Update app.py

app.py

@@ -195,7 +195,7 @@ def predict_classification(image, show_gradcam):
     """업로드된 이미지를 분류하고, 선택 시 Grad-CAM 결과까지 함께 반환한다."""
     # 이미지가 없으면 Gradio 출력 개수에 맞춰 빈 결과를 반환한다.
     if image is None:
-        return None, "Please upload an image.", {}, []
+        return None, "Please upload an image.", []
 
     runtime = get_classification_runtime()
     params = runtime["params"]
@@ -226,10 +226,10 @@ def predict_classification(image, show_gradcam):
     top_probs = top_probs.detach().cpu().tolist()
     top_indices = top_indices.detach().cpu().tolist()
 
-    confidences = {
-        class_names[idx]: float(prob)
-        for idx, prob in zip(top_indices, top_probs)
-    }
+    # confidences = {
+    #     class_names[idx]: float(prob)
+    #     for idx, prob in zip(top_indices, top_probs)
+    # }
 
     predicted_idx = top_indices[0]
     predicted_label = class_names[predicted_idx]
@@ -262,7 +262,7 @@ def predict_classification(image, show_gradcam):
             device,
         )
 
-    return gradcam_image, summary, confidences, table
+    return gradcam_image, summary, table
 
 
 def caption_token_labels(generated_tokens, runtime, caption):