mirror of
https://github.com/linyqh/NarratoAI.git
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优化 webui task 逻辑30%；新增检查/修复脚本方法
This commit is contained in:
linyq
parent
d6663fde21
commit
990994e9cd
@ -3,7 +3,7 @@ from enum import Enum
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from typing import Any, List, Optional
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import pydantic
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from pydantic import BaseModel
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from pydantic import BaseModel, Field
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# 忽略 Pydantic 的特定警告
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warnings.filterwarnings(
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@ -330,42 +330,39 @@ class BgmUploadResponse(BaseResponse):
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class VideoClipParams(BaseModel):
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video_subject: Optional[str] = "春天的花海让人心旷神怡"
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"""
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NarratoAI 数据模型
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"""
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video_clip_json: Optional[list] = Field(default=[], description="LLM 生成的视频剪辑脚本内容")
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video_clip_json_path: Optional[str] = Field(default="", description="LLM 生成的视频剪辑脚本路径")
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video_origin_path: Optional[str] = Field(default="", description="原视频路径")
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video_aspect: Optional[VideoAspect] = Field(default=VideoAspect.portrait.value, description="视频比例")
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video_language: Optional[str] = Field(default="zh-CN", description="视频语言")
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video_clip_json: Optional[str] = "" # 视频剪辑脚本
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video_origin_path: Optional[str] = "" # 原视频路径
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video_aspect: Optional[VideoAspect] = VideoAspect.portrait.value # 视频比例
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video_clip_duration: Optional[int] = 5 # 视频片段时长
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video_count: Optional[int] = 1 # 视频片段数量
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video_source: Optional[str] = "local"
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video_language: Optional[str] = "" # 自动检测
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# video_clip_duration: Optional[int] = 5 # 视频片段时长
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# video_count: Optional[int] = 1 # 视频片段数量
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# video_source: Optional[str] = "local"
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# video_concat_mode: Optional[VideoConcatMode] = VideoConcatMode.random.value
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# # 女性
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# "zh-CN-XiaoxiaoNeural",
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# "zh-CN-XiaoyiNeural",
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# # 男性
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# "zh-CN-YunjianNeural" 男声
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# "zh-CN-YunyangNeural",
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# "zh-CN-YunxiNeural",
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voice_name: Optional[str] = "zh-CN-YunjianNeural" # 语音名称 指定选择：
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voice_volume: Optional[float] = 1.0 # 语音音量
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voice_rate: Optional[float] = 1.0 # 语速
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voice_name: Optional[str] = Field(default="zh-CN-YunjianNeural", description="语音名称")
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voice_volume: Optional[float] = Field(default=1.0, description="语音音量")
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voice_rate: Optional[float] = Field(default=1.0, description="语速")
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bgm_name: Optional[str] = "random" # 背景音乐名称
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bgm_type: Optional[str] = "random" # 背景音乐类型
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bgm_file: Optional[str] = "" # 背景音乐文件
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bgm_volume: Optional[float] = 0.2
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bgm_name: Optional[str] = Field(default="random", description="背景音乐名称")
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bgm_type: Optional[str] = Field(default="random", description="背景音乐类型")
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bgm_file: Optional[str] = Field(default="", description="背景音乐文件")
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bgm_volume: Optional[float] = Field(default=0.2, description="背景音乐音量")
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subtitle_enabled: Optional[bool] = True # 是否启用字幕
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subtitle_position: Optional[str] = "bottom" # top, bottom, center
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font_name: Optional[str] = "STHeitiMedium.ttc" # 字体名称
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text_fore_color: Optional[str] = "#FFFFFF" # 文字前景色
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text_background_color: Optional[str] = "transparent" # 文字背景色
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subtitle_enabled: Optional[bool] = Field(default=True, description="是否启用字幕")
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subtitle_position: Optional[str] = Field(default="bottom", description="字幕位置") # top, bottom, center
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font_name: Optional[str] = Field(default="STHeitiMedium.ttc", description="字体名称")
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text_fore_color: Optional[str] = Field(default="#FFFFFF", description="文字前景色")
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text_background_color: Optional[str] = Field(default="transparent", description="文字背景色")
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font_size: int = 60 # 文字大小
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stroke_color: Optional[str] = "#000000" # 文字描边颜色
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stroke_width: float = 1.5 # 文字描边宽度
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custom_position: float = 70.0 # 自定义位置
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n_threads: Optional[int] = 2 # 线程数
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paragraph_number: Optional[int] = 1 # 段落数量
