import math import json import os.path import re import traceback from os import path from loguru import logger from app.config import config from app.config.audio_config import AudioConfig, get_recommended_volumes_for_content from app.models import const from app.models.schema import VideoClipParams from app.services import ( voice, audio_merger, subtitle_merger, clip_video, merger_video, update_script, generate_video, script_subtitle, ) from app.services import state as sm from app.utils import utils VIDEO_GENERATION_TOTAL_STEPS = 6 def _update_video_generation_task( task_id: str, progress: int, message: str, step_current: int = 0, ffmpeg_progress: float | None = None, state: int = const.TASK_STATE_PROCESSING, **kwargs, ) -> None: task_fields = { "message": message, "step_current": step_current, "step_total": VIDEO_GENERATION_TOTAL_STEPS, **kwargs, } if ffmpeg_progress is not None: task_fields["ffmpeg_progress"] = round( max(0.0, min(100.0, float(ffmpeg_progress))), 1, ) sm.state.update_task( task_id, state=state, progress=progress, **task_fields, ) def _is_auto_transcription_enabled(params: VideoClipParams) -> bool: return bool( getattr(params, "subtitle_enabled", True) and getattr(params, "subtitle_auto_transcribe_enabled", False) ) def _get_auto_transcription_backend(params: VideoClipParams) -> str: backend = str(getattr(params, "subtitle_auto_transcribe_backend", "") or "").strip().lower() if backend not in {"local", "firered", "bailian"}: backend = "local" return backend def _get_original_subtitle_paths(params: VideoClipParams) -> list[str]: subtitle_paths = getattr(params, "original_subtitle_paths", []) or [] if isinstance(subtitle_paths, str): subtitle_paths = [subtitle_paths] normalized_paths = [] seen = set() for subtitle_path in subtitle_paths: if not isinstance(subtitle_path, str): continue subtitle_path = subtitle_path.strip() if subtitle_path and subtitle_path not in seen: normalized_paths.append(subtitle_path) seen.add(subtitle_path) single_subtitle_path = str(getattr(params, "original_subtitle_path", "") or "").strip() if single_subtitle_path and single_subtitle_path not in seen: normalized_paths.insert(0, single_subtitle_path) if not normalized_paths: normalized_paths = _find_original_subtitle_paths_for_videos(_get_video_origin_paths(params)) return normalized_paths def _get_video_origin_paths(params: VideoClipParams) -> list[str]: video_paths = getattr(params, "video_origin_paths", []) or [] if isinstance(video_paths, str): video_paths = [video_paths] normalized_paths = [] seen = set() for video_path in video_paths: if not isinstance(video_path, str): continue video_path = video_path.strip() if video_path and video_path not in seen: normalized_paths.append(video_path) seen.add(video_path) single_video_path = str(getattr(params, "video_origin_path", "") or "").strip() if single_video_path and single_video_path not in seen: normalized_paths.insert(0, single_video_path) return normalized_paths def _video_stem_candidates(video_path: str) -> list[str]: stem = path.splitext(path.basename(str(video_path or "").strip()))[0] if not stem: return [] candidates = [stem] timestamp_stripped = re.sub(r"_[0-9]{14}$", "", stem) if timestamp_stripped and timestamp_stripped not in candidates: candidates.append(timestamp_stripped) return candidates def _find_original_subtitle_paths_for_videos(video_paths: list[str]) -> list[str]: subtitle_dir = utils.subtitle_dir() if not path.isdir(subtitle_dir): return [] subtitle_files = [ path.join(subtitle_dir, filename) for filename in os.listdir(subtitle_dir) if filename.lower().endswith(".srt") ] if not subtitle_files: return [] resolved_paths = [] seen = set() for video_path in video_paths: candidates = _video_stem_candidates(video_path) if not candidates: continue matches = [] for subtitle_path in subtitle_files: subtitle_stem = path.splitext(path.basename(subtitle_path))[0] for candidate in candidates: if subtitle_stem == candidate or subtitle_stem.startswith(f"{candidate}_"): matches.append(subtitle_path) break if not matches: continue matches.sort(key=lambda item: path.getmtime(item), reverse=True) selected_path = matches[0] if selected_path not in seen: resolved_paths.append(selected_path) seen.add(selected_path) if resolved_paths: logger.info(f"未从参数获取原片字幕，已按视频文件名自动匹配: {resolved_paths}") return resolved_paths def _create_programmatic_subtitle_file( task_id: str, list_script: list[dict], params: VideoClipParams, ) -> str: if not getattr(params, "subtitle_enabled", True): return "" original_subtitle_paths = _get_original_subtitle_paths(params) logger.info(f"程序化字幕使用原片字幕路径: {original_subtitle_paths or '未提供'}") return script_subtitle.create_script_subtitle_file( task_id=task_id, list_script=list_script, original_subtitle_paths=original_subtitle_paths, video_origin_paths=_get_video_origin_paths(params), ) def _build_subtitle_mask_options(params: VideoClipParams, enabled=None) -> dict: mask_configured = bool( getattr(params, "subtitle_enabled", True) and getattr(params, "subtitle_mask_enabled", False) ) mask_enabled = mask_configured if enabled is None else mask_configured and enabled return { 'subtitle_mask_enabled': mask_enabled, 'subtitle_mask_landscape_x_percent': getattr(params, "subtitle_mask_landscape_x_percent", 10.0), 'subtitle_mask_landscape_y_percent': getattr(params, "subtitle_mask_landscape_y_percent", 78.0), 'subtitle_mask_landscape_width_percent': getattr(params, "subtitle_mask_landscape_width_percent", 80.0), 'subtitle_mask_landscape_height_percent': getattr(params, "subtitle_mask_landscape_height_percent", 14.0), 'subtitle_mask_landscape_blur_radius': getattr(params, "subtitle_mask_landscape_blur_radius", 18), 'subtitle_mask_landscape_opacity_percent': getattr(params, "subtitle_mask_landscape_opacity_percent", 82), 'subtitle_mask_portrait_x_percent': getattr(params, "subtitle_mask_portrait_x_percent", 8.0), 'subtitle_mask_portrait_y_percent': getattr(params, "subtitle_mask_portrait_y_percent", 79.0), 'subtitle_mask_portrait_width_percent': getattr(params, "subtitle_mask_portrait_width_percent", 84.0), 'subtitle_mask_portrait_height_percent': getattr(params, "subtitle_mask_portrait_height_percent", 16.0), 'subtitle_mask_portrait_blur_radius': getattr(params, "subtitle_mask_portrait_blur_radius", 26), 'subtitle_mask_portrait_opacity_percent': getattr(params, "subtitle_mask_portrait_opacity_percent", 84), 'subtitle_position_landscape_y_percent': getattr(params, "subtitle_position_landscape_y_percent", 85.0), 'subtitle_position_portrait_y_percent': getattr(params, "subtitle_position_portrait_y_percent", 82.0), } def _transcribe_final_video(task_id: str, video_path: str, params: VideoClipParams) -> str: """Transcribe the fully merged video into an SRT file.""" from app.services import fun_asr_subtitle if not video_path or not path.exists(video_path): raise FileNotFoundError(f"自动转录视频不存在: {video_path}") backend = _get_auto_transcription_backend(params) subtitle_file = path.join(utils.task_dir(task_id), "auto_transcribed_final.srt") logger.info(f"开始自动转录最终视频: {video_path}, backend={backend}") if backend == "local": api_url = str( getattr(params, "subtitle_auto_transcribe_api_url", "") or config.fun_asr.get("api_url", fun_asr_subtitle.LOCAL_FUN_ASR_API_URL) ).strip() if not api_url: raise ValueError("请先输入本地 FunASR-Pack API 