Updating Application File

app.py

@@ -1,7 +1,33 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../app.ipynb.
+
+# %% auto 0
+__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'classify_image']
+
+# %% ../app.ipynb 0
+from fastai.vision.all import *
+import PIL
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+def is_cat(x):
+    return x[0].isupper()
+# %% ../app.ipynb 3
+learn = load_learner('model.pkl')
+
+# %% ../app.ipynb 5
+categories = ('American Bulldog', 'American Pit Bull Terrier', 'Basset Hound',
+            'Beagle', 'Boxer', 'Chihuahua', 'English Cocker Spaniel', 'English Setter', 'German Shorthaired', 
+            'Great Pyrenees', 'Havanese', 'Japanese Chin', 'Keeshond', 'Leonberger', 'Miniature Pinscher', 'Newfoundland',
+            'Pomeranian', 'Pug', 'St.Bernard', 'Samyoed', 'Scottish Terrier', 'Shiba Inu', 'Staffordshire Bull Terrier', 
+            'Wheaten Terrier', 'Yorkshire Terrier', 'Abyssian', 'Bengal', 'Birman', 'Bombay', 'British Shorthair',
+            'Egyptian Mau', 'Main Coon', 'Persian', 'Ragdoll', 'Russian Blue', 'Siamese', 'Sphynx')
+
+def classify_image(img):
+    pred, idx, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+# %% ../app.ipynb 
+image = gr.Image(shape=(192,192))
+label = gr.Label()
+examples = ['americanBulldog.jpg', 'bernard.jpg', 'ragdoll.jpg']
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)