mirror of
https://github.com/linyqh/NarratoAI.git
synced 2025-12-16 07:02:54 +00:00
124 lines
4.6 KiB
Python
124 lines
4.6 KiB
Python
import os
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import json
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import subprocess
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import edge_tts
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from edge_tts import submaker
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from pydub import AudioSegment
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from typing import List, Dict
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from loguru import logger
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from app.utils import utils
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def check_ffmpeg():
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"""检查FFmpeg是否已安装"""
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try:
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subprocess.run(['ffmpeg', '-version'], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
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return True
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except FileNotFoundError:
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return False
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def merge_audio_files(task_id: str, audio_file_paths: List[str], total_duration: int, video_script: list):
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"""
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合并多个音频文件到一个指定总时长的音频文件中，并生成相应的字幕
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:param task_id: 任务ID
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:param audio_file_paths: 音频文件路径列表
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:param total_duration: 最终音频文件的总时长（秒）
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:param video_script: JSON格式的视频脚本
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"""
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output_dir = utils.task_dir(task_id)
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if not check_ffmpeg():
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logger.error("错误：FFmpeg未安装。请安装FFmpeg后再运行此脚本。")
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return None, None
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# 创建一个总时长为total_duration的空白音频
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blank_audio = AudioSegment.silent(duration=total_duration * 1000) # pydub使用毫秒
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# 创建SubMaker对象
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sub_maker = edge_tts.SubMaker()
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# 解析JSON格式的video_script
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script_data = video_script
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for segment in script_data:
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start_time, end_time = parse_timestamp(segment['new_timestamp'])
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duration = (end_time - start_time) * 1000 # 转换为毫秒
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if not segment['OST']:
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# 如果不是原声，则添加narration作为字幕
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sub_maker.create_sub((start_time * 1000, duration), segment['narration'])
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for audio_path in audio_file_paths:
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if not os.path.exists(audio_path):
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logger.info(f"警告：文件 {audio_path} 不存在，已跳过。")
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continue
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# 从文件名中提取时间戳
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filename = os.path.basename(audio_path)
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start_time, end_time = extract_timestamp(filename)
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# 读取音频文件
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try:
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audio = AudioSegment.from_mp3(audio_path)
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except Exception as e:
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logger.error(f"错误：无法读取文件 {audio_path}。错误信息：{str(e)}")
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continue
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# 将音频插入到空白音频的指定位置
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blank_audio = blank_audio.overlay(audio, position=start_time * 1000)
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# 尝试导出为WAV格式
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try:
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output_file = os.path.join(output_dir, "audio.wav")
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blank_audio.export(output_file, format="wav")
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logger.info(f"音频合并完成，已保存为 {output_file}")
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except Exception as e:
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logger.info(f"导出为WAV格式失败，尝试使用MP3格式：{str(e)}")
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try:
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output_file = os.path.join(output_dir, "audio.mp3")
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blank_audio.export(output_file, format="mp3", codec="libmp3lame")
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logger.info(f"音频合并完成，已保存为 {output_file}")
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except Exception as e:
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logger.error(f"导出音频失败：{str(e)}")
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return None, None
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return output_file, sub_maker
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def parse_timestamp(timestamp: str) -> tuple:
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"""解析时间戳字符串为秒数"""
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start, end = timestamp.split('-')
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return time_to_seconds(*start.split(':')), time_to_seconds(*end.split(':'))
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def extract_timestamp(filename):
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"""从文件名中提取开始和结束时间戳"""
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time_part = filename.split('_')[1].split('.')[0]
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times = time_part.split('-')
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# 将时间戳转换为秒
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start_seconds = time_to_seconds(times[0], times[1])
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end_seconds = time_to_seconds(times[2], times[3])
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return start_seconds, end_seconds
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def time_to_seconds(minutes, seconds):
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"""将分钟和秒转换为总秒数"""
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return int(minutes) * 60 + int(seconds)
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if __name__ == "__main__":
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# 示例用法
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audio_files =[
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"/Users/apple/Desktop/home/NarratoAI/storage/tasks/test456/audio_00-06-00-24.mp3",
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"/Users/apple/Desktop/home/NarratoAI/storage/tasks/test456/audio_00-32-00-38.mp3",
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"/Users/apple/Desktop/home/NarratoAI/storage/tasks/test456/audio_00-43-00-52.mp3",
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"/Users/apple/Desktop/home/NarratoAI/storage/tasks/test456/audio_00-52-01-09.mp3",
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"/Users/apple/Desktop/home/NarratoAI/storage/tasks/test456/audio_01-13-01-15.mp3",
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]
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total_duration = 38
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video_script_path = "/Users/apple/Desktop/home/NarratoAI/resource/scripts/test003.json"
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with open(video_script_path, "r", encoding="utf-8") as f:
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video_script = json.load(f)
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output_file, sub_maker = merge_audio_files("test456", audio_files, total_duration, video_script)
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print(output_file, sub_maker) |