地址") generated_path = fun_asr_subtitle.create_with_local_fun_asr( local_file=video_path, subtitle_file=subtitle_file, api_url=api_url, hotword=str(getattr(params, "subtitle_auto_transcribe_hotword", "") or "").strip(), enable_spk=bool(getattr(params, "subtitle_auto_transcribe_enable_spk", False)), ) elif backend == "firered": api_url = str( getattr(params, "subtitle_auto_transcribe_firered_api_url", "") or config.fun_asr.get("firered_api_url", fun_asr_subtitle.LOCAL_FIRERED_ASR_API_URL) ).strip() if not api_url: raise ValueError("请先输入本地ASR API 地址") generated_path = fun_asr_subtitle.create_with_local_firered_asr( local_file=video_path, subtitle_file=subtitle_file, api_url=api_url, ) else: api_key = str( getattr(params, "subtitle_auto_transcribe_api_key", "") or config.fun_asr.get("api_key", "") ).strip() if not api_key: raise ValueError("请先输入阿里百炼 API Key") generated_path = fun_asr_subtitle.create_with_fun_asr( local_file=video_path, subtitle_file=subtitle_file, api_key=api_key, ) if not generated_path or not path.exists(generated_path): raise RuntimeError("自动转录失败：未生成字幕文件") logger.info(f"自动转录字幕生成成功: {generated_path}") return generated_path def _merge_auto_transcribed_subtitles( source_video_path: str, output_video_path: str, subtitle_path: str, params: VideoClipParams, ) -> str: subtitle_options = { 'voice_volume': 1.0, 'bgm_volume': 0.0, 'original_audio_volume': 1.0, 'keep_original_audio': True, 'subtitle_enabled': True, 'subtitle_font': params.font_name, 'subtitle_font_size': params.font_size, 'subtitle_color': params.text_fore_color, 'subtitle_bg_color': None, 'subtitle_position': params.subtitle_position, 'custom_position': params.custom_position, 'threads': params.n_threads, **_build_subtitle_mask_options(params, enabled=True), } return generate_video.merge_materials( video_path=source_video_path, audio_path="", subtitle_path=subtitle_path, bgm_path="", output_path=output_video_path, options=subtitle_options ) def start_subclip(task_id: str, params: VideoClipParams, subclip_path_videos: dict = None): """ 后台任务（统一视频裁剪处理）- 优化版本 实施基于OST类型的统一视频裁剪策略，消除双重裁剪问题： - OST=0: 根据TTS音频时长动态裁剪，移除原声 - OST=1: 严格按照脚本timestamp精确裁剪，保持原声 - OST=2: 根据TTS音频时长动态裁剪，保持原声 Args: task_id: 任务ID params: 视频参数 subclip_path_videos: 视频片段路径（可选，仅作为备用方案） """ global merged_audio_path, merged_subtitle_path logger.info(f"\n\n## 开始任务: {task_id}") sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=0) """ 1. 加载剪辑脚本 """ logger.info("\n\n## 1. 加载视频脚本") video_script_path = path.join(params.video_clip_json_path) if path.exists(video_script_path): try: with open(video_script_path, "r", encoding="utf-8") as f: list_script = json.load(f) video_list = [i['narration'] for i in list_script] video_ost = [i['OST'] for i in list_script] time_list = [i['timestamp'] for i in list_script] video_script = " ".join(video_list) logger.debug(f"解说完整脚本: \n{video_script}") logger.debug(f"解说 OST 列表: \n{video_ost}") logger.debug(f"解说时间戳列表: \n{time_list}") except Exception as e: logger.error(f"无法读取视频json脚本，请检查脚本格式是否正确") raise ValueError("无法读取视频json脚本，请检查脚本格式是否正确") else: logger.error(f"解说脚本文件不存在: {video_script_path}，请先点击【保存脚本】按钮保存脚本后再生成视频") raise ValueError("解说脚本文件不存在！请先点击【保存脚本】按钮保存脚本后再生成视频。") """ 2. 使用 TTS 生成音频素材 """ logger.info("\n\n## 2. 