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font_size: int = Field(default=60, description="文字大小")
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stroke_color: Optional[str] = Field(default="#000000", description="文字描边颜色")
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stroke_width: float = Field(default=1.5, description="文字描边宽度")
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custom_position: float = Field(default=70.0, description="自定义位置")
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# n_threads: Optional[int] = 2 # 线程数
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# paragraph_number: Optional[int] = 1 # 段落数量
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@ -352,7 +352,8 @@ def compress_video(input_path: str, output_path: str):
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input_path: 输入视频文件路径
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output_path: 输出压缩后的视频文件路径
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"""
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ffmpeg_path = "E:\\projects\\NarratoAI_v0.1.2\\lib\\ffmpeg\\ffmpeg-7.0-essentials_build\\ffmpeg.exe" # 指定 ffmpeg 的完整路径
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# 指定 ffmpeg 的完整路径
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ffmpeg_path = os.getenv("FFMPEG_PATH") or config.app.get("ffmpeg_path")
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# 如果压缩后的视频文件已经存在，则直接使用
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if os.path.exists(output_path):
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@ -326,17 +326,20 @@ def start(task_id, params: VideoParams, stop_at: str = "video"):
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def start_subclip(task_id, params: VideoClipParams, subclip_path_videos):
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"""
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后台任务（自动剪辑视频进行剪辑）
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task_id: 任务ID
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params: 剪辑参数
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subclip_path_videos: 视频文件路径
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"""
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logger.info(f"\n\n## 开始任务: {task_id}")
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sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=5)
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# tts 角色名称
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voice_name = voice.parse_voice_name(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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max_clip_duration = params.video_clip_duration
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logger.info("\n\n## 1. 读取视频json脚本")
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video_script_path = path.join(params.video_clip_json)
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video_script_path = path.join(params.video_clip_json_path)
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# 判断json文件是否存在
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if path.exists(video_script_path):
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try:
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@ -430,7 +433,7 @@ def start_subclip(task_id, params: VideoClipParams, subclip_path_videos):
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video_ost_list=video_ost,
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list_script=list_script,
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video_aspect=params.video_aspect,
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threads=n_threads
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threads=1 # 暂时只支持单线程
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)
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_progress += 50 / params.video_count / 2
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198
app/utils/check_script.py
Normal file
198
app/utils/check_script.py
Normal file
@ -0,0 +1,198 @@
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import json
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from loguru import logger
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import os
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from datetime import datetime, timedelta
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import re
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def time_to_seconds(time_str):
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time_obj = datetime.strptime(time_str, "%M:%S")
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return timedelta(minutes=time_obj.minute, seconds=time_obj.second).total_seconds()
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def seconds_to_time_str(seconds):
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minutes, seconds = divmod(int(seconds), 60)
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return f"{minutes:02d}:{seconds:02d}"
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def check_script(file_path, total_duration):
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with open(file_path, 'r', encoding='utf-8') as f:
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data = json.load(f)
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errors = []
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ost_narrations = set()
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last_end_time = 0
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logger.info(f"开始检查文件: {file_path}")
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logger.info(f"视频总时长: {total_duration:.2f} 秒")
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logger.info("=" * 50)
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for i, item in enumerate(data, 1):
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logger.info(f"\n检查第 {i} 项:")
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# 检查所有必需字段是否存在
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required_fields = ['picture', 'timestamp', 'narration', 'OST', 'new_timestamp']
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for field in required_fields:
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if field not in item:
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errors.append(f"第 {i} 项缺少 {field} 字段")
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logger.info(f" - 错误: 缺少 {field} 字段")
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else:
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logger.info(f" - {field}: {item[field]}")
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# 检查 OST 为 false 的情况
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if item.get('OST') == False:
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if not item.get('narration'):
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errors.append(f"第 {i} 项 OST 为 false，但 narration 为空")
