fix: 视频切分
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@@ -41,9 +41,10 @@ class BatchSceneDetectionWorkflowState:
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use_advanced_split: bool = True
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split_quality: int = 23
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split_preset: str = "fast"
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max_video_duration: float = 60.0 # 最大视频时长（秒），默认60秒
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# 批量处理配置
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max_concurrent: int = 2
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max_concurrent: int = 4
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continue_on_error: bool = True
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# 工作流状态
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@@ -5,9 +5,8 @@ Batch Workflow Nodes
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"""
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import time
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import asyncio
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from pathlib import Path
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from typing import Dict, Any, List
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from typing import Dict, Any
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from python_core.utils.logger import logger
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@@ -17,7 +16,7 @@ from ..types.enums import DetectorType, OutputFormat
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from ..services.detector_service import SceneDetectorService
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from ..services.video_info_service import VideoInfoService
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from ..services.ai_analysis_service import AIAnalysisService
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from python_core.services.ffmpeg_slice_service import FfmpegSliceService, SliceOptions
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from python_core.services.ffmpeg_slice_service_sync import FfmpegSliceService, SliceOptions, SliceSegment
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from ..utils.result_saver import ResultSaver
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@@ -202,13 +201,100 @@ class BatchWorkflowNodes:
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preset=state.split_preset
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)
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split_results_raw = self.splitter_service.split_video_by_scenes(
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task.video_path,
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detection_result.scenes,
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task.output_dir / "scenes",
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use_advanced=state.use_advanced_split,
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options=slice_options
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)
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# 转换场景为SliceSegment
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segments = [
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SliceSegment(start=scene.start_time, end=scene.end_time)
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for scene in detection_result.scenes
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]
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# 创建输出目录
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scenes_dir = task.output_dir / "scenes"
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scenes_dir.mkdir(parents=True, exist_ok=True)
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# 生成输出路径
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base_output_path = str(scenes_dir / f"{task.video_path.stem}_scene")
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# 使用同步方法进行切分
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# 检查是否无场景，如果是则跳过切分
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if len(segments) <= 0:
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logger.info(f"🔄 检测到 0 个场景切换，跳过切分，直接使用源文件")
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# 创建输出目录
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scenes_dir.mkdir(parents=True, exist_ok=True)
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# 直接复制源文件作为结果
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import shutil
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source_file = task.video_path
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target_file = scenes_dir / f"{task.video_path.stem}_scene_001.mp4"
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try:
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shutil.copy2(source_file, target_file)
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logger.info(f"✅ 源文件已复制到: {target_file}")
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# 获取源文件元数据
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metadata = self.splitter_service.get_video_metadata(str(source_file))
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# 创建模拟的切分结果
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slice_results = [(str(target_file), metadata)]
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# 修正场景统计：无场景切换 = 1个场景（整个视频）
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detection_result.total_scenes = 1
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except Exception as e:
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logger.error(f"❌ 复制源文件失败: {e}")
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slice_results = []
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else:
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logger.info(f"🎬 检测到 {len(segments)} 个场景，开始切分")
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slice_results = self.splitter_service.slice_video(
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media_path=str(task.video_path),
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segments=segments,
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options=slice_options,
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output_path=base_output_path
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)
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# 转换为兼容格式
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split_results_raw = []
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# 创建一个简单的结果对象
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class SplitResult:
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def __init__(self, scene_index, output_path, start_time, end_time, duration, file_size, success, error=None):
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self.scene_index = scene_index
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self.output_path = Path(output_path)
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self.start_time = start_time
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self.end_time = end_time
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self.duration = duration
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self.file_size = file_size
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self.success = success
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self.error = error
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for i, (output_path, metadata) in enumerate(slice_results):
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if len(detection_result.scenes) == 0:
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# 无场景切换的情况：整个视频作为一个场景
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split_result = SplitResult(
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scene_index=0,
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output_path=output_path,
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start_time=0.0,
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end_time=metadata.duration,
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duration=metadata.duration,
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file_size=metadata.size,
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success=Path(output_path).exists(),
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error=None if Path(output_path).exists() else "文件不存在"
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)
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split_results_raw.append(split_result)
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else:
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# 有场景切换的情况
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scene = detection_result.scenes[i] if i < len(detection_result.scenes) else None
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if scene:
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split_result = SplitResult(
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scene_index=i,
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output_path=output_path,
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start_time=scene.start_time,
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end_time=scene.end_time,
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duration=scene.duration,
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file_size=metadata.size,
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success=Path(output_path).exists(),
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error=None if Path(output_path).exists() else "文件不存在"
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)
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split_results_raw.append(split_result)
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# 转换为字典格式
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split_results = [
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@@ -225,10 +311,18 @@ class BatchWorkflowNodes:
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for r in split_results_raw
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]
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# 保存切分摘要
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split_summary = self.splitter_service.create_split_summary(
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task.video_path, split_results_raw
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)
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# 创建切分摘要
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successful_results = [r for r in split_results_raw if r.success]
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failed_results = [r for r in split_results_raw if not r.success]
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split_summary = {
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"video_path": str(task.video_path),
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"total_scenes": len(split_results_raw),
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"successful_splits": len(successful_results),
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"failed_splits": len(failed_results),
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"success_rate": len(successful_results) / len(split_results_raw) * 100 if split_results_raw else 0,
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"total_output_size": sum(r.file_size for r in successful_results)
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}
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summary_file = task.output_dir / "split_summary.json"
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import json
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with open(summary_file, 'w', encoding='utf-8') as f:
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@@ -238,6 +332,8 @@ class BatchWorkflowNodes:
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logger.error(f"视频切分失败: {e}")
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# 切分失败不影响整体任务成功
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# 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
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task.end_time = time.time()
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return {
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