feat: 添加最大视频时长检测和二次切分功能

- 添加最大视频时长限制配置 (默认2秒)
- 实现二次切分功能，超过时长限制的视频自动切分
- 优化单场景检测逻辑，跳过不必要的切分
- 修复场景和片段统计逻辑，无场景切换时统计为1个场景
- 添加CLI参数 --max-duration 支持自定义时长限制
- 集成FfmpegSliceService同步版本，简化异步复杂性
- 完善错误处理和文件清理机制

python_core/cli/commands/scene_detect.py

@@ -111,6 +111,7 @@ def batch_detect_and_split(
     use_advanced_split: bool = typer.Option(True, "--advanced/--traditional", help="使用高效批量切分/传统逐个切分"),
     split_quality: int = typer.Option(23, "--quality", "-q", help="切分质量 (CRF值, 18-28)"),
     split_preset: str = typer.Option("fast", "--preset", help="编码预设 (ultrafast/fast/medium/slow)"),
+    max_duration: float = typer.Option(2.0, "--max-duration", "-d", help="最大视频时长限制（秒），超过将二次切分"),
     verbose: bool = typer.Option(False, "--verbose", "-v", help="详细输出")
 ):
     """批量场景检测和视频切分"""
@@ -162,7 +163,8 @@ def batch_detect_and_split(
             continue_on_error=continue_on_error,
             use_advanced_split=use_advanced_split,
             split_quality=split_quality,
-            split_preset=split_preset
+            split_preset=split_preset,
+            max_video_duration=max_duration
         )
 
         # 显示结果

python_core/scene_detection/scene_detector.py

@@ -120,11 +120,12 @@ class SceneDetector:
                               enable_ai_analysis: bool = False, enable_video_splitting: bool = True,
                               max_concurrent: int = 2, continue_on_error: bool = True,
                               use_advanced_split: bool = True, split_quality: int = 23, split_preset: str = "fast",
-                              request_id: Optional[str] = None) -> Dict[str, Any]:
+                              max_video_duration: float = 60.0, request_id: Optional[str] = None) -> Dict[str, Any]:
         """批量场景检测和视频切分"""
         return self.workflow_manager.batch_detect_and_split(
             video_paths, output_base_dir, detector_type, threshold, min_scene_length,
             output_format, enable_ai_analysis, enable_video_splitting,
-            max_concurrent, continue_on_error, use_advanced_split, split_quality, split_preset, request_id
+            max_concurrent, continue_on_error, use_advanced_split, split_quality, split_preset,
+            max_video_duration, request_id
         )
 

python_core/scene_detection/types/batch_workflow_state.py

@@ -41,7 +41,7 @@ class BatchSceneDetectionWorkflowState:
     use_advanced_split: bool = True
     split_quality: int = 23
     split_preset: str = "fast"
-    max_video_duration: float = 60.0  # 最大视频时长（秒），默认60秒
+    max_video_duration: float = 2.0  # 最大视频时长（秒），默认60秒
 
     # 批量处理配置
     max_concurrent: int = 4

python_core/scene_detection/workflows/batch_workflow_nodes.py

@@ -296,20 +296,6 @@ class BatchWorkflowNodes:
                                 )
                                 split_results_raw.append(split_result)
                     
-                    # 转换为字典格式
-                    split_results = [
-                        {
-                            "scene_index": r.scene_index + 1,
-                            "output_path": str(r.output_path),
-                            "start_time": r.start_time,
-                            "end_time": r.end_time,
-                            "duration": r.duration,
-                            "file_size": r.file_size,
-                            "success": r.success,
-                            "error": r.error
-                        }
-                        for r in split_results_raw
-                    ]
                     
                     # 创建切分摘要
                     successful_results = [r for r in split_results_raw if r.success]
@@ -333,6 +319,79 @@ class BatchWorkflowNodes:
                     # 切分失败不影响整体任务成功
             