根据OST设置生成音频列表") # 只为OST=0 or 2的判断生成音频， OST=0 仅保留解说 OST=2 保留解说和原声 tts_segments = [ segment for segment in list_script if segment['OST'] in [0, 2] ] logger.debug(f"需要生成TTS的片段数: {len(tts_segments)}") tts_results = voice.tts_multiple( task_id=task_id, list_script=tts_segments, # 只传入需要TTS的片段 tts_engine=params.tts_engine, voice_name=params.voice_name, voice_rate=params.voice_rate, voice_pitch=params.voice_pitch, ) sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=20) # """ # 3. (可选) 使用 whisper 生成字幕 # """ # if merged_subtitle_path is None: # if audio_files: # merged_subtitle_path = path.join(utils.task_dir(task_id), f"subtitle.srt") # subtitle_provider = config.app.get("subtitle_provider", "").strip().lower() # logger.info(f"\n\n使用 {subtitle_provider} 生成字幕") # # subtitle.create( # audio_file=merged_audio_path, # subtitle_file=merged_subtitle_path, # ) # subtitle_lines = subtitle.file_to_subtitles(merged_subtitle_path) # if not subtitle_lines: # logger.warning(f"字幕文件无效: {merged_subtitle_path}") # # sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=40) """ 3. 统一视频裁剪 - 基于OST类型的差异化裁剪策略 """ logger.info("\n\n## 3. 统一视频裁剪（基于OST类型）") # 使用新的统一裁剪策略 video_clip_result = clip_video.clip_video_unified( video_origin_path=params.video_origin_path, video_origin_paths=getattr(params, "video_origin_paths", []), script_list=list_script, tts_results=tts_results ) # 更新 list_script 中的时间戳和路径信息 tts_clip_result = {tts_result['_id']: tts_result['audio_file'] for tts_result in tts_results} subclip_clip_result = { tts_result['_id']: tts_result['subtitle_file'] for tts_result in tts_results } new_script_list = update_script.update_script_timestamps(list_script, video_clip_result, tts_clip_result, subclip_clip_result) logger.info(f"统一裁剪完成，处理了 {len(video_clip_result)} 个视频片段") sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=60) """ 4. 合并音频和字幕 """ logger.info("\n\n## 4. 合并音频和字幕") total_duration = sum([script["duration"] for script in new_script_list]) if tts_segments: try: # 合并音频文件 merged_audio_path = audio_merger.merge_audio_files( task_id=task_id, total_duration=total_duration, list_script=new_script_list ) logger.info(f"音频文件合并成功->{merged_audio_path}") # 合并字幕文件 merged_subtitle_path = "" if getattr(params, "subtitle_enabled", True): try: merged_subtitle_path = _create_programmatic_subtitle_file( task_id, new_script_list, params, ) except Exception as e: logger.warning(f"程序化字幕生成失败，将尝试合并TTS字幕: {e}") if not merged_subtitle_path and getattr(params, "subtitle_enabled", True): merged_subtitle_path = subtitle_merger.merge_subtitle_files(new_script_list) if merged_subtitle_path: logger.info(f"字幕文件合并成功->{merged_subtitle_path}") else: logger.warning("没有有效的字幕内容，将生成无字幕视频") merged_subtitle_path = "" except Exception as e: logger.error(f"合并音频/字幕文件失败: {str(e)}") # 确保即使合并失败也有默认值 if 'merged_audio_path' not in locals(): merged_audio_path = "" if 'merged_subtitle_path' not in locals(): merged_subtitle_path = "" else: logger.warning("没有需要合并的音频/字幕") merged_audio_path = "" merged_subtitle_path = "" if getattr(params, "subtitle_enabled", True): try: merged_subtitle_path = _create_programmatic_subtitle_file( task_id, new_script_list, params, ) except Exception as e: logger.warning(f"程序化字幕生成失败: {e}") """ 5. 合并视频 """ final_video_paths = [] combined_video_paths = [] combined_video_path = path.join(utils.task_dir(task_id), f"merger.mp4") logger.info(f"\n\n## 5. 合并视频: => {combined_video_path}") # 使用统一裁剪后的视频片段 video_clips = [] for new_script in new_script_list: video_path = new_script.get('video') if video_path and os.path.exists(video_path): video_clips.append(video_path) else: logger.warning(f"片段 {new_script.get('_id')} 的视频文件不存在或未生成: {video_path}") # 如果统一裁剪失败，尝试使用备用方案（如果提供了subclip_path_videos） if subclip_path_videos and new_script.get('_id') in subclip_path_videos: backup_video = subclip_path_videos[new_script.get('_id')] if os.path.exists(backup_video): video_clips.append(backup_video) logger.info(f"使用备用视频: {backup_video}") else: logger.error(f"备用视频也不存在: {backup_video}") else: logger.error(f"无法找到片段 {new_script.get('_id')} 的视频文件") logger.info(f"准备合并 {len(video_clips)} 个视频片段") merger_video.combine_clip_videos( output_video_path=combined_video_path, video_paths=video_clips, video_ost_list=video_ost, video_aspect=params.video_aspect, threads=params.n_threads ) sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=80) """ 6. 