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https://github.com/linyqh/NarratoAI.git
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6d8cc671ab
在clip_video.py和merger_video.py中，注释掉了成功处理视频的日志信息，以减少调试时的冗余输出。同时，在manager.py中更新了提示词渲染成功的日志格式，确保版本信息的清晰展示。这些更改旨在提升日志的可读性和有效性，优化调试过程。
713 lines
25 KiB
Python
713 lines
25 KiB
Python
#!/usr/bin/env python
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# -*- coding: UTF-8 -*-
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'''
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@Project: NarratoAI
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@File : clip_video
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@Author : Viccy同学
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@Date : 2025/5/6 下午6:14
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'''
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import os
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import subprocess
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import json
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import hashlib
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from loguru import logger
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from typing import Dict, List, Optional
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from pathlib import Path
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from app.utils import ffmpeg_utils
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def parse_timestamp(timestamp: str) -> tuple:
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"""
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解析时间戳字符串，返回开始和结束时间
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Args:
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timestamp: 格式为'HH:MM:SS-HH:MM:SS'或'HH:MM:SS,sss-HH:MM:SS,sss'的时间戳字符串
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Returns:
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tuple: (开始时间, 结束时间) 格式为'HH:MM:SS'或'HH:MM:SS,sss'
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"""
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start_time, end_time = timestamp.split('-')
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return start_time, end_time
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def calculate_end_time(start_time: str, duration: float, extra_seconds: float = 1.0) -> str:
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"""
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根据开始时间和持续时间计算结束时间
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Args:
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start_time: 开始时间，格式为'HH:MM:SS'或'HH:MM:SS,sss'(带毫秒)
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duration: 持续时间，单位为秒
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extra_seconds: 额外添加的秒数，默认为1秒
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Returns:
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str: 计算后的结束时间，格式与输入格式相同
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"""
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# 检查是否包含毫秒
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has_milliseconds = ',' in start_time
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milliseconds = 0
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if has_milliseconds:
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time_part, ms_part = start_time.split(',')
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h, m, s = map(int, time_part.split(':'))
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milliseconds = int(ms_part)
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else:
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h, m, s = map(int, start_time.split(':'))
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# 转换为总毫秒数
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total_milliseconds = ((h * 3600 + m * 60 + s) * 1000 + milliseconds +
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int((duration + extra_seconds) * 1000))
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# 计算新的时、分、秒、毫秒
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ms_new = total_milliseconds % 1000
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total_seconds = total_milliseconds // 1000
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h_new = int(total_seconds // 3600)
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m_new = int((total_seconds % 3600) // 60)
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s_new = int(total_seconds % 60)
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# 返回与输入格式一致的时间字符串
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if has_milliseconds:
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return f"{h_new:02d}:{m_new:02d}:{s_new:02d},{ms_new:03d}"
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else:
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return f"{h_new:02d}:{m_new:02d}:{s_new:02d}"
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def check_hardware_acceleration() -> Optional[str]:
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"""
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检查系统支持的硬件加速选项
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Returns:
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Optional[str]: 硬件加速参数，如果不支持则返回None
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"""
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# 使用集中式硬件加速检测
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return ffmpeg_utils.get_ffmpeg_hwaccel_type()
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def get_safe_encoder_config(hwaccel_type: Optional[str] = None) -> Dict[str, str]:
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"""
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获取安全的编码器配置，基于ffmpeg_demo.py成功方案优化
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Args:
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hwaccel_type: 硬件加速类型
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Returns:
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Dict[str, str]: 编码器配置字典
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"""
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# 基础配置 - 参考ffmpeg_demo.py的成功方案
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config = {
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"video_codec": "libx264",
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"audio_codec": "aac",
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"pixel_format": "yuv420p",
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"preset": "medium",
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"quality_param": "crf", # 质量参数类型
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"quality_value": "23" # 质量值
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}
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# 根据硬件加速类型调整配置（简化版本）
