cat')
+# %% app.ipynb 3
+categories=('bird','forest')
 
 def classify_image(img):
-    pred,idx,probs = learn.predict(img)
-    return dict(zip(categories, map(float,probs)))
+    pred,indx,probs=learn.predict(img)
+    return dict(zip(categories,map(float,probs)))
+
 
-# Cell
-image = gr.inputs.Image(shape=(192, 192))
-label = gr.outputs.Label()
-examples = ['a.jpg', 'b.jpg', 'c.jpg']
+# %% app.ipynb 4
+image=gr.inputs.Image(shape=(192,192))
+label=gr.outputs.Label()
+examples=['a.jpg', 'b.jpg','c.jpg','d.jpg']
 
-intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
-intf.launch(inline=False)
+interface=gr.Interface(fn=classify_image, inputs=image ,outputs=label,examples=examples)
+interface.launch(inline=False)