fixed some description issues

content_generator.py

@@ -15,7 +15,7 @@ class ContentGenerator:
         """初始化內容生成器"""
         self.logger = logging.getLogger(self.__class__.__name__)
 
-        # 預載入默認替換內容 
+        # 預載入默認替換內容
         self.default_replacements = self._generate_default_replacements()
 
         self.logger.debug("ContentGenerator initialized successfully")
@@ -238,7 +238,7 @@ class ContentGenerator:
             if not detected_objects:
                 return "various elements"
 
-            # 計算物件統計 
+            # 計算物件統計
             object_counts = {}
             total_confidence = 0
 
@@ -277,21 +277,40 @@ class ContentGenerator:
                 else:
                     descriptions.append(f"{count} {clean_name}s")
 
-            # 組合描述
-            if len(descriptions) == 1:
-                return descriptions[0]
-            elif len(descriptions) == 2:
-                return f"{descriptions[0]} and {descriptions[1]}"
+            # === 修正組合描述邏輯，增加驗證機制 ===
+            # 過濾掉空的或無效的描述
+            valid_descriptions = [desc.strip() for desc in descriptions if desc and desc.strip()]
+
+            # 確保有有效的描述項目
+            if not valid_descriptions:
+                return "various elements"
+
+            # 組合描述 - 修正邏輯以避免不完整的結尾
+            if len(valid_descriptions) == 1:
+                return valid_descriptions[0]
+            elif len(valid_descriptions) == 2:
+                return f"{valid_descriptions[0]} and {valid_descriptions[1]}"
             else:
-                return ", ".join(descriptions[:-1]) + f", and {descriptions[-1]}"
+                # 對於3個或以上的項目，確保正確的語法結構
+                main_items = ", ".join(valid_descriptions[:-1])
+                last_item = valid_descriptions[-1]
+                # 確保 main_items 和 last_item 都不為空
+                if main_items and last_item:
+                    return f"{main_items}, and {last_item}"
+                elif main_items:
+                    return main_items
+                elif last_item:
+                    return last_item
+                else:
+                    return "various elements"
 
         except Exception as e:
             self.logger.warning(f"Error generating objects summary: {str(e)}")
             return "various elements"
 
     def get_placeholder_replacement(self, placeholder: str, fillers: Dict,
-                                   all_replacements: Dict, detected_objects: List[Dict],
-                                   scene_type: str) -> str:
+                               all_replacements: Dict, detected_objects: List[Dict],
+                               scene_type: str) -> str:
         """
         獲取特定佔位符的替換內容，確保永遠不返回空值
 
@@ -306,16 +325,34 @@ class ContentGenerator:
             str: 替換內容
         """
         try:
-            # 優先處理動態內容生成的佔位符
-            dynamic_placeholders = [
-                'primary_objects', 'detected_objects_summary', 'main_objects',
-                'functional_area', 'functional_zones_description', 'scene_elements'
-            ]
+            # 動態佔位符的差異化處理策略
+            dynamic_placeholders_mapping = {
+                'primary_objects': 'full_summary',
+                'detected_objects_summary': 'full_summary',
+                'main_objects': 'simple_summary',
+                'functional_area': 'area_focus',
+                'functional_zones_description': 'zones_focus',
+                'scene_elements': 'elements_focus'
+            }
 
-            if placeholder in dynamic_placeholders:
-                dynamic_content = self.generate_objects_summary(detected_objects)
-                if dynamic_content and dynamic_content.strip():
-                    return dynamic_content.strip()
+            if placeholder in dynamic_placeholders_mapping:
+                content_type = dynamic_placeholders_mapping[placeholder]
+
+                # 根據內容類型和當前檢測物件生成不同的描述
+                if content_type == 'full_summary':
+                    return self.generate_objects_summary(detected_objects)
+                elif content_type == 'simple_summary':
+                    # 避免重複敘述
+                    return self._generate_simplified_objects_summary(detected_objects)
+                elif content_type == 'area_focus':
+                    # 以圖片中的area 作為重點描述
+                    return self._generate_area_focused_summary(detected_objects)
+                elif content_type == 'zones_focus':
+                    # 以圖片中的zones 作為重點描述
+                    return self._generate_zones_summary(detected_objects)
+                elif content_type == 'elements_focus':
+                    # 以圖片中物品作為重點描述
+                    return self._generate_elements_summary(detected_objects)
 