合并字幕/BGM/配音/视频 """ output_video_path = path.join(utils.task_dir(task_id), f"combined.mp4") auto_transcription_enabled = _is_auto_transcription_enabled(params) merge_output_video_path = ( path.join(utils.task_dir(task_id), "combined_without_auto_subtitles.mp4") if auto_transcription_enabled else output_video_path ) logger.info(f"\n\n## 6. 最后一步: 合并字幕/BGM/配音/视频 -> {merge_output_video_path}") # bgm_path = '/Users/apple/Desktop/home/NarratoAI/resource/songs/bgm.mp3' bgm_path = utils.get_bgm_file( bgm_type=getattr(params, "bgm_type", "random"), bgm_file=getattr(params, "bgm_file", ""), ) # 获取优化的音量配置 optimized_volumes = get_recommended_volumes_for_content('mixed') # 检查是否有OST=1的原声片段，如果有，则保持原声音量为1.0不变 has_original_audio_segments = any(segment['OST'] == 1 for segment in list_script) # 应用用户设置和优化建议的组合 # 如果用户设置了非默认值，优先使用用户设置 final_tts_volume = params.tts_volume if hasattr(params, 'tts_volume') and params.tts_volume != 1.0 else optimized_volumes['tts_volume'] # 关键修复：如果有原声片段，保持原声音量为1.0，确保与原视频音量一致 if has_original_audio_segments: final_original_volume = 1.0 # 保持原声音量不变 logger.info("检测到原声片段，原声音量设置为1.0以保持与原视频一致") else: final_original_volume = params.original_volume if hasattr(params, 'original_volume') and params.original_volume != 0.7 else optimized_volumes['original_volume'] final_bgm_volume = params.bgm_volume if hasattr(params, 'bgm_volume') and params.bgm_volume != 0.3 else optimized_volumes['bgm_volume'] logger.info(f"音量配置 - TTS: {final_tts_volume}, 原声: {final_original_volume}, BGM: {final_bgm_volume}") # 调用示例 options = { 'voice_volume': final_tts_volume, # 配音音量（优化后） 'bgm_volume': final_bgm_volume, # 背景音乐音量（优化后） 'original_audio_volume': final_original_volume, # 视频原声音量（优化后） 'keep_original_audio': True, # 是否保留原声 'subtitle_enabled': params.subtitle_enabled and not auto_transcription_enabled, 'subtitle_font': params.font_name, # 这里使用相对字体路径，会自动在 font_dir() 目录下查找 'subtitle_font_size': params.font_size, 'subtitle_color': params.text_fore_color, 'subtitle_bg_color': None, # 直接使用None表示透明背景 'subtitle_position': params.subtitle_position, 'custom_position': params.custom_position, 'threads': params.n_threads, **_build_subtitle_mask_options(params, enabled=not auto_transcription_enabled), } generate_video.merge_materials( video_path=combined_video_path, audio_path=merged_audio_path, subtitle_path=merged_subtitle_path, bgm_path=bgm_path, output_path=merge_output_video_path, options=options ) auto_subtitle_path = "" if auto_transcription_enabled: sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=90) logger.info("\n\n## 7. 自动转录最终视频字幕") auto_subtitle_path = _transcribe_final_video(task_id, merge_output_video_path, params) sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=95) logger.info(f"\n\n## 8. 压入自动转录字幕 -> {output_video_path}") _merge_auto_transcribed_subtitles( source_video_path=merge_output_video_path, output_video_path=output_video_path, subtitle_path=auto_subtitle_path, params=params, ) final_video_paths.append(output_video_path) combined_video_paths.append(combined_video_path) logger.success(f"任务 {task_id} 已完成, 生成 {len(final_video_paths)} 个视频.") kwargs = { "videos": final_video_paths, "combined_videos": combined_video_paths } if auto_subtitle_path: kwargs["subtitles"] = [auto_subtitle_path] sm.state.update_task(task_id, state=const.TASK_STATE_COMPLETE, progress=100, **kwargs) return kwargs def start_subclip_unified(task_id: str, params: VideoClipParams): """ 统一视频裁剪处理函数 - 完全基于OST类型的新实现 这是优化后的版本，完全移除了对预裁剪视频的依赖， 实现真正的统一裁剪策略。 