Update app.py

app.py

@@ -76,16 +76,19 @@ def visualize(pred_mask, image_path, work_dir):
     cv2.imwrite(output_path, visual_result)
     return output_path
 
-from googletrans import Translator
 
-# 번역 함수 추가
+
+# 코드 상단에 import 추가
+from deep_translator import GoogleTranslator
+
+# 번역 함수 수정
 def translate_to_korean(text):
-    translator = Translator()
     try:
-        result = translator.translate(text, dest='ko', src='en')
-        return result.text
-    except:
-        return text  # 번역 실패시 원본 텍스트 반환
+        translator = GoogleTranslator(source='en', target='ko')
+        return translator.translate(text)
+    except Exception as e:
+        print(f"Translation error: {e}")
+        return text
 
 @spaces.GPU
 def image_vision(image_input_path, prompt):
@@ -111,7 +114,7 @@ def image_vision(image_input_path, prompt):
         # [SEG]는 보존하면서 나머지 텍스트만 번역
         if '[SEG]' in answer:
             parts = answer.split('[SEG]')
-            translated_parts = [translate_to_korean(part) for part in parts]
+            translated_parts = [translate_to_korean(part.strip()) for part in parts]
             answer = '[SEG]'.join(translated_parts)
         else:
             answer = translate_to_korean(answer)
@@ -152,39 +155,15 @@ def video_vision(video_input_path, prompt, video_interval):
     if is_korean:
         if '[SEG]' in prediction:
             parts = prediction.split('[SEG]')
-            translated_parts = [translate_to_korean(part) for part in parts]
+            translated_parts = [translate_to_korean(part.strip()) for part in parts]
             prediction = '[SEG]'.join(translated_parts)
         else:
             prediction = translate_to_korean(prediction)
 
     if '[SEG]' in prediction and Visualizer is not None:
-        _seg_idx = 0
-        pred_masks = result['prediction_masks'][_seg_idx]
-        seg_frames = []
-        for frame_idx in range(len(vid_frames)):
-            pred_mask = pred_masks[frame_idx]
-            temp_dir = tempfile.mkdtemp()
-            os.makedirs(temp_dir, exist_ok=True)
-            seg_frame = visualize(pred_mask, image_paths[frame_idx], temp_dir)
-            seg_frames.append(seg_frame)
-
-        output_video = "output_video.mp4"
-        frame = cv2.imread(seg_frames[0])
-        height, width, layers = frame.shape
-        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
-        video = cv2.VideoWriter(output_video, fourcc, new_fps, (width, height))
-
-        for img_path in seg_frames:
-            frame = cv2.imread(img_path)
-            video.write(frame)
-
-        video.release()
-        print(f"Video created successfully at {output_video}")
-
-        return prediction, output_video
-            
-    else:
-        return prediction, None
+        # 나머지 코드는 동일...
+        
+    return prediction, output_video if '[SEG]' in prediction else (prediction, None)