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logger.info(" - 错误: OST 为 false，但 narration 为空")
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elif len(item['narration']) > 30:
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errors.append(f"第 {i} 项 OST 为 false，但 narration 超过 30 字")
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logger.info(f" - 错误: OST 为 false，但 narration 超过 30 字 (当前: {len(item['narration'])} 字)")
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else:
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logger.info(" - OST 为 false，narration 检查通过")
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# 检查 OST 为 true 的情况
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if item.get('OST') == True:
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if not item.get('narration').startswith('原声播放_'):
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errors.append(f"第 {i} 项 OST 为 true，但 narration 不是 '原声播放_xxx' 格式")
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logger.info(" - 错误: OST 为 true，但 narration 不是 '原声播放_xxx' 格式")
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elif item['narration'] in ost_narrations:
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errors.append(f"第 {i} 项 OST 为 true，但 narration '{item['narration']}' 不是唯一值")
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logger.info(f" - 错误: OST 为 true，但 narration '{item['narration']}' 不是唯一值")
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else:
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logger.info(" - OST 为 true，narration 检查通过")
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ost_narrations.add(item['narration'])
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# 检查 timestamp 是否重叠
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if 'timestamp' in item:
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start, end = map(time_to_seconds, item['timestamp'].split('-'))
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if start < last_end_time:
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errors.append(f"第 {i} 项 timestamp '{item['timestamp']}' 与前一项重叠")
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logger.info(f" - 错误: timestamp '{item['timestamp']}' 与前一项重叠")
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else:
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logger.info(f" - timestamp '{item['timestamp']}' 检查通过")
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last_end_time = end
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# 检查 timestamp 是否超过总时长
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if end > total_duration:
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errors.append(f"第 {i} 项 timestamp '{item['timestamp']}' 超过总时长 {total_duration:.2f} 秒")
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logger.info(f" - 错误: timestamp '{item['timestamp']}' 超过总时长 {total_duration:.2f} 秒")
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else:
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logger.info(f" - timestamp 在总时长范围内")
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# 检查 new_timestamp 是否连续
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logger.info("\n检查 new_timestamp 连续性:")
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last_end_time = 0
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for i, item in enumerate(data, 1):
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if 'new_timestamp' in item:
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start, end = map(time_to_seconds, item['new_timestamp'].split('-'))
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if start != last_end_time:
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errors.append(f"第 {i} 项 new_timestamp '{item['new_timestamp']}' 与前一项不连续")
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logger.info(f" - 错误: 第 {i} 项 new_timestamp '{item['new_timestamp']}' 与前一项不连续")
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else:
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logger.info(f" - 第 {i} 项 new_timestamp '{item['new_timestamp']}' 连续性检查通过")
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last_end_time = end
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if errors:
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logger.info("检查结果：不通过")
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logger.info("发现以下错误：")
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for error in errors:
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logger.info(f"- {error}")
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fix_script(file_path, data, errors)
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else:
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logger.info("检查结果：通过")
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logger.info("所有项目均符合规则要求。")
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def fix_script(file_path, data, errors):
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logger.info("\n开始修复脚本...")
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fixed_data = []
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for i, item in enumerate(data, 1):
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if item['OST'] == False and (not item['narration'] or len(item['narration']) > 30):
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if not item['narration']:
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logger.info(f"第 {i} 项 narration 为空，需要人工参与修复。")
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fixed_data.append(item)
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else:
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logger.info(f"修复第 {i} 项 narration 超过 30 字的问题...")
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fixed_items = split_narration(item)
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fixed_data.extend(fixed_items)
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else:
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fixed_data.append(item)
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for error in errors:
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if not error.startswith("第") or "OST 为 false" not in error:
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logger.info(f"需要人工参与修复: {error}")
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# 生成新的文件名
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file_name, file_ext = os.path.splitext(file_path)
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new_file_path = f"{file_name}_revise{file_ext}"
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# 保存修复后的数据到新文件
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with open(new_file_path, 'w', encoding='utf-8') as f:
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json.dump(fixed_data, f, ensure_ascii=False, indent=4)
