added pred categories

app.py

@@ -3,10 +3,16 @@ import gradio as gr
 
 learn = load_learner('petClassifierModel.pkl')
 
-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", "Saint Bernard", "Samyoed", "Scottish Terrier", "Shiba Inu", "Staffordshire Bull Terrier")
 
-def greet(name):
-    return "Hello " + name + "!!"
+categories = learn.dls.vocab
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+def classify_image(img):
+    pred, idx, probs = learn.predict(img)
+    return dict(zip(categories(map(float, probs))))
+
+image = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label()
+
+
+iface = gr.Interface(fn=classify_image, inputs="image", outputs="label")
 iface.launch()