Update app.py

app.py

@@ -23,20 +23,20 @@ def classify_potato_plant(img):
     confidence = predictions[0][predicted_class]
     model_output = "None"
 
-    if class_labels[predicted_class] == "Potato__Early_blight":
+    if class_labels[predicted_class] == "Potato___Early_blight":
         model_output = "Early blight"
-    elif class_labels[predicted_class] == "Potato__Late_blight":
+    elif class_labels[predicted_class] == "Potato___Late_blight":
         model_output = "Late blight"
-    elif class_labels[predicted_class] == "Potato__healthy":
+    elif class_labels[predicted_class] == "Potato___healthy":
         model_output = "Healthy"
 
-    return class_labels[predicted_class], model_output, confidence
+    return model_output, confidence
 
 # Create the Gradio interface
 interface = gr.Interface(
     fn=classify_potato_plant,
     inputs=gr.Image(type="pil"),
-    outputs=[gr.Label(label="Predicted Classes", num_top_classes=3), gr.Textbox(label="Predicted Output"), gr.Textbox(label="Confidence Score")],
+    outputs=[gr.Textbox(label="Predicted Output"), gr.Textbox(label="Confidence Score")],
     title="Acres - PPDC",
     description="Acres PPDC, is our Potato Plant Disease Classification vision model, capable of accurately classifying potato plant disease, based on a single image."
 )