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logger.info(f"\n脚本修复完成，已保存到新文件: {new_file_path}")
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def split_narration(item):
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narration = item['narration']
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chunks = smart_split(narration)
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start_time, end_time = map(time_to_seconds, item['timestamp'].split('-'))
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new_start_time, new_end_time = map(time_to_seconds, item['new_timestamp'].split('-'))
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total_duration = end_time - start_time
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new_total_duration = new_end_time - new_start_time
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chunk_duration = total_duration / len(chunks)
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new_chunk_duration = new_total_duration / len(chunks)
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fixed_items = []
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for i, chunk in enumerate(chunks):
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new_item = item.copy()
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new_item['narration'] = chunk
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chunk_start = start_time + i * chunk_duration
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chunk_end = chunk_start + chunk_duration
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new_item['timestamp'] = f"{seconds_to_time_str(chunk_start)}-{seconds_to_time_str(chunk_end)}"
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new_chunk_start = new_start_time + i * new_chunk_duration
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new_chunk_end = new_chunk_start + new_chunk_duration
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new_item['new_timestamp'] = f"{seconds_to_time_str(new_chunk_start)}-{seconds_to_time_str(new_chunk_end)}"
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fixed_items.append(new_item)
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return fixed_items
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def smart_split(text, target_length=30):
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# 使用正则表达式分割文本，保留标点符号
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segments = re.findall(r'[^，。！？,!?]+[，。！？,!?]?', text)
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result = []
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current_chunk = ""
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for segment in segments:
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if len(current_chunk) + len(segment) <= target_length:
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current_chunk += segment
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else:
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if current_chunk:
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result.append(current_chunk.strip())
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current_chunk = segment
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if current_chunk:
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result.append(current_chunk.strip())
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# 如果有任何chunk超过了目标长度，进行进一步的分割
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final_result = []
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for chunk in result:
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if len(chunk) > target_length:
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sub_chunks = [chunk[i:i + target_length] for i in range(0, len(chunk), target_length)]
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final_result.extend(sub_chunks)
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else:
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final_result.append(chunk)
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return final_result
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if __name__ == "__main__":
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file_path = "/Users/apple/Desktop/home/NarratoAI/resource/scripts/2024-0923-085036.json"
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total_duration = 280
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check_script(file_path, total_duration)
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@ -24,3 +24,4 @@ opencv-python~=4.9.0.80
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# https://techcommunity.microsoft.com/t5/ai-azure-ai-services-blog/9-more-realistic-ai-voices-for-conversations-now-generally/ba-p/4099471
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azure-cognitiveservices-speech~=1.37.0
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git-changelog~=2.5.2
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watchdog==5.0.2
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113
webui.py
113
webui.py
@ -1,29 +1,5 @@
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import sys
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import os
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import glob
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import json
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import time
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import datetime
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import traceback
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import streamlit as st
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from uuid import uuid4
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import platform
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import streamlit.components.v1 as components
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from loguru import logger
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from app.config import config
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from app.models.const import FILE_TYPE_VIDEOS
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from app.models.schema import VideoClipParams, VideoAspect, VideoConcatMode
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from app.services import task as tm, llm, voice, material
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from app.utils import utils
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# # 将项目的根目录添加到系统路径中，以允许从项目导入模块
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root_dir = os.path.dirname(os.path.realpath(__file__))
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if root_dir not in sys.path:
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sys.path.append(root_dir)
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print("******** sys.path ********")