Args: task_id: 任务ID params: 视频参数 """ global merged_audio_path, merged_subtitle_path logger.info(f"\n\n## 开始统一视频处理任务: {task_id}") _update_video_generation_task( task_id, progress=0, message="正在初始化视频生成任务", step_current=0, ) """ 1. 加载剪辑脚本 """ logger.info("\n\n## 1. 加载视频脚本") _update_video_generation_task( task_id, progress=5, message="正在加载剪辑脚本", step_current=1, ) video_script_path = path.join(params.video_clip_json_path) if path.exists(video_script_path): try: with open(video_script_path, "r", encoding="utf-8") as f: list_script = json.load(f) video_list = [i['narration'] for i in list_script] video_ost = [i['OST'] for i in list_script] time_list = [i['timestamp'] for i in list_script] video_script = " ".join(video_list) logger.debug(f"解说完整脚本: \n{video_script}") logger.debug(f"解说 OST 列表: \n{video_ost}") logger.debug(f"解说时间戳列表: \n{time_list}") except Exception as e: logger.error(f"无法读取视频json脚本，请检查脚本格式是否正确") raise ValueError("无法读取视频json脚本，请检查脚本格式是否正确") else: logger.error(f"解说脚本文件不存在: {video_script_path}，请先点击【保存脚本】按钮保存脚本后再生成视频") raise ValueError("解说脚本文件不存在！请先点击【保存脚本】按钮保存脚本后再生成视频。") """ 2. 使用 TTS 生成音频素材 """ logger.info("\n\n## 2. 根据OST设置生成音频列表") _update_video_generation_task( task_id, progress=10, message="正在生成 TTS 配音", step_current=2, ) # 只为OST=0 or 2的判断生成音频， OST=0 仅保留解说 OST=2 保留解说和原声 tts_segments = [ segment for segment in list_script if segment['OST'] in [0, 2] ] logger.debug(f"需要生成TTS的片段数: {len(tts_segments)}") tts_results = voice.tts_multiple( task_id=task_id, list_script=tts_segments, # 只传入需要TTS的片段 tts_engine=params.tts_engine, voice_name=params.voice_name, voice_rate=params.voice_rate, voice_pitch=params.voice_pitch, ) _update_video_generation_task( task_id, progress=20, message="TTS 配音生成完成", step_current=2, ) """ 3. 统一视频裁剪 - 基于OST类型的差异化裁剪策略 """ logger.info("\n\n## 3. 统一视频裁剪（基于OST类型）") _update_video_generation_task( task_id, progress=30, message="正在按脚本裁剪视频片段", step_current=3, ) # 使用新的统一裁剪策略 video_clip_result = clip_video.clip_video_unified( video_origin_path=params.video_origin_path, video_origin_paths=getattr(params, "video_origin_paths", []), script_list=list_script, tts_results=tts_results ) # 更新 list_script 中的时间戳和路径信息 tts_clip_result = {tts_result['_id']: tts_result['audio_file'] for tts_result in tts_results} subclip_clip_result = { tts_result['_id']: tts_result['subtitle_file'] for tts_result in tts_results } new_script_list = update_script.update_script_timestamps(list_script, video_clip_result, tts_clip_result, subclip_clip_result) logger.info(f"统一裁剪完成，处理了 {len(video_clip_result)} 个视频片段") _update_video_generation_task( task_id, progress=60, message="视频片段裁剪完成", step_current=3, ) """ 4. 合并音频和字幕 """ logger.info("\n\n## 4. 合并音频和字幕") _update_video_generation_task( task_id, progress=65, message="正在合并配音和字幕", step_current=4, ) total_duration = sum([script["duration"] for script in new_script_list]) if tts_segments: try: # 合并音频文件 merged_audio_path = audio_merger.merge_audio_files( task_id=task_id, total_duration=total_duration, list_script=new_script_list ) logger.info(f"音频文件合并成功->{merged_audio_path}") # 优先基于脚本文案和成片时间线生成字幕，失败时回退到TTS字幕合并 merged_subtitle_path = "" if getattr(params, "subtitle_enabled", True): try: merged_subtitle_path = _create_programmatic_subtitle_file( task_id, new_script_list, params, ) except Exception as e: logger.warning(f"程序化字幕生成失败，将尝试合并TTS字幕: {e}") if not merged_subtitle_path and getattr(params, "subtitle_enabled", True): merged_subtitle_path = subtitle_merger.merge_subtitle_files(new_script_list) if merged_subtitle_path: logger.info(f"字幕文件合并成功->{merged_subtitle_path}") else: