Updating app

app.py

@@ -14,12 +14,12 @@ def is_cat(x):
 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')
+categories = ('Abyssian', 'American Bulldog', 'American Pit Bull Terrier', 'Basset Hound', 'Beagle','Bengal',
+                'Birman', 'Bombay', 'Boxer','British Shorthair', 'Chihuahua',
+            'Egyptian Mau', 'English Cocker Spaniel', 'English Setter', 'German Shorthaired', 'Great Pyrenees', 'Havanese', 'Japanese Chin', 
+            'Keeshond', 'Leonberger', 'Main Coon', 'Miniature Pinscher', 'Newfoundland', 'Persian', 'Pomeranian', 'Pug', 'Ragdoll', 'Russian Blue', 
+            'St.Bernard', 'Samyoed', 'Scottish Terrier', 'Shiba Inu', 'Siamese', 'Sphynx',  
+             'Staffordshire Bull Terrier', 'Wheaten Terrier', 'Yorkshire Terrier')
 
 def classify_image(img):
     pred, idx, probs = learn.predict(img)