洛阳网站建设优化案例亚马逊关键词优化怎么做
写在前面：主要原理是提取视频中的音频，通过语音识别文字的方法完成字幕提取；因此，不支持没有声音的视频。
1.音频提取
def convert_mp4_to_mp3(input_file, output_file):"""Convert MP4 video file to MP3 audio."""video_clip = VideoFileClip(input_file)audio = video_clip.audioaudio.write_audiofile(output_file)2.音频转文字
model = whisper.load_model(WHISPER_MODEL_PATH).to(device)
def transcribe_audio(file_path):"""Transcribe audio file using Whisper model."""result = model.transcribe(file_path,language="zh",# Explicitly tell Whisper to use Chinesetask="transcribe",initial_prompt="这是一段视频教程，请加上标点符号",beam_size=5,# Add beam_size directlyprompt="- 吃了没？- 吃了。",# Add prompt directlyword_timestamps=True, # 设置为 True 以获取单词时间戳fp16=False,)return result3.文字保存为字幕
def save_transcription_to_srt(segments, file_path):"""Save transcription segments to an SRT file."""with open(file_path, 'w', encoding='utf-8') as f:for i, segment in enumerate(segments):f.write(f"{i + 1}\n")f.write(f"{seconds_to_hmsm(segment['start'])} --> {seconds_to_hmsm(segment['end'])}\n")translated_text = translate_text(segment['text'])f.write(segment['text'] + f'\n{translated_text}\n\n')该代码中
translated_text = translate_text(segment['text'])功能是对字幕进行翻译，因此保存的字幕为双语字幕（解放字幕组劳动力o(*￣▽￣*)ブ）。翻译方法很多，简单提供一个基于ollama的翻译。
def translate_text(content):"""Translate text to English using Ollama."""stream = ollama.chat(model="llama3.2:1b",messages=[{"role": "user", "content": f"下列文字翻译为简体中文,只输出翻译结果：{content}"}],stream=True)output = ''for chunk in stream:output += chunk['message']['content']return output在上述功能的基础上，进阶两个功能。
4.更新字幕到视频内
def videoclip_with_subtitles(src_mp4, dst_mp4, srt_file):"""Add translated subtitles to the video."""video = VideoFileClip(src_mp4)subtitles = parse_srt(srt_file)text_clips = []for text, start, duration in tqdm(subtitles):# translated_text = translate_text(text)wrapped_text = insert_newlines(text, max_words=10)text_clip = (TextClip(wrapped_text, font='msyh.ttc', fontsize=30, color='red').set_position('top').set_duration(duration).set_start(start))text_clips.append(text_clip)final_video = CompositeVideoClip([video, *text_clips])final_video.write_videofile(dst_mp4, audio_codec='aac')其中字幕解析为：
def parse_srt(srt_file):"""Parse SRT file and return subtitles as text, start time, and duration."""subtitles = []with open(srt_file, 'r', encoding='utf-8') as file:content = file.read()entries = re.split(r'\n\n+', content.strip())for entry in entries:lines = entry.splitlines()if len(lines) >= 3:time_range = lines[1]start, end = time_range.split('-->')start_time = convert_srt_time_to_seconds(start)duration = convert_srt_time_to_seconds(end) - start_timetext = '\n'.join(lines[2:])subtitles.append((text, start_time, duration))return subtitles5.根据新的字幕，生成新的音频（方法很多，另开贴，更新后网址会贴在这里），即可以将外文音频转为中文音频。（代码还存在一些缺陷，修改后更新）
def text_to_speech(text, mp3_filename="output.mp3"):# 初始化TTS引擎engine = pyttsx3.init()# 设置语音属性（可选）engine.setProperty('rate', 150) # 语速engine.setProperty('volume', 1) # 音量 (0.0到1.0)# 保存为WAV文件wav_filename = "1.wav"engine.save_to_file(text, wav_filename)engine.runAndWait()# 使用pydub将WAV转换为MP3audio = AudioSegment.from_wav(wav_filename)audio.export(mp3_filename, format="mp3")# 读取字幕文件
subs = pysrt.open('data\\27364690929-1-192.srt')# 创建一个空的音频文件列表
audio_clips = []# 遍历每条字幕
for sub in tqdm(subs):# 将字幕文本转换为语音text_list = sub.text.split('\n')text_zh = text_list[-1] # 确保提取的文本是字符串而不是列表# 生成音频文件audio_filename = f"audio_temp/audio_{sub.index}.mp3"text_to_speech(text_zh, audio_filename)# 创建音频片段audio_clip = AudioFileClip(audio_filename)# 确保使用正确的单位：毫秒到秒# duration = (sub.end.ordinal - sub.start.ordinal) / 1000 # 转为秒# audio_clip = audio_clip.set_duration(duration)# 计算合适的开始时间start_time = sub.start.ordinal # 转为秒audio_clip = audio_clip.set_start(start_time)audio_clips.append(audio_clip)# 合并所有音频片段
final_audio = concatenate_audioclips(audio_clips)
将新的音频合并到视频内，即可完成音频替换
video = VideoFileClip('data\\27364690929-1-192.mp4').without_audio()# 将新的音频合并到视频中
final_video = video.set_audio(final_audio)# 保存最终视频
final_video.write_videofile('data\\27364690929-1-192-zh-audio.mp4', codec='libx264')github上有一些非常棒的类似项目，做完才看到，还没深入研究，大家可以上去多看看。