logger.warning("没有有效的字幕内容，将生成无字幕视频") merged_subtitle_path = "" except Exception as e: logger.error(f"合并音频/字幕文件失败: {str(e)}") # 确保即使合并失败也有默认值 if 'merged_audio_path' not in locals(): merged_audio_path = "" if 'merged_subtitle_path' not in locals(): merged_subtitle_path = "" else: logger.warning("没有需要合并的音频/字幕") merged_audio_path = "" merged_subtitle_path = "" if getattr(params, "subtitle_enabled", True): try: merged_subtitle_path = _create_programmatic_subtitle_file( task_id, new_script_list, params, ) except Exception as e: logger.warning(f"程序化字幕生成失败: {e}") _update_video_generation_task( task_id, progress=70, message="配音和字幕合并完成", step_current=4, ) """ 5. 合并视频 """ final_video_paths = [] combined_video_paths = [] combined_video_path = path.join(utils.task_dir(task_id), f"merger.mp4") logger.info(f"\n\n## 5. 合并视频: => {combined_video_path}") _update_video_generation_task( task_id, progress=75, message="正在合并视频片段", step_current=5, ) # 使用统一裁剪后的视频片段 video_clips = [] for new_script in new_script_list: video_path = new_script.get('video') if video_path and os.path.exists(video_path): video_clips.append(video_path) else: logger.error(f"片段 {new_script.get('_id')} 的视频文件不存在: {video_path}") logger.info(f"准备合并 {len(video_clips)} 个视频片段") merger_video.combine_clip_videos( output_video_path=combined_video_path, video_paths=video_clips, video_ost_list=video_ost, video_aspect=params.video_aspect, threads=params.n_threads ) _update_video_generation_task( task_id, progress=80, message="视频片段合并完成", step_current=5, ) """ 6. 合并字幕/BGM/配音/视频 """ output_video_path = path.join(utils.task_dir(task_id), f"combined.mp4") auto_transcription_enabled = _is_auto_transcription_enabled(params) and not bool(merged_subtitle_path) if _is_auto_transcription_enabled(params) and merged_subtitle_path: logger.info("已生成字幕文件，跳过最终视频自动转录") merge_output_video_path = ( path.join(utils.task_dir(task_id), "combined_without_auto_subtitles.mp4") if auto_transcription_enabled else output_video_path ) logger.info(f"\n\n## 6. 最后一步: 合并字幕/BGM/配音/视频 -> {merge_output_video_path}") _update_video_generation_task( task_id, progress=85, message="正在合成最终视频", step_current=6, ffmpeg_progress=0, ) bgm_path = utils.get_bgm_file( bgm_type=getattr(params, "bgm_type", "random"), bgm_file=getattr(params, "bgm_file", ""), ) # 获取优化的音量配置 optimized_volumes = get_recommended_volumes_for_content('mixed') # 检查是否有OST=1的原声片段，如果有，则保持原声音量为1.0不变 has_original_audio_segments = any(segment['OST'] == 1 for segment in list_script) # 应用用户设置和优化建议的组合 final_tts_volume = params.tts_volume if hasattr(params, 'tts_volume') and params.tts_volume != 1.0 else optimized_volumes['tts_volume'] # 关键修复：如果有原声片段，保持原声音量为1.0，确保与原视频音量一致 if has_original_audio_segments: final_original_volume = 1.0 # 保持原声音量不变 logger.info("检测到原声片段，原声音量设置为1.0以保持与原视频一致") else: final_original_volume = params.original_volume if hasattr(params, 'original_volume') and params.original_volume != 0.7 else optimized_volumes['original_volume'] final_bgm_volume = params.bgm_volume if hasattr(params, 'bgm_volume') and params.bgm_volume != 0.3 else optimized_volumes['bgm_volume'] logger.info(f"音量配置 - TTS: {final_tts_volume}, 原声: {final_original_volume}, BGM: {final_bgm_volume}") # 调用示例 options = { 'voice_volume': final_tts_volume, 'bgm_volume': final_bgm_volume, 'original_audio_volume': final_original_volume, 'keep_original_audio': True, 'subtitle_enabled': params.subtitle_enabled and not auto_transcription_enabled, 'subtitle_font': params.font_name, 'subtitle_font_size': params.font_size, 'subtitle_color': params.text_fore_color, 'subtitle_bg_color': None, 'subtitle_position': params.subtitle_position, 'custom_position': params.custom_position, 