Update app.py

UX updated, added confidence labels for the output components

app.py

@@ -21,6 +21,8 @@ def predict(image):
     # Apply the threshold
     threshold = 0.570
     classes_with_probs = [(learn.dls.vocab[i], probs[i].item()) for i in range(len(mask)) if probs[i] > threshold]
+    confidences = {learn.dls.vocab[i]: float(probs[i].item()) for i in range(len(probs)) if probs[i] > threshold}
+
 
     # Check if the prediction includes "dog" or "cat"
     pet_type = None
@@ -42,14 +44,14 @@ def predict(image):
     result = f"This is a {pet_type}, the breed is {breed if breed else 'unknown'}.\n" \
              f"The probability for it being a {pet_type} is {pet_prob * 100:.2f}%, the probability of being the breed is {breed_prob * 100:.2f}%."
 
-    return result
+    return result, confidences
 
 
 # Define the Gradio interface
 iface = gr.Interface(
     fn=predict,
     inputs=gr.inputs.Image(shape=(224, 224)),
-    outputs="text",
+    outputs=[gr.outputs.Textbox(label="Prediction"), gr.outputs.Label(label='confidences',num_top_classes=2)],
     live=True,
     theme="gradio/monochrome",
     title="Cat and Dog Image Classifier",