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if hwaccel_type in ["nvenc_pure", "nvenc_software", "cuda_careful", "nvenc", "cuda", "cuda_decode"]:
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# NVIDIA硬件加速 - 使用ffmpeg_demo.py中验证有效的参数
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config["video_codec"] = "h264_nvenc"
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config["preset"] = "medium"
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config["quality_param"] = "cq" # CQ质量控制，而不是CRF
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config["quality_value"] = "23"
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config["pixel_format"] = "yuv420p"
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elif hwaccel_type == "amf":
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# AMD AMF编码器
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config["video_codec"] = "h264_amf"
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config["preset"] = "balanced"
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config["quality_param"] = "qp_i"
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config["quality_value"] = "23"
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elif hwaccel_type == "qsv":
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# Intel QSV编码器
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config["video_codec"] = "h264_qsv"
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config["preset"] = "medium"
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config["quality_param"] = "global_quality"
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config["quality_value"] = "23"
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elif hwaccel_type == "videotoolbox":
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# macOS VideoToolbox编码器
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config["video_codec"] = "h264_videotoolbox"
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config["preset"] = "medium"
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config["quality_param"] = "b:v"
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config["quality_value"] = "5M"
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else:
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# 软件编码（默认）
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config["video_codec"] = "libx264"
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config["preset"] = "medium"
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config["quality_param"] = "crf"
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config["quality_value"] = "23"
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return config
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def build_ffmpeg_command(
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input_path: str,
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output_path: str,
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start_time: str,
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end_time: str,
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encoder_config: Dict[str, str],
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hwaccel_args: List[str] = None
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) -> List[str]:
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"""
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构建优化的ffmpeg命令，基于测试结果使用正确的硬件加速方案
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重要发现：对于视频裁剪场景，CUDA硬件解码会导致滤镜链错误，
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应该使用纯NVENC编码器（无硬件解码）来获得最佳兼容性
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Args:
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input_path: 输入视频路径
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output_path: 输出视频路径
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start_time: 开始时间
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end_time: 结束时间
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encoder_config: 编码器配置
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hwaccel_args: 硬件加速参数
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Returns:
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List[str]: ffmpeg命令列表
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"""
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cmd = ["ffmpeg", "-y"]
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# 关键修正：对于视频裁剪，不使用CUDA硬件解码，只使用NVENC编码器
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# 这样能避免滤镜链格式转换错误，同时保持编码性能优势
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if encoder_config["video_codec"] == "h264_nvenc":
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# 不添加硬件解码参数，让FFmpeg自动处理
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# 这避免了 "Impossible to convert between the formats" 错误
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pass
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elif hwaccel_args:
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# 对于其他编码器，可以使用硬件解码参数
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cmd.extend(hwaccel_args)
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# 输入文件
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cmd.extend(["-i", input_path])
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# 时间范围
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cmd.extend(["-ss", start_time, "-to", end_time])
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# 编码器设置
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cmd.extend(["-c:v", encoder_config["video_codec"]])
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cmd.extend(["-c:a", encoder_config["audio_codec"]])
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# 像素格式
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cmd.extend(["-pix_fmt", encoder_config["pixel_format"]])
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# 质量和预设参数 - 针对NVENC优化
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if encoder_config["video_codec"] == "h264_nvenc":
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# 纯NVENC编码器配置（无硬件解码，兼容性最佳）
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cmd.extend(["-preset", encoder_config["preset"]])
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cmd.extend(["-cq", encoder_config["quality_value"]])
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cmd.extend(["-profile:v", "main"]) # 提高兼容性
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logger.debug("使用纯NVENC编码器（无硬件解码，避免滤镜链问题）")
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elif encoder_config["video_codec"] == "h264_amf":
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# AMD AMF编码器
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cmd.extend(["-quality", encoder_config["preset"]])
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cmd.extend(["-qp_i", encoder_config["quality_value"]])