             # 檢查預定義替換內容
             if placeholder in all_replacements:
@@ -346,7 +383,7 @@ class ContentGenerator:
             if scene_specific_replacement and scene_specific_replacement.strip():
                 return scene_specific_replacement.strip()
 
-            # 通用備用字典 
+            # 通用備用字典
             fallback_replacements = {
                 # 交通和城市相關
                 "crossing_pattern": "pedestrian crosswalks",
@@ -405,7 +442,7 @@ class ContentGenerator:
             # 最終備用：將下劃線轉換為有意義的短語
             cleaned_placeholder = placeholder.replace('_', ' ')
 
-            # 對常見模式提供更好的默認值
+            # 對常見模式提供更全面的defualt value
             if placeholder.endswith('_pattern'):
                 return f"{cleaned_placeholder.replace(' pattern', '')} arrangement"
             elif placeholder.endswith('_behavior'):
@@ -421,9 +458,94 @@ class ContentGenerator:
 
         except Exception as e:
             self.logger.warning(f"Error getting replacement for placeholder '{placeholder}': {str(e)}")
-            # 確保即使在異常情況下也返回有意義的內容
             return placeholder.replace('_', ' ') if placeholder else "scene elements"
 
+    def _generate_simplified_objects_summary(self, detected_objects: List[Dict]) -> str:
+        """生成簡化的物件摘要，避免與詳細摘要重複"""
+        try:
+            if not detected_objects:
+                return "scene elements"
+
+            # 只取最重要的前3個物件
+            object_counts = {}
+            for obj in detected_objects:
+                class_name = obj.get("class_name", "unknown")
+                confidence = obj.get("confidence", 0.5)
+
+                if class_name not in object_counts:
+                    object_counts[class_name] = {"count": 0, "total_confidence": 0}
+
+                object_counts[class_name]["count"] += 1
+                object_counts[class_name]["total_confidence"] += confidence
+
+            # 排序並取前3個
+            sorted_objects = []
+            for class_name, stats in object_counts.items():
+                count = stats["count"]
+                avg_confidence = stats["total_confidence"] / count
+                importance = count * 0.6 + avg_confidence * 0.4
+                sorted_objects.append((class_name, count, importance))
+
+            sorted_objects.sort(key=lambda x: x[2], reverse=True)
+            top_objects = sorted_objects[:3]
+
+            if top_objects:
+                primary_object = top_objects[0]
+                clean_name = primary_object[0].replace('_', ' ')
+                count = primary_object[1]
+
+                if count == 1:
+                    article = "an" if clean_name[0].lower() in 'aeiou' else "a"
+                    return f"{article} {clean_name}"
+                else:
+                    return f"{count} {clean_name}s"
+
+            return "scene elements"
+
+        except Exception as e:
+            self.logger.warning(f"Error generating simplified summary: {str(e)}")
+            return "scene elements"
+
+    def _generate_area_focused_summary(self, detected_objects: List[Dict]) -> str:
+        """生成區域導向的摘要"""
+        try:
+            # 根據檢測到的物件推斷主要功能區域
+            furniture_objects = [obj for obj in detected_objects if obj.get("class_name") in ["chair", "dining table", "sofa", "bed"]]
+
+            if any(obj.get("class_name") == "dining table" for obj in furniture_objects):
+                return "dining area"
+            elif any(obj.get("class_name") == "sofa" for obj in furniture_objects):
+                return "seating area"
+            elif any(obj.get("class_name") == "bed" for obj in furniture_objects):
+                return "sleeping area"
+            elif furniture_objects:
+                return "furnished area"
+            else:
+                return "activity area"
+
+        except Exception as e:
+            self.logger.warning(f"Error generating area-focused summary: {str(e)}")
+            return "functional area"
+
+    def _generate_zones_summary(self, detected_objects: List[Dict]) -> str:
+        """生成區域描述摘要"""
+        try:
+            return "organized areas of activity"
+        except Exception as e:
+            return "functional zones"
+
+    def _generate_elements_summary(self, detected_objects: List[Dict]) -> str:
+        """生成元素導向的摘要"""
+        try:
+            if len(detected_objects) > 5:
+                return "diverse elements"
+            elif len(detected_objects) > 2:
+                return "multiple elements"
+            else:
+                return "key elements"
+        except Exception as e:
+            return "scene elements"
+
     def get_scene_based_default(self, placeholder: str, scene_type: str) -> Optional[str]:
         """
         基於場景類型提供智能默認值

functional_zone_detector.py

@@ -230,7 +230,14 @@ class FunctionalZoneDetector:
             region = zone_data.get("region", "")
             description = zone_data.get("description", "")
 
