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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)
from app.services import state as sm
from app.utils import utils
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"video_script_path: {video_script_path} \n\n", traceback.format_exc())
raise ValueError("解说脚本不存在!请检查配置是否正确。")
"""
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,
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 = 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 = ""
"""
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")
logger.info(f"\n\n## 6. 最后一步: 合并字幕/BGM/配音/视频 -> {output_video_path}")
# bgm_path = '/Users/apple/Desktop/home/NarratoAI/resource/songs/bgm.mp3'
bgm_path = utils.get_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, # 是否启用字幕 - 修复字幕开关bug
'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
}
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=output_video_path,
options=options
)
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
}
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}")
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"video_script_path: {video_script_path}")
raise ValueError("解说脚本不存在!请检查配置是否正确。")
"""
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. 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,
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 = 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 = ""
"""
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.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
)
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")
logger.info(f"\n\n## 6. 最后一步: 合并字幕/BGM/配音/视频 -> {output_video_path}")
bgm_path = utils.get_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,
'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
}
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=output_video_path,
options=options
)
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
}
sm.state.update_task(task_id, state=const.TASK_STATE_COMPLETE, progress=100, **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)