'threads': params.n_threads, **_build_subtitle_mask_options(params, enabled=not auto_transcription_enabled), } final_merge_progress_start = 85 final_merge_progress_end = 89 if auto_transcription_enabled else 99 def update_final_merge_progress(ffmpeg_progress: float): progress_span = final_merge_progress_end - final_merge_progress_start overall_progress = final_merge_progress_start + int( round((max(0.0, min(100.0, float(ffmpeg_progress))) / 100) * progress_span) ) _update_video_generation_task( task_id, progress=overall_progress, message="正在合成最终视频", step_current=6, ffmpeg_progress=ffmpeg_progress, ) generate_video.merge_materials( video_path=combined_video_path, audio_path=merged_audio_path, subtitle_path=merged_subtitle_path, bgm_path=bgm_path, output_path=merge_output_video_path, options=options, progress_callback=update_final_merge_progress, ) auto_subtitle_path = "" if auto_transcription_enabled: _update_video_generation_task( task_id, progress=90, message="正在自动转录最终视频", step_current=6, ) logger.info("\n\n## 7. 自动转录最终视频字幕") auto_subtitle_path = _transcribe_final_video(task_id, merge_output_video_path, params) _update_video_generation_task( task_id, progress=95, message="正在压入自动转录字幕", step_current=6, ) logger.info(f"\n\n## 8. 压入自动转录字幕 -> {output_video_path}") _merge_auto_transcribed_subtitles( source_video_path=merge_output_video_path, output_video_path=output_video_path, subtitle_path=auto_subtitle_path, params=params, ) final_video_paths.append(output_video_path) combined_video_paths.append(combined_video_path) logger.success(f"统一处理任务 {task_id} 已完成, 生成 {len(final_video_paths)} 个视频.") kwargs = { "videos": final_video_paths, "combined_videos": combined_video_paths } if auto_subtitle_path: kwargs["subtitles"] = [auto_subtitle_path] _update_video_generation_task( task_id, progress=100, message="视频生成完成", step_current=VIDEO_GENERATION_TOTAL_STEPS, state=const.TASK_STATE_COMPLETE, **kwargs ) return kwargs def validate_params(video_path, audio_path, output_file, params): """ 验证输入参数 Args: video_path: 视频文件路径 audio_path: 音频文件路径（可以为空字符串） output_file: 输出文件路径 params: 视频参数 Raises: FileNotFoundError: 文件不存在时抛出 ValueError: 参数无效时抛出 """ if not video_path: raise ValueError("视频路径不能为空") if not os.path.exists(video_path): raise FileNotFoundError(f"视频文件不存在: {video_path}") # 如果提供了音频路径，则验证文件是否存在 if audio_path and not os.path.exists(audio_path): raise FileNotFoundError(f"音频文件不存在: {audio_path}") if not output_file: raise ValueError("输出文件路径不能为空") # 确保输出目录存在 output_dir = os.path.dirname(output_file) if not os.path.exists(output_dir): os.makedirs(output_dir) if not params: raise ValueError("视频参数不能为空") if __name__ == "__main__": task_id = "demo" # 提前裁剪是为了方便检查视频 subclip_path_videos = { 1: '/Users/apple/Desktop/home/NarratoAI/storage/temp/clip_video/113343d127b5a09d0bf84b68bd1b3b97/vid_00-00-05-390@00-00-57-980.mp4', 2: '/Users/apple/Desktop/home/NarratoAI/storage/temp/clip_video/113343d127b5a09d0bf84b68bd1b3b97/vid_00-00-28-900@00-00-43-700.mp4', 3: '/Users/apple/Desktop/home/NarratoAI/storage/temp/clip_video/113343d127b5a09d0bf84b68bd1b3b97/vid_00-01-17-840@00-01-27-600.mp4', 4: '/Users/apple/Desktop/home/NarratoAI/storage/temp/clip_video/113343d127b5a09d0bf84b68bd1b3b97/vid_00-02-35-460@00-02-52-380.mp4', 5: '/Users/apple/Desktop/home/NarratoAI/storage/temp/clip_video/113343d127b5a09d0bf84b68bd1b3b97/vid_00-06-59-520@00-07-29-500.mp4', } params = VideoClipParams( video_clip_json_path="/Users/apple/Desktop/home/NarratoAI/resource/scripts/2025-0507-223311.json", video_origin_path="/Users/apple/Desktop/home/NarratoAI/resource/videos/merged_video_4938.mp4", ) start_subclip(task_id, params, subclip_path_videos)