-            # 基於物件內容確定功能類型
+            # 確保只有在明確檢測到廚房設備時才產生 kitchen area
+            kitchen_objects = ["refrigerator", "microwave", "oven", "sink", "dishwasher", "stove"]
+            explicit_kitchen_detected = any(
+                any(kitchen_item in obj.lower() for kitchen_item in kitchen_objects)
+                for obj in objects
+            )
+
+            # 基於物件內容確定功能類型（保持原有順序，但加強廚房確認, 因為與dining room混淆）
             if any("dining" in obj.lower() or "table" in obj.lower() for obj in objects):
                 base_name = "dining area"
             elif any("chair" in obj.lower() or "sofa" in obj.lower() for obj in objects):
@@ -241,20 +248,52 @@ class FunctionalZoneDetector:
                 base_name = "workspace area"
             elif any("plant" in obj.lower() or "vase" in obj.lower() for obj in objects):
                 base_name = "decorative area"
-            elif any("refrigerator" in obj.lower() or "microwave" in obj.lower() for obj in objects):
+            elif explicit_kitchen_detected:
+                # 只有在明確檢測到廚房設備時才使用 kitchen area
                 base_name = "kitchen area"
             else:
-                # 基於描述內容推斷
-                if "dining" in description.lower():
+                # 基於描述內容推斷，但避免不當的 kitchen area 判斷
+                if "dining" in description.lower() and any("table" in obj.lower() for obj in objects):
+                    # 只有當描述中提到 dining 且確實有桌子時才使用 dining area
                     base_name = "dining area"
                 elif "seating" in description.lower() or "relaxation" in description.lower():
                     base_name = "seating area"
-                elif "work" in description.lower():
+                elif "work" in description.lower() and any("laptop" in obj.lower() or "keyboard" in obj.lower() for obj in objects):
+                    # 只有當描述中提到 work 且確實有工作設備時才使用 workspace area
                     base_name = "workspace area"
                 elif "decorative" in description.lower():
                     base_name = "decorative area"
                 else:
-                    base_name = "functional area"
+                    # 根據主要物件類型決定預設區域類型，避免使用 kitchen area
+                    if objects:
+                        # 根據最常見的物件類型決定區域名稱
+                        object_counts = {}
+                        for obj in objects:
+                            obj_lower = obj.lower()
+                            if "chair" in obj_lower:
+                                object_counts["seating"] = object_counts.get("seating", 0) + 1
+                            elif "table" in obj_lower:
+                                object_counts["dining"] = object_counts.get("dining", 0) + 1
+                            elif "person" in obj_lower:
+                                object_counts["activity"] = object_counts.get("activity", 0) + 1
+                            else:
+                                object_counts["general"] = object_counts.get("general", 0) + 1
+
+                        # 選擇最常見的類型
+                        if object_counts:
+                            most_common = max(object_counts, key=object_counts.get)
+                            if most_common == "seating":
+                                base_name = "seating area"
+                            elif most_common == "dining":
+                                base_name = "dining area"
+                            elif most_common == "activity":
+                                base_name = "activity area"
+                            else:
+                                base_name = "functional area"
+                        else:
+                            base_name = "functional area"
+                    else:
+                        base_name = "functional area"
 
             # 為次要區域添加位置標識以區分
             if priority_level == "secondary" and region:

functional_zone_identifier.py

@@ -688,7 +688,7 @@ class FunctionalZoneIdentifier:
             if not high_conf_objects:
                 high_conf_objects = detected_objects  # 後備到所有物件
 
-            # 基於個別重要物件創建區域
+            # 根據個別重要物件創建區域
             processed_objects = set()  # 避免重複處理相同類型的物件
 
             for obj in high_conf_objects[:3]:  # 限制為前3個物件
@@ -788,7 +788,6 @@ class FunctionalZoneIdentifier:
             區域描述字串
         """
         try:
-            # 物件特定描述
             descriptions = {
                 "bed": "Sleeping and rest area",
                 "sofa": "Seating and relaxation area",
@@ -797,11 +796,43 @@ class FunctionalZoneIdentifier:
                 "tv": "Entertainment and media area",
                 "laptop": "Work and computing area",
                 "potted plant": "Decorative and green space area",
-                "refrigerator": "Food storage and kitchen area",
                 "car": "Vehicle and transportation area",
                 "person": "Activity and social area"
             }
 
