mirror of
https://github.com/linyqh/NarratoAI.git
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128 lines
4.7 KiB
Python
128 lines
4.7 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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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
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def parse_timestamp(timestamp: str):
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"""解析时间戳字符串为秒数"""
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# 确保使用冒号作为分隔符
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timestamp = timestamp.replace('_', ':')
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return time_to_seconds(timestamp)
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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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# 从 "audio_00_06-00_24.mp3" 这样的格式中提取时间
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time_part = filename.split('_', 1)[1].split('.')[0] # 获取 "00_06-00_24" 部分
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start_time, end_time = time_part.split('-') # 分割成 "00_06" 和 "00_24"
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# 将下划线格式转换回冒号格式
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start_time = start_time.replace('_', ':')
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end_time = end_time.replace('_', ':')
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# 将时间戳转换为秒
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start_seconds = time_to_seconds(start_time)
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end_seconds = time_to_seconds(end_time)
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return start_seconds, end_seconds
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def time_to_seconds(time_str):
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"""将 "00:06" 或 "00_06" 格式转换为总秒数"""
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# 确保使用冒号作为分隔符
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time_str = time_str.replace('_', ':')
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try:
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parts = time_str.split(':')
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if len(parts) != 2:
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logger.error(f"Invalid time format: {time_str}")
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return 0
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return int(parts[0]) * 60 + int(parts[1])
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except (ValueError, IndexError) as e:
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logger.error(f"Error parsing time {time_str}: {str(e)}")
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return 0
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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 = merge_audio_files("test456", audio_files, total_duration, video_script)
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print(output_file)
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