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elif encoder_config["video_codec"] == "h264_qsv":
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# Intel QSV编码器
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cmd.extend(["-preset", encoder_config["preset"]])
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cmd.extend(["-global_quality", encoder_config["quality_value"]])
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elif encoder_config["video_codec"] == "h264_videotoolbox":
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# macOS VideoToolbox编码器
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cmd.extend(["-profile:v", "high"])
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cmd.extend(["-b:v", encoder_config["quality_value"]])
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else:
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# 软件编码器（libx264）
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cmd.extend(["-preset", encoder_config["preset"]])
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cmd.extend(["-crf", encoder_config["quality_value"]])
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# 音频设置
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cmd.extend(["-ar", "44100", "-ac", "2"])
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# 优化参数
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cmd.extend(["-avoid_negative_ts", "make_zero"])
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cmd.extend(["-movflags", "+faststart"])
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# 输出文件
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cmd.append(output_path)
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return cmd
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def execute_ffmpeg_with_fallback(
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cmd: List[str],
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timestamp: str,
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input_path: str,
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output_path: str,
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start_time: str,
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end_time: str
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) -> bool:
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"""
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执行ffmpeg命令，带有智能fallback机制
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Args:
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cmd: 主要的ffmpeg命令
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timestamp: 时间戳（用于日志）
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input_path: 输入路径
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output_path: 输出路径
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start_time: 开始时间
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end_time: 结束时间
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Returns:
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bool: 是否成功
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"""
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try:
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# logger.debug(f"执行ffmpeg命令: {' '.join(cmd)}")
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# 在Windows系统上使用UTF-8编码处理输出
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is_windows = os.name == 'nt'
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process_kwargs = {
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"stdout": subprocess.PIPE,
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"stderr": subprocess.PIPE,
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"text": True,
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"check": True
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}
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if is_windows:
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process_kwargs["encoding"] = 'utf-8'
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result = subprocess.run(cmd, **process_kwargs)
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# 验证输出文件
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if os.path.exists(output_path) and os.path.getsize(output_path) > 0:
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# logger.info(f"✓ 视频裁剪成功: {timestamp}")
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return True
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else:
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logger.warning(f"输出文件无效: {output_path}")
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return False
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except subprocess.CalledProcessError as e:
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error_msg = e.stderr if e.stderr else str(e)
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logger.warning(f"主要命令失败: {error_msg}")
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# 智能错误分析
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error_type = analyze_ffmpeg_error(error_msg)
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logger.debug(f"错误类型分析: {error_type}")
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# 根据错误类型选择fallback策略
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if error_type == "filter_chain_error":
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logger.info(f"检测到滤镜链错误，尝试兼容性模式: {timestamp}")
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return try_compatibility_fallback(input_path, output_path, start_time, end_time, timestamp)
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elif error_type == "hardware_error":
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logger.info(f"检测到硬件加速错误，尝试软件编码: {timestamp}")
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return try_software_fallback(input_path, output_path, start_time, end_time, timestamp)
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elif error_type == "encoder_error":
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logger.info(f"检测到编码器错误，尝试基本编码: {timestamp}")
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return try_basic_fallback(input_path, output_path, start_time, end_time, timestamp)
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else:
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logger.info(f"尝试通用fallback方案: {timestamp}")
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return try_fallback_encoding(input_path, output_path, start_time, end_time, timestamp)
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except Exception as e:
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logger.error(f"执行ffmpeg命令时发生异常: {str(e)}")
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return False
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def analyze_ffmpeg_error(error_msg: str) -> str:
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"""