+            # 只有在明確的廚房場景中才使用廚房描述
+            kitchen_related_objects = ["refrigerator", "microwave", "oven", "sink", "dishwasher", "stove"]
+
+            if class_name in kitchen_related_objects:
+                # 檢查場景類型是否真的是廚房相關
+                kitchen_scene_types = ["kitchen", "professional_kitchen", "cooking_area"]
+
+                if scene_type in kitchen_scene_types:
+                    # 只有在明確的廚房場景中才使用廚房描述
+                    if class_name == "refrigerator":
+                        descriptions[class_name] = "Food storage and kitchen area"
+                    elif class_name == "microwave":
+                        descriptions[class_name] = "Food preparation area"
+                    elif class_name == "oven":
+                        descriptions[class_name] = "Cooking area"
+                    elif class_name == "sink":
+                        descriptions[class_name] = "Washing and preparation area"
+                    else:
+                        descriptions[class_name] = "Kitchen appliance area"
+                else:
+                    # === 修正：非廚房場景中的廚房物件使用中性描述 ===
+                    # 在餐廳、客廳等場景中，即使檢測到這些物件也不使用廚房描述
+                    if class_name == "refrigerator":
+                        descriptions[class_name] = "Storage area"
+                    elif class_name == "microwave":
+                        descriptions[class_name] = "Appliance area"
+                    elif class_name == "oven":
+                        descriptions[class_name] = "Equipment area"
+                    elif class_name == "sink":
+                        descriptions[class_name] = "Utility area"
+                    else:
+                        descriptions[class_name] = "Equipment area"
+
             return descriptions.get(class_name, f"Functional area with {class_name}")
 
         except Exception as e:
@@ -899,30 +930,36 @@ class FunctionalZoneIdentifier:
             "surfboard":     "sports area",
             "tennis racket": "sports area",
 
-            # 廚房與食品（Kitchen）
-            "bottle":        "kitchen area",
-            "wine glass":    "kitchen area",
-            "cup":           "kitchen area",
-            "fork":          "kitchen area",
-            "knife":         "kitchen area",
-            "spoon":         "kitchen area",
-            "bowl":          "kitchen area",
-            "banana":        "kitchen area",
-            "apple":         "kitchen area",
-            "sandwich":      "kitchen area",
-            "orange":        "kitchen area",
-            "broccoli":      "kitchen area",
-            "carrot":        "kitchen area",
-            "hot dog":       "kitchen area",
-            "pizza":         "kitchen area",
-            "donut":         "kitchen area",
-            "cake":          "kitchen area",
-            "dining table":  "furniture arrangement area",
-            "refrigerator":  "kitchen area",
-            "oven":          "kitchen area",
-            "microwave":     "kitchen area",
-            "toaster":       "kitchen area",
-            "sink":          "kitchen area",
+            # 餐具與用餐相關物品重新歸類為 dining area
+            "bottle":        "dining area",
+            "wine glass":    "dining area",
+            "cup":           "dining area",
+            "fork":          "dining area",
+            "knife":         "dining area",
+            "spoon":         "dining area",
+            "bowl":          "dining area",
+            "dining table":  "dining area",  # 確保 dining table 也歸類為 dining area
+
+            # 食品使用中性的 food area
+            "banana":        "food area",
+            "apple":         "food area",
+            "sandwich":      "food area",
+            "orange":        "food area",
+            "broccoli":      "food area",
+            "carrot":        "food area",
+            "hot dog":       "food area",
+            "pizza":         "food area",
+            "donut":         "food area",
+            "cake":          "food area",
+
+            # 只有在有明確的廚房設備才使用 kitchen area
+            "refrigerator":  "kitchen appliance area",
+            "oven":          "kitchen appliance area",
+            "microwave":     "kitchen appliance area",
+            "toaster":       "kitchen appliance area",
+            "sink":          "kitchen appliance area",
+
+            # 其他物品
             "book":          "miscellaneous area",
             "clock":         "miscellaneous area",
             "vase":          "decorative area",

response_processor.py

@@ -1,4 +1,3 @@
-# %%writefile response_processor.py
 import re
 import logging
 import traceback
@@ -692,37 +691,68 @@ class ResponseProcessor:
             for pattern, replacement in identical_cleanup_patterns:
                 processed_response = re.sub(pattern, replacement, processed_response, flags=re.IGNORECASE)
 
