Update app.py

app.py

@@ -47,17 +47,13 @@ def predict_image(input_img_pil):
 
         # 3. Prediction
         print(f"Array shape for model input: {img_array.shape}")
-        predictions = model.predict(img_array)[0] # Get the single prediction result
+        predictions = model.predict(img_array) # Get the single prediction result
         print(f"Raw model predictions: {predictions}")
 
         # 4. Format the output for Gradio's Label component
         # Assuming predictions is a 2-element array: [prob_cat, prob_dog]
-        output_dict = {
-            CLASS_LABELS[0]: float(predictions[0]),
-            CLASS_LABELS[1]: float(predictions[1])
-        }
         
-        return output_dict
+        return predictions
     
     except Exception as e:
         # Catch any error, log it, and return it to the user in a visible format