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分析ffmpeg错误信息，返回错误类型
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Args:
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error_msg: 错误信息
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Returns:
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str: 错误类型
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"""
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error_msg_lower = error_msg.lower()
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# 滤镜链错误
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if any(keyword in error_msg_lower for keyword in [
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"impossible to convert", "filter", "format", "scale", "auto_scale",
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"null", "parsed_null", "reinitializing filters"
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]):
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return "filter_chain_error"
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# 硬件加速错误
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if any(keyword in error_msg_lower for keyword in [
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"cuda", "nvenc", "amf", "qsv", "d3d11va", "dxva2", "videotoolbox",
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"hardware", "hwaccel", "gpu", "device"
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]):
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return "hardware_error"
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# 编码器错误
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if any(keyword in error_msg_lower for keyword in [
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"encoder", "codec", "h264", "libx264", "bitrate", "preset"
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]):
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return "encoder_error"
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# 文件访问错误
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if any(keyword in error_msg_lower for keyword in [
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"no such file", "permission denied", "access denied", "file not found"
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]):
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return "file_error"
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return "unknown_error"
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def try_compatibility_fallback(
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input_path: str,
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output_path: str,
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start_time: str,
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end_time: str,
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timestamp: str
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) -> bool:
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"""
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尝试兼容性fallback方案（解决滤镜链问题）
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Args:
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input_path: 输入路径
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output_path: 输出路径
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start_time: 开始时间
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end_time: 结束时间
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timestamp: 时间戳
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Returns:
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bool: 是否成功
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"""
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# 兼容性模式：避免所有可能的滤镜链问题
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fallback_cmd = [
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"ffmpeg", "-y", "-hide_banner", "-loglevel", "error",
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"-i", input_path,
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"-ss", start_time,
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"-to", end_time,
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"-c:v", "libx264",
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"-c:a", "aac",
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"-pix_fmt", "yuv420p", # 明确指定像素格式
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"-preset", "fast",
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"-crf", "23",
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"-ar", "44100", "-ac", "2", # 标准化音频
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"-avoid_negative_ts", "make_zero",
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"-movflags", "+faststart",
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"-max_muxing_queue_size", "1024", # 增加缓冲区大小
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output_path
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]
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return execute_simple_command(fallback_cmd, timestamp, "兼容性模式")
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def try_software_fallback(
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input_path: str,
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output_path: str,
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start_time: str,
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end_time: str,
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timestamp: str
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) -> bool:
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"""
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尝试软件编码fallback方案
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Args:
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input_path: 输入路径
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output_path: 输出路径
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start_time: 开始时间
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end_time: 结束时间
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timestamp: 时间戳
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Returns:
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bool: 是否成功
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"""
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# 纯软件编码
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fallback_cmd = [
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"ffmpeg", "-y", "-hide_banner", "-loglevel", "error",
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"-i", input_path,
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"-ss", start_time,
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"-to", end_time,
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"-c:v", "libx264",
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"-c:a", "aac",
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"-pix_fmt", "yuv420p",
