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refactor(app): 优化视频剪辑函数（毫秒+缓存目录）
- 优化时间格式处理，支持更灵活的时间输入- 改进视频缓存目录结构，基于原视频生成哈希值 - 优化日志输出和错误处理 - 调整合并视频功能，移除未使用的示例代码 - 修复了一些与时间戳相关的小问题
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linyqh
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974a219dd3
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@ -254,10 +254,14 @@ def download_videos(
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def time_to_seconds(time_str: str) -> float:
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"""
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将时间字符串转换为秒数，支持多种格式：
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1. 'HH:MM:SS,mmm' (时:分:秒,毫秒)
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2. 'MM:SS' (分:秒)
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3. 'SS' (秒)
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将时间字符串转换为秒数
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支持格式: 'HH:MM:SS,mmm' (时:分:秒,毫秒)
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Args:
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time_str: 时间字符串,如 "00:00:20,100"
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Returns:
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float: 转换后的秒数(包含毫秒)
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"""
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try:
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# 处理毫秒部分
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@ -268,26 +272,30 @@ def time_to_seconds(time_str: str) -> float:
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time_part = time_str
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ms = 0
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# 根据格式分别处理
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# 处理时分秒
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parts = time_part.split(':')
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if len(parts) == 3: # HH:MM:SS
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time_obj = datetime.strptime(time_part, "%H:%M:%S")
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seconds = time_obj.hour * 3600 + time_obj.minute * 60 + time_obj.second
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elif len(parts) == 2: # MM:SS
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time_obj = datetime.strptime(time_part, "%M:%S")
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seconds = time_obj.minute * 60 + time_obj.second
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else: # SS
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seconds = float(time_part)
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h, m, s = map(int, parts)
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seconds = h * 3600 + m * 60 + s
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else:
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raise ValueError("时间格式必须为 HH:MM:SS,mmm")
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return seconds + ms
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except ValueError as e:
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logger.error(f"时间格式错误: {time_str}")
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raise ValueError(f"时间格式错误，支持的格式：HH:MM:SS,mmm 或 MM:SS 或 SS") from e
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raise ValueError(f"时间格式错误: 必须为 HH:MM:SS,mmm 格式") from e
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def format_timestamp(seconds: float) -> str:
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"""
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将秒数转换为可读的时间格式 (HH:MM:SS,mmm)
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Args:
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seconds: 秒数(可包含毫秒)
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Returns:
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str: 格式化的时间字符串,如 "00:00:20,100"
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"""
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hours = int(seconds // 3600)
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minutes = int((seconds % 3600) // 60)
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@ -301,41 +309,44 @@ def format_timestamp(seconds: float) -> str:
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def save_clip_video(timestamp: str, origin_video: str, save_dir: str = "") -> dict:
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"""
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保存剪辑后的视频
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Args:
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timestamp: 需要裁剪的单个时间戳，支持格式：
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1. 'HH:MM:SS,mmm-HH:MM:SS,mmm' (时:分:秒,毫秒)
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2. 'MM:SS-MM:SS' (分:秒-分:秒)
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3. 'SS-SS' (秒-秒)
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timestamp: 需要裁剪的时间戳,格式为 'HH:MM:SS,mmm-HH:MM:SS,mmm'
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例如: '00:00:00,000-00:00:20,100'
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origin_video: 原视频路径
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save_dir: 存储目录
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Returns:
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裁剪后的视频路径，格式为 {timestamp: video_path}
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dict: 裁剪后的视频路径,格式为 {timestamp: video_path}
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"""
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# 使用新的路径结构
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if not save_dir:
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save_dir = utils.storage_dir("cache_videos")
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base_dir = os.path.join(utils.temp_dir(), "clip_video")
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video_hash = utils.md5(origin_video)
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save_dir = os.path.join(base_dir, video_hash)
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if not os.path.exists(save_dir):
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os.makedirs(save_dir)
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video_id = f"vid-{timestamp.replace(':', '_').replace(',', '-')}"
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video_path = f"{save_dir}/{video_id}.mp4"
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# 生成更规范的视频文件名
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video_id = f"vid-{timestamp.replace(':', '-').replace(',', '_')}"
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video_path = os.path.join(save_dir, f"{video_id}.mp4")
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if os.path.exists(video_path) and os.path.getsize(video_path) > 0:
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logger.info(f"video already exists: {video_path}")
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return {timestamp: video_path}
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try:
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# 先加载视频获取总时长
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# 加载视频获取总时长
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video = VideoFileClip(origin_video)