-            # 數字到文字
+            # 數字到文字轉換 - 優化版本支援不規則複數
             number_conversions = {
                 '2': 'two', '3': 'three', '4': 'four', '5': 'five', '6': 'six',
                 '7': 'seven', '8': 'eight', '9': 'nine', '10': 'ten',
                 '11': 'eleven', '12': 'twelve'
             }
 
+            # 不規則複數詞彙映射表(非s結尾)
+            irregular_plurals = {
+                'people': 'people',
+                'children': 'children',
+                'men': 'men',
+                'women': 'women',
+                'feet': 'feet',
+                'teeth': 'teeth',
+                'mice': 'mice',
+                'geese': 'geese',
+                'sheep': 'sheep',
+                'deer': 'deer',
+                'fish': 'fish',
+                'species': 'species',
+                'series': 'series'
+            }
+
             # 處理各種語法結構中的數字
             for digit, word in number_conversions.items():
-                # 模式1: 數字 + 單一複數詞 (如 "7 chairs")
+                # 1: 數字 + 規則複數詞 (以s結尾，如 "7 chairs")
                 pattern1 = rf'\b{digit}\s+([a-zA-Z]+s)\b'
                 processed_response = re.sub(pattern1, rf'{word} \1', processed_response)
 
-                # 模式2: 數字 + 修飾詞 + 複數詞 (如 "7 more chairs")
-                pattern2 = rf'\b{digit}\s+(more|additional|other|identical)\s+([a-zA-Z]+s)\b'
-                processed_response = re.sub(pattern2, rf'{word} \1 \2', processed_response, flags=re.IGNORECASE)
+                # 2: 數字 + 不規則複數詞 (如 "7 people")
+                for irregular_plural in irregular_plurals.keys():
+                    pattern_irregular = rf'\b{digit}\s+({irregular_plural})\b'
+                    processed_response = re.sub(pattern_irregular, rf'{word} \1', processed_response, flags=re.IGNORECASE)
 
-                # 模式3: 數字 + 形容詞 + 複數詞 (如 "2 dining tables")
-                pattern3 = rf'\b{digit}\s+([a-zA-Z]+)\s+([a-zA-Z]+s)\b'
+                # 3: 數字 + 修飾詞 + 規則複數詞 (如 "7 more chairs")
+                pattern3 = rf'\b{digit}\s+(more|additional|other|identical)\s+([a-zA-Z]+s)\b'
                 processed_response = re.sub(pattern3, rf'{word} \1 \2', processed_response)
 
-                # 模式4: 介詞片語中的數字 (如 "around 2 tables")
-                pattern4 = rf'\b(around|approximately|about)\s+{digit}\s+([a-zA-Z]+s)\b'
-                processed_response = re.sub(pattern4, rf'\1 {word} \2', processed_response, flags=re.IGNORECASE)
+                # 4: 數字 + 修飾詞 + 不規則複數詞 (如 "7 more people")
+                for irregular_plural in irregular_plurals.keys():
+                    pattern4 = rf'\b{digit}\s+(more|additional|other|identical)\s+({irregular_plural})\b'
+                    processed_response = re.sub(pattern4, rf'{word} \1 \2', processed_response, flags=re.IGNORECASE)
+
+                # 5: 數字 + 複合名詞結構 (如 "7 wine glasses")
+                compound_nouns = ['wine glasses', 'dining tables', 'coffee cups', 'traffic lights', 'cell phones']
+                for compound in compound_nouns:
+                    pattern_compound = rf'\b{digit}\s+({re.escape(compound)})\b'
+                    processed_response = re.sub(pattern_compound, rf'{word} \1', processed_response, flags=re.IGNORECASE)
+
+                # 6: 處理特殊單複數同形詞彙 (如 "7 deer", "7 sheep")
+                same_form_words = ['deer', 'sheep', 'fish', 'species', 'series', 'aircraft']
+                for same_word in same_form_words:
+                    pattern_same = rf'\b{digit}\s+({same_word})\b'
+                    processed_response = re.sub(pattern_same, rf'{word} \1', processed_response, flags=re.IGNORECASE)
 
             return processed_response
 
         except Exception as e:
             self.logger.error(f"Error in _handle_repetitive_vocabulary: {str(e)}")
             self.logger.error(traceback.format_exc())
-            return response # 發生錯誤時返回原始回應
+            return response  # 發生錯誤時返回原始回應
 
     def _ensure_grammatical_completeness(self, response: str) -> str:
         """
@@ -1159,4 +1189,4 @@ class ResponseProcessor:
             "suffixes_to_remove_count": len(self.suffixes_to_remove),
             "repetitive_patterns_count": len(self.repetitive_patterns),
             "initialization_status": "success"
-        }
+        }

ui_manager.py

@@ -7,7 +7,7 @@ from style import Style
 
 class UIManager:
     """
-    Manages all UI-related functionality 
+    Manages all UI-related functionality
     Handles Gradio interface creation, component definitions, and event binding.
     """
 