             # 4. 添加视频时长检查，如果时长大于 最大视频时长 那么就要进行二次切分 确保 视频不大于 最大视频时长
+            final_split_results = []
+
+            for split_result in split_results_raw:
+                try:
+                    # 检查切分后的视频时长
+                    video_path = str(split_result.output_path)
+
+                    if split_result.duration > state.max_video_duration:
+                        logger.info(f"⚠️ 片段 {split_result.scene_index + 1} 时长 {split_result.duration:.2f}s 超过限制 {state.max_video_duration:.2f}s，进行二次切分")
+
+                        # 进行二次切分
+                        secondary_results = self.splitter_service.check_and_split_by_duration(
+                            video_path=video_path,
+                            max_duration=state.max_video_duration,
+                            options=slice_options,
+                            output_dir=str(split_result.output_path.parent)
+                        )
+
+                        # 处理二次切分结果
+                        for i, (secondary_path, secondary_metadata) in enumerate(secondary_results):
+                            if len(secondary_results) > 1:
+                                # 如果进行了二次切分，创建新的结果对象
+                                secondary_split_result = SplitResult(
+                                    scene_index=split_result.scene_index,
+                                    output_path=secondary_path,
+                                    start_time=split_result.start_time + (i * state.max_video_duration),
+                                    end_time=min(split_result.start_time + ((i + 1) * state.max_video_duration), split_result.end_time),
+                                    duration=secondary_metadata.duration,
+                                    file_size=secondary_metadata.size,
+                                    success=Path(secondary_path).exists(),
+                                    error=None if Path(secondary_path).exists() else "二次切分文件不存在"
+                                )
+                                final_split_results.append(secondary_split_result)
+
+                                # 删除原始的过长片段（如果二次切分成功）
+                                if Path(video_path).exists() and len(secondary_results) > 1:
+                                    try:
+                                        Path(video_path).unlink()
+                                        logger.info(f"🗑️ 已删除过长的原始片段: {Path(video_path).name}")
+                                    except Exception as e:
+                                        logger.warning(f"⚠️ 删除原始片段失败: {e}")
+                            else:
+                                # 如果没有进行二次切分（时长检查通过），保持原结果
+                                final_split_results.append(split_result)
+                    else:
+                        # 时长未超过限制，直接添加到最终结果
+                        final_split_results.append(split_result)
+
+                except Exception as e:
+                    logger.error(f"❌ 处理片段 {split_result.scene_index + 1} 的时长检查时出错: {e}")
+                    # 出错时保持原结果
+                    final_split_results.append(split_result)
+
+            # 使用最终的切分结果
+            split_results_raw = final_split_results
+
+            # 转换为字典格式
+            split_results = [
+                {
+                    "scene_index": r.scene_index + 1,
+                    "output_path": str(r.output_path),
+                    "start_time": r.start_time,
+                    "end_time": r.end_time,
+                    "duration": r.duration,
+                    "file_size": r.file_size,
+                    "success": r.success,
+                    "error": r.error
+                }
+                for r in split_results_raw
+            ]
+            
+            # 更新统计信息
+            logger.info(f"📊 最终生成 {len(split_results_raw)} 个视频片段（包含二次切分）")
             
             task.end_time = time.time()
             

python_core/scene_detection/workflows/workflow_manager.py

@@ -184,7 +184,7 @@ class SceneDetectionWorkflowManager:
                               enable_ai_analysis: bool = False, enable_video_splitting: bool = True,
                               max_concurrent: int = 2, continue_on_error: bool = True,
                               use_advanced_split: bool = True, split_quality: int = 23, split_preset: str = "fast",
-                              request_id: Optional[str] = None) -> Dict[str, Any]:
+                              max_video_duration: float = 60.0, request_id: Optional[str] = None) -> Dict[str, Any]:
         """批量场景检测和视频切分"""
 
         # 创建批量工作流状态
@@ -200,6 +200,7 @@ class SceneDetectionWorkflowManager:
             use_advanced_split=use_advanced_split,
             split_quality=split_quality,
             split_preset=split_preset,
+            max_video_duration=max_video_duration,
             max_concurrent=max_concurrent,
             continue_on_error=continue_on_error,
             request_id=request_id,