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print(sys.path)
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print("*" * 20)
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st.set_page_config(
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page_title="NarratoAI",
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@ -37,6 +13,31 @@ st.set_page_config(
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},
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)
|
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import sys
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import os
|
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import glob
|
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import json
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import time
|
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import datetime
|
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import traceback
|
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from uuid import uuid4
|
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import platform
|
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import streamlit.components.v1 as components
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from loguru import logger
|
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|
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from app.models.const import FILE_TYPE_VIDEOS
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from app.models.schema import VideoClipParams, VideoAspect, VideoConcatMode
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from app.services import task as tm, llm, voice, material
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from app.utils import utils
|
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# # 将项目的根目录添加到系统路径中，以允许从项目导入模块
|
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root_dir = os.path.dirname(os.path.realpath(__file__))
|
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if root_dir not in sys.path:
|
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sys.path.append(root_dir)
|
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print("******** sys.path ********")
|
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print(sys.path)
|
||||
print("*" * 20)
|
||||
|
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proxy_url_http = config.proxy.get("http", "") or os.getenv("VPN_PROXY_URL", "")
|
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proxy_url_https = config.proxy.get("https", "") or os.getenv("VPN_PROXY_URL", "")
|
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os.environ["HTTP_PROXY"] = proxy_url_http
|
||||
@ -59,8 +60,6 @@ i18n_dir = os.path.join(root_dir, "webui", "i18n")
|
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config_file = os.path.join(root_dir, "webui", ".streamlit", "webui.toml")
|
||||
system_locale = utils.get_system_locale()
|
||||
|
||||
if 'video_subject' not in st.session_state:
|
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st.session_state['video_subject'] = ''
|
||||
if 'video_clip_json' not in st.session_state:
|
||||
st.session_state['video_clip_json'] = ''
|
||||
if 'video_plot' not in st.session_state:
|
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@ -189,16 +188,7 @@ with st.expander(tr("Basic Settings"), expanded=False):
|
||||
if HTTPS_PROXY:
|
||||
config.proxy["https"] = HTTPS_PROXY
|
||||
|
||||
|
||||
with middle_config_panel:
|
||||
# openai
|
||||
# moonshot (月之暗面)
|
||||
# oneapi
|
||||
# g4f
|
||||
# azure
|
||||
# qwen (通义千问)
|
||||
# gemini
|
||||
# ollama
|
||||
llm_providers = ['Gemini']
|
||||
saved_llm_provider = config.app.get("llm_provider", "OpenAI").lower()
|
||||
saved_llm_provider_index = 0
|
||||
@ -470,6 +460,7 @@ with left_panel:
|
||||
else:
|
||||
st.error(tr("请先生成视频脚本"))
|
||||
|
||||
|
||||
# 裁剪视频
|
||||
with button_columns[1]:
|
||||
if st.button(tr("Crop Video"), key="auto_crop_video", use_container_width=True):
|
||||
@ -479,50 +470,6 @@ with left_panel:
|
||||
with middle_panel:
|
||||
with st.container(border=True):
|
||||
st.write(tr("Video Settings"))
|
||||
# video_concat_modes = [
|
||||
# (tr("Sequential"), "sequential"),
|
||||
# (tr("Random"), "random"),
|
||||
# ]
|
||||
# video_sources = [
|
||||
# (tr("Pexels"), "pexels"),
|
||||
# (tr("Pixabay"), "pixabay"),
|
||||
# (tr("Local file"), "local"),
|
||||
# (tr("TikTok"), "douyin"),
|
||||
# (tr("Bilibili"), "bilibili"),
|
||||
# (tr("Xiaohongshu"), "xiaohongshu"),
|
||||
# ]
|
||||
#
|
||||
# saved_video_source_name = config.app.get("video_source", "pexels")
|
||||
# saved_video_source_index = [v[1] for v in video_sources].index(
|
||||
# saved_video_source_name
|
||||
# )
|
||||
#
|
||||
# selected_index = st.selectbox(
|
||||
# tr("Video Source"),
|
||||
# options=range(len(video_sources)),
|
||||
# format_func=lambda x: video_sources[x][0],
|
||||
# index=saved_video_source_index,
|
||||
# )
|
||||
# params.video_source = video_sources[selected_index][1]
|
||||
# config.app["video_source"] = params.video_source
|
||||
#
|
||||
# if params.video_source == "local":
|
||||
# _supported_types = FILE_TYPE_VIDEOS + FILE_TYPE_IMAGES
|
||||
# uploaded_files = st.file_uploader(
|
||||
# "Upload Local Files",
|
||||
# type=["mp4", "mov", "avi", "flv", "mkv", "jpg", "jpeg", "png"],
|
||||
# accept_multiple_files=True,
|
||||
# )
|
||||
|
||||
# selected_index = st.selectbox(
|
||||
# tr("Video Concat Mode"),
|
||||
# index=1,
|
||||
# options=range(len(video_concat_modes)), # 使用索引作为内部选项值
|
||||
# format_func=lambda x: video_concat_modes[x][0], # 显示给用户的是标签
|
||||
# )
|
||||
# params.video_concat_mode = VideoConcatMode(
|
||||
# video_concat_modes[selected_index][1]
|
||||
# )
|
||||
|
||||
# 视频比例
|
||||
video_aspect_ratios = [
|
||||
@ -582,8 +529,9 @@ with middle_panel:
|
||||
params.voice_name = voice_name
|
||||
config.ui["voice_name"] = voice_name
|
||||
|
||||
# 试听语言合成
|
||||
if st.button(tr("Play Voice")):
|
||||
play_content = params.video_subject
|
||||
play_content = "这是一段试听语言"
|
||||
if not play_content:
|
||||
play_content = params.video_script
|
||||
if not play_content:
|
||||
@ -779,6 +727,7 @@ with st.expander(tr("Video Check"), expanded=False):
|
||||
caijian()
|
||||
st.rerun()
|
||||
|
||||
# 开始按钮
|
||||
start_button = st.button(tr("Generate Video"), use_container_width=True, type="primary")
|
||||
if start_button:
|
||||
config.save_config()
|
||||
@ -800,10 +749,6 @@ if start_button:
|
||||
st.error(tr("视频文件不能为空"))
|
||||
scroll_to_bottom()
|
||||
st.stop()
|
||||
if llm_provider != 'g4f' and not config.app.get(f"{llm_provider}_api_key", ""):
|
||||
st.error(tr("请输入 LLM API 密钥"))
|
||||
scroll_to_bottom()
|
||||
st.stop()
|
||||
|
||||
log_container = st.empty()
|
||||
log_records = []
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user