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total_duration = video.duration
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# 获取目标时间段
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# 解析时间戳
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start_str, end_str = timestamp.split('-')
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start = time_to_seconds(start_str)
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end = time_to_seconds(end_str)
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# 验证时间段是否有效
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# 验证时间段
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if start >= total_duration:
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logger.warning(f"起始时间 {format_timestamp(start)} ({start:.3f}秒) 超出视频总时长 {format_timestamp(total_duration)} ({total_duration:.3f}秒)")
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video.close()
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@ -353,6 +364,8 @@ def save_clip_video(timestamp: str, origin_video: str, save_dir: str = "") -> di
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# 剪辑视频
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duration = end - start
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logger.info(f"开始剪辑视频: {format_timestamp(start)} - {format_timestamp(end)}，时长 {format_timestamp(duration)}")
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# 剪辑视频
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subclip = video.subclip(start, end)
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try:
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@ -401,13 +414,21 @@ def clip_videos(task_id: str, timestamp_terms: List[str], origin_video: str, pro
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剪辑视频
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Args:
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task_id: 任务id
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timestamp_terms: 需要剪辑的时间戳列表，如:['00:00-00:20', '00:36-00:40', '07:07-07:22']
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timestamp_terms: 需要剪辑的时间戳列表，如:['00:00:00,000-00:00:20,100', '00:00:43,039-00:00:46,959']
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origin_video: 原视频路径
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progress_callback: 进度回调函数
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Returns:
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剪辑后的视频路径
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"""
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# 创建基于原视频的缓存目录
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video_cache_dir = os.path.join(utils.temp_dir(), "video")
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video_hash = utils.md5(origin_video + str(os.path.getmtime(origin_video)))
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video_clips_dir = os.path.join(video_cache_dir, video_hash)
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if not os.path.exists(video_clips_dir):
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os.makedirs(video_clips_dir)
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video_paths = {}
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total_items = len(timestamp_terms)
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for index, item in enumerate(timestamp_terms):
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@ -415,8 +436,9 @@ def clip_videos(task_id: str, timestamp_terms: List[str], origin_video: str, pro
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if material_directory == "task":
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material_directory = utils.task_dir(task_id)
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elif material_directory and not os.path.isdir(material_directory):
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material_directory = ""
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material_directory = video_clips_dir # 如果没有指定material_directory,使用缓存目录
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logger.debug("material_directory:",material_directory)
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try:
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saved_video_path = save_clip_video(timestamp=item, origin_video=origin_video, save_dir=material_directory)
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if saved_video_path:
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@ -429,6 +451,7 @@ def clip_videos(task_id: str, timestamp_terms: List[str], origin_video: str, pro
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except Exception as e:
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logger.error(f"视频裁剪失败: {utils.to_json(item)} =>\n{str(traceback.format_exc())}")
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return {}
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logger.success(f"裁剪 {len(video_paths)} videos")
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return video_paths
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@ -490,27 +513,5 @@ def merge_videos(video_paths, ost_list):
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return output_file
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# 使用示例
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# if __name__ == "__main__":
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# video_paths = ['/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-01_17-01_37.mp4', '/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-00_00-00_06.mp4',
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# '/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-00_06-00_09.mp4', '/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-01_03-01_10.mp4',
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# '/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-01_10-01_17.mp4', '/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-00_24-00_27.mp4',
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# '/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-01_28-01_36.mp4', '/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-00_32-00_41.mp4',
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# '/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-01_36-01_58.mp4', '/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-00_12-00_15.mp4',
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# '/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-00_09-00_12.mp4', '/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-02_12-02_25.mp4',
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# '/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-02_03-02_12.mp4', '/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-01_58-02_03.mp4',
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# '/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-03_14-03_18.mp4', '/Users/apple/Desktop/home/NarratoAI/storage/cache_videos/vid-03_18-03_20.mp4']
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#
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# ost_list = [True, False, False, False, False, False, False, False, True, False, False, False, False, False, False,
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# False]
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#