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"-preset", "fast",
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"-crf", "23",
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"-ar", "44100", "-ac", "2",
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"-avoid_negative_ts", "make_zero",
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"-movflags", "+faststart",
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output_path
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]
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return execute_simple_command(fallback_cmd, timestamp, "软件编码")
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def try_basic_fallback(
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input_path: str,
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output_path: str,
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start_time: str,
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end_time: str,
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timestamp: str
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) -> bool:
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"""
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尝试基本编码fallback方案
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Args:
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input_path: 输入路径
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output_path: 输出路径
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start_time: 开始时间
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end_time: 结束时间
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timestamp: 时间戳
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Returns:
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bool: 是否成功
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"""
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# 最基本的编码参数
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fallback_cmd = [
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"ffmpeg", "-y", "-hide_banner", "-loglevel", "error",
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"-i", input_path,
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"-ss", start_time,
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"-to", end_time,
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"-c:v", "libx264",
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"-c:a", "aac",
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"-pix_fmt", "yuv420p",
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"-preset", "ultrafast", # 最快速度
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"-crf", "28", # 稍微降低质量
|
||
"-avoid_negative_ts", "make_zero",
|
||
output_path
|
||
]
|
||
|
||
return execute_simple_command(fallback_cmd, timestamp, "基本编码")
|
||
|
||
|
||
def execute_simple_command(cmd: List[str], timestamp: str, method_name: str) -> bool:
|
||
"""
|
||
执行简单的ffmpeg命令
|
||
|
||
Args:
|
||
cmd: 命令列表
|
||
timestamp: 时间戳
|
||
method_name: 方法名称
|
||
|
||
Returns:
|
||
bool: 是否成功
|
||
"""
|
||
try:
|
||
logger.debug(f"执行{method_name}命令: {' '.join(cmd)}")
|
||
|
||
is_windows = os.name == 'nt'
|
||
process_kwargs = {
|
||
"stdout": subprocess.PIPE,
|
||
"stderr": subprocess.PIPE,
|
||
"text": True,
|
||
"check": True
|
||
}
|
||
|
||
if is_windows:
|
||
process_kwargs["encoding"] = 'utf-8'
|
||
|
||
subprocess.run(cmd, **process_kwargs)
|
||
|
||
output_path = cmd[-1] # 输出路径总是最后一个参数
|
||
if os.path.exists(output_path) and os.path.getsize(output_path) > 0:
|
||
logger.info(f"✓ {method_name}成功: {timestamp}")
|
||
return True
|
||
else:
|
||
logger.error(f"{method_name}失败，输出文件无效: {output_path}")
|
||
return False
|
||
|
||
except subprocess.CalledProcessError as e:
|
||
error_msg = e.stderr if e.stderr else str(e)
|
||
logger.error(f"{method_name}失败: {error_msg}")
|
||
return False
|
||
except Exception as e:
|
||
logger.error(f"{method_name}异常: {str(e)}")
|
||
return False
|
||
|
||
|
||
def try_fallback_encoding(
|
||
input_path: str,
|
||
output_path: str,
|
||
start_time: str,
|
||
end_time: str,
|
||
timestamp: str
|
||
) -> bool:
|
||
"""
|
||
尝试fallback编码方案（通用方案）
|
||
|
||
Args:
|
||
input_path: 输入路径
|
||
output_path: 输出路径
|
||
start_time: 开始时间
|
||
end_time: 结束时间
|
||
timestamp: 时间戳
|
||
|
||
Returns:
|
||
bool: 是否成功
|
||
"""
|
||
# 最简单的软件编码命令
|
||
fallback_cmd = [
|
||
"ffmpeg", "-y",
|
||
"-i", input_path,
|
||
"-ss", start_time,
|
||
"-to", end_time,
|
||
"-c:v", "libx264",
|
||
"-c:a", "aac",
|
||
"-pix_fmt", "yuv420p",
|
||
"-preset", "ultrafast", # 最快速度
|
||
"-crf", "28", # 稍微降低质量以提高兼容性
|
||
"-avoid_negative_ts", "make_zero",
|
||
"-movflags", "+faststart",
|
||
output_path
|
||
]
|
||
|
||
return execute_simple_command(fallback_cmd, timestamp, "通用Fallback")
|
||
|
||
|
||
def clip_video(
|
||
video_origin_path: str,
|
||
tts_result: List[Dict],
|
||
output_dir: Optional[str] = None,
|
||
task_id: Optional[str] = None
|
||
) -> Dict[str, str]:
|
||
"""
|
||
根据时间戳裁剪视频 - 优化版本，增强Windows兼容性和错误处理
|
||
|
||
Args:
|
||
video_origin_path: 原始视频的路径
|
||
tts_result: 包含时间戳和持续时间信息的列表
|
||
output_dir: 输出目录路径，默认为None时会自动生成
|
||
task_id: 任务ID，用于生成唯一的输出目录，默认为None时会自动生成
|
||
|
||
Returns:
|
||
Dict[str, str]: 时间戳到裁剪后视频路径的映射
|
||
"""
|
||
# 检查视频文件是否存在
|
||
if not os.path.exists(video_origin_path):
|
||
raise FileNotFoundError(f"视频文件不存在: {video_origin_path}")
|
||
|
||
# 如果未提供task_id，则根据输入生成一个唯一ID
|
||
if task_id is None:
|
||
content_for_hash = f"{video_origin_path}_{json.dumps(tts_result)}"
|
||
task_id = hashlib.md5(content_for_hash.encode()).hexdigest()
|
||
|
||
# 设置输出目录
|
||
if output_dir is None:
|
||
output_dir = os.path.join(
|
||
os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))),
|
||
"storage", "temp", "clip_video", task_id
|
||
)
|
||
|
||
# 确保输出目录存在
|
||
Path(output_dir).mkdir(parents=True, exist_ok=True)
|
||
|
||
# 获取硬件加速支持
|
||
hwaccel_type = check_hardware_acceleration()
|
||
hwaccel_args = []
|
||
|
||
if hwaccel_type:
|
||
hwaccel_args = ffmpeg_utils.get_ffmpeg_hwaccel_args()
|
||
hwaccel_info = ffmpeg_utils.get_ffmpeg_hwaccel_info()
|
||
logger.info(f"🚀 使用硬件加速: {hwaccel_type} ({hwaccel_info.get('message', '')})")
|
||
else:
|
||
logger.info("🔧 使用软件编码")
|
||
|
||
# 获取编码器配置
|
||
encoder_config = get_safe_encoder_config(hwaccel_type)
|
||
logger.debug(f"编码器配置: {encoder_config}")
|
||
|
||
# 统计信息
|
||
total_clips = len(tts_result)
|
||
result = {}
|
||
failed_clips = []
|
||
success_count = 0
|
||
|
||
logger.info(f"📹 开始裁剪视频，总共{total_clips}个片段")
|
||
|
||
for i, item in enumerate(tts_result, 1):
|
||
_id = item.get("_id", item.get("timestamp", "unknown"))
|
||
timestamp = item["timestamp"]
|
||
start_time, _ = parse_timestamp(timestamp)
|
||
|
||
# 根据持续时间计算真正的结束时间（加上1秒余量）
|
||
duration = item["duration"]
|
||
calculated_end_time = calculate_end_time(start_time, duration)
|
||
|
||
# 转换为FFmpeg兼容的时间格式（逗号替换为点）
|
||
ffmpeg_start_time = start_time.replace(',', '.')
