114 lines
4.1 KiB
Python
114 lines
4.1 KiB
Python
from os import path
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from loguru import logger
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from app.config import config
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from app.models.schema import VideoParams, VoiceNames
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from app.services import gpt, material, voice, video, subtitle
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from app.utils import utils
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def _parse_voice(name: str):
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# "female-zh-CN-XiaoxiaoNeural",
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# remove first part split by "-"
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if name not in VoiceNames:
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name = VoiceNames[0]
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parts = name.split("-")
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_lang = f"{parts[1]}-{parts[2]}"
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_voice = f"{_lang}-{parts[3]}"
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return _voice, _lang
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def start(task_id, params: VideoParams):
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"""
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{
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"video_subject": "",
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"video_aspect": "横屏 16:9（西瓜视频）",
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"voice_name": "女生-晓晓",
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"enable_bgm": false,
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"font_name": "STHeitiMedium 黑体-中",
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"text_color": "#FFFFFF",
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"font_size": 60,
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"stroke_color": "#000000",
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"stroke_width": 1.5
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}
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"""
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logger.info(f"start task: {task_id}")
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video_subject = params.video_subject
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voice_name, language = _parse_voice(params.voice_name)
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paragraph_number = params.paragraph_number
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n_threads = params.n_threads
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logger.info("\n\n## generating video script")
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script = gpt.generate_script(video_subject=video_subject, language=language, paragraph_number=paragraph_number)
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logger.info("\n\n## generating video terms")
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search_terms = gpt.generate_terms(video_subject=video_subject, video_script=script, amount=5)
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script_file = path.join(utils.task_dir(task_id), f"script.json")
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script_data = {
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"script": script,
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"search_terms": search_terms
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}
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with open(script_file, "w") as f:
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f.write(utils.to_json(script_data))
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audio_file = path.join(utils.task_dir(task_id), f"audio.mp3")
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subtitle_path = path.join(utils.task_dir(task_id), f"subtitle.srt")
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logger.info("\n\n## generating audio")
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sub_maker = voice.tts(text=script, voice_name=voice_name, voice_file=audio_file)
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subtitle_provider = config.app.get("subtitle_provider", "").strip().lower()
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logger.info(f"\n\n## generating subtitle, provider: {subtitle_provider}")
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if subtitle_provider == "edge":
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voice.create_subtitle(text=script, sub_maker=sub_maker, subtitle_file=subtitle_path)
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if subtitle_provider == "whisper":
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subtitle.create(audio_file=audio_file, subtitle_file=subtitle_path)
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logger.info("\n\n## correcting subtitle")
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subtitle.correct(subtitle_file=subtitle_path, video_script=script)
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logger.info("\n\n## downloading videos")
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video_paths = material.download_videos(task_id=task_id, search_terms=search_terms, video_aspect=params.video_aspect,
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wanted_count=20,
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minimum_duration=5)
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logger.info("\n\n## combining videos")
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combined_video_path = path.join(utils.task_dir(task_id), f"combined.mp4")
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video.combine_videos(combined_video_path=combined_video_path,
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video_paths=video_paths,
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audio_file=audio_file,
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video_aspect=params.video_aspect,
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max_clip_duration=5,
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threads=n_threads)
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final_video_path = path.join(utils.task_dir(task_id), f"final.mp4")
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bgm_file = video.get_bgm_file(bgm_name=params.bgm_name)
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logger.info("\n\n## generating video")
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# Put everything together
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video.generate_video(video_path=combined_video_path,
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audio_path=audio_file,
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subtitle_path=subtitle_path,
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output_file=final_video_path,
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video_aspect=params.video_aspect,
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threads=n_threads,
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font_name=params.font_name,
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fontsize=params.font_size,
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text_fore_color=params.text_fore_color,
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stroke_color=params.stroke_color,
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stroke_width=params.stroke_width,
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bgm_file=bgm_file
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)
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logger.start(f"task {task_id} finished")
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return {
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"video_file": final_video_path,
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}
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