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# result = merge_videos(video_paths, ost_list)
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# if result:
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# print(f"合并后的视频文件：{result}")
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# else:
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# print("视频合并失败")
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#
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if __name__ == "__main__":
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save_clip_video('00:50-01:41', 'E:\\projects\\NarratoAI\\resource\\videos\\WeChat_20241110144511.mp4')
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@ -68,8 +68,9 @@ def get_batch_timestamps(batch_files, prev_batch_files=None):
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将时间字符串转换为 HH:MM:SS,mmm 格式
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Args:
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time_str: 9位数字字符串,格式为 MMSSSMMM
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例如: 000050100 表示 00分50秒100毫秒
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time_str: 9位数字字符串,格式为 HHMMSSMMM
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例如: 000010000 表示 00时00分10秒000毫秒
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000043039 表示 00时00分43秒039毫秒
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Returns:
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str: HH:MM:SS,mmm 格式的时间戳
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@ -79,22 +80,12 @@ def get_batch_timestamps(batch_files, prev_batch_files=None):
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logger.warning(f"Invalid timestamp format: {time_str}")
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return "00:00:00,000"
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# 提取分钟、秒和毫秒
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minutes = int(time_str[-9:-6]) # 取后9位的前3位作为分钟
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seconds = int(time_str[-6:-3]) # 取中间3位作为秒数
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milliseconds = int(time_str[-3:]) # 取最后3位作为毫秒
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# 从时间戳中提取时、分、秒和毫秒
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hours = int(time_str[0:2]) # 前2位作为小时
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minutes = int(time_str[2:4]) # 第3-4位作为分钟
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seconds = int(time_str[4:6]) # 第5-6位作为秒数
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milliseconds = int(time_str[6:]) # 最后3位作为毫秒
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# 处理进位
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if seconds >= 60:
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minutes += seconds // 60
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seconds = seconds % 60
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if minutes >= 60:
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hours = minutes // 60
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minutes = minutes % 60
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else:
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hours = 0
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return f"{hours:02d}:{minutes:02d}:{seconds:02d},{milliseconds:03d}"
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except ValueError as e:
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@ -113,7 +104,7 @@ def get_batch_timestamps(batch_files, prev_batch_files=None):
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last_timestamp = format_timestamp(last_time)
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timestamp_range = f"{first_timestamp}-{last_timestamp}"
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logger.debug(f"解析时间戳: {first_frame} -> {first_timestamp}, {last_frame} -> {last_timestamp}")
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# logger.debug(f"解析时间戳: {first_frame} -> {first_timestamp}, {last_frame} -> {last_timestamp}")
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return first_timestamp, last_timestamp, timestamp_range
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def get_batch_files(keyframe_files, result, batch_size=5):
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@ -410,7 +401,7 @@ def generate_script(tr, params):
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skip_seconds=0
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)
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# 获取所有关键帧文件路径
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# 获取所有关键文件路径
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for filename in sorted(os.listdir(video_keyframes_dir)):
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if filename.endswith('.jpg'):
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keyframe_files.append(os.path.join(video_keyframes_dir, filename))
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@ -446,7 +437,7 @@ def generate_script(tr, params):
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vision_base_url = st.session_state.get('vision_gemini_base_url')
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if not vision_api_key or not vision_model:
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raise ValueError("未配置 Gemini API Key 或者 模型，请在基础设置中配置")
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raise ValueError("未配置 Gemini API Key 或者 型，请在基础设置配置")
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analyzer = vision_analyzer.VisionAnalyzer(
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model_name=vision_model,
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@ -484,7 +475,7 @@ def generate_script(tr, params):
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# 获取当前批次的文件列表 keyframe_001136_000045.jpg 将 000045 精度提升到 毫秒
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batch_files = get_batch_files(keyframe_files, result, vision_batch_size)
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logger.debug(f"批次 {result['batch_index']} 处理完成，共 {len(batch_files)} 张图片")
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logger.debug(batch_files)
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# logger.debug(batch_files)
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first_timestamp, last_timestamp, _ = get_batch_timestamps(batch_files, prev_batch_files)
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logger.debug(f"处理时间戳: {first_timestamp}-{last_timestamp}")
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@ -767,7 +758,7 @@ def crop_video(tr, params):
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utils.cut_video(params, update_progress)
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time.sleep(0.5)
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progress_bar.progress(100)
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status_text.text("剪辑完成！")
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status_text.text("剪完成！")
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st.success("视频剪辑成功完成！")
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except Exception as e:
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st.error(f"剪辑过程中发生错误: {str(e)}")
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