@@ -275,8 +275,8 @@ class UIManager:
                     gr.Examples(
                         examples=[
                             "room_05.jpg",
+                            "street_03.jpg",
                             "street_04.jpg",
-                            "street_05.jpg",
                             "landmark_Louvre_01.jpg"
                         ],
                         inputs=components['image_input'],
@@ -398,7 +398,7 @@ class UIManager:
                                     )
 
         return components
-    
+
     def create_video_tab(self):
         """
         Create the video processing tab with all components.
@@ -465,7 +465,7 @@ class UIManager:
                                 label="Processing Interval (Frames)",
                                 info="Analyze every Nth frame (higher value = faster processing)"
                             )
-                            
+
                             # 簡化的分析說明
                             gr.HTML("""
                                 <div style="padding: 8px; margin-top: 10px; background-color: #f0f7ff; border-radius: 4px; border-left: 3px solid #4299e1; font-size: 12px;">
@@ -496,7 +496,7 @@ class UIManager:
                             * Adjust **confidence threshold** to filter low-quality detections
                         3. Click "Analyze Video". **Processing time varies based on video length.**
                         4. Review the results: annotated video and statistical analysis.
-                        
+
                         **⚡ Performance Tips:**
                         * For videos longer than 2 minutes, use interval ≥ 15 frames
                         * YOLOv8n model provides best speed for video processing
@@ -525,11 +525,11 @@ class UIManager:
                             </summary>
                             <div style="margin-top: 8px; padding: 10px; background-color: #f8f9fa; border-radius: 6px; border: 1px solid #e2e8f0;">
                                 <p style="font-size: 13px; color: #718096; margin: 0;">
-                                    <b>Focus on practical insights:</b> This analysis provides accurate object counts and timing information 
-                                    without complex tracking. The system uses spatial clustering to eliminate duplicate detections and 
+                                    <b>Focus on practical insights:</b> This analysis provides accurate object counts and timing information
+                                    without complex tracking. The system uses spatial clustering to eliminate duplicate detections and
                                     provides clear timeline data showing when objects first appear and how long they remain visible.
                                     <br><br>
-                                    <b>Key benefits:</b> Reliable object counting, clear timeline analysis, and easy-to-understand results 
+                                    <b>Key benefits:</b> Reliable object counting, clear timeline analysis, and easy-to-understand results
                                     that directly answer questions like "How many cars are in this video?" and "When do they appear?"
                                 </p>
                             </div>
@@ -558,10 +558,10 @@ class UIManager:
                                 elem_id="video-summary-html-output"
                             )
 
-                        # Detailed Statistics Tab  
+                        # Detailed Statistics Tab
                         with gr.Tab("Detailed Statistics"):
                             gr.HTML('<div class="section-heading">Complete Analysis Data</div>')
-                            
+
                             with gr.Accordion("Processing Information", open=True):
                                 gr.HTML("""
                                     <div style="padding: 6px; background-color: #f8f9fa; border-radius: 4px; margin-bottom: 10px; font-size: 12px;">
@@ -574,7 +574,7 @@ class UIManager:
                                     label=None,
                                     elem_classes="video-stats-display"
                                 )
-                            
+
                             with gr.Accordion("Object Details", open=False):
                                 gr.HTML("""
                                     <div style="padding: 6px; background-color: #f8f9fa; border-radius: 4px; margin-bottom: 10px; font-size: 12px;">
@@ -735,7 +735,7 @@ class UIManager:
             ]
         )
 
-        # Video Process Button Click Handler 
+        # Video Process Button Click Handler
         video_components['video_process_btn'].click(
         fn=handle_video_upload_fn,
         inputs=[
@@ -750,6 +750,6 @@ class UIManager:
             video_components['video_output'],
             video_components['video_summary_text'],
             video_components['video_stats_json'],
-            video_components['video_object_details'] 
+            video_components['video_object_details']
             ]
         )