|
||
ffmpeg_end_time = calculated_end_time.replace(',', '.')
|
||
|
||
# 格式化输出文件名（使用连字符替代冒号和逗号）
|
||
safe_start_time = start_time.replace(':', '-').replace(',', '-')
|
||
safe_end_time = calculated_end_time.replace(':', '-').replace(',', '-')
|
||
output_filename = f"vid_{safe_start_time}@{safe_end_time}.mp4"
|
||
output_path = os.path.join(output_dir, output_filename)
|
||
|
||
# 构建FFmpeg命令
|
||
ffmpeg_cmd = build_ffmpeg_command(
|
||
video_origin_path,
|
||
output_path,
|
||
ffmpeg_start_time,
|
||
ffmpeg_end_time,
|
||
encoder_config,
|
||
hwaccel_args
|
||
)
|
||
|
||
# 执行FFmpeg命令
|
||
logger.info(f"📹 [{i}/{total_clips}] 裁剪视频片段: {timestamp} -> {ffmpeg_start_time}到{ffmpeg_end_time}")
|
||
|
||
success = execute_ffmpeg_with_fallback(
|
||
ffmpeg_cmd,
|
||
timestamp,
|
||
video_origin_path,
|
||
output_path,
|
||
ffmpeg_start_time,
|
||
ffmpeg_end_time
|
||
)
|
||
|
||
if success:
|
||
result[_id] = output_path
|
||
success_count += 1
|
||
logger.info(f"✅ [{i}/{total_clips}] 片段裁剪成功: {timestamp}")
|
||
else:
|
||
failed_clips.append(timestamp)
|
||
logger.error(f"❌ [{i}/{total_clips}] 片段裁剪失败: {timestamp}")
|
||
|
||
# 最终统计
|
||
logger.info(f"📊 视频裁剪完成: 成功 {success_count}/{total_clips}, 失败 {len(failed_clips)}")
|
||
|
||
# 检查是否有失败的片段
|
||
if failed_clips:
|
||
logger.warning(f"⚠️ 以下片段裁剪失败: {failed_clips}")
|
||
if len(failed_clips) == total_clips:
|
||
raise RuntimeError("所有视频片段裁剪都失败了，请检查视频文件和ffmpeg配置")
|
||
elif len(failed_clips) > total_clips / 2:
|
||
logger.warning(f"⚠️ 超过一半的片段裁剪失败 ({len(failed_clips)}/{total_clips})，请检查硬件加速配置")
|
||
|
||
if success_count > 0:
|
||
logger.info(f"🎉 视频裁剪任务完成! 输出目录: {output_dir}")
|
||
|
||
return result
|
||
|
||
|
||
if __name__ == "__main__":
|
||
video_origin_path = "/Users/apple/Desktop/home/NarratoAI/resource/videos/qyn2-2无片头片尾.mp4"
|
||
|
||
tts_result = [{'timestamp': '00:00:00-00:01:15',
|
||
'audio_file': '/Users/apple/Desktop/home/NarratoAI/storage/tasks/qyn2-2-demo/audio_00_00_00-00_01_15.mp3',
|
||
'subtitle_file': '/Users/apple/Desktop/home/NarratoAI/storage/tasks/qyn2-2-demo/subtitle_00_00_00-00_01_15.srt',
|
||
'duration': 25.55,
|
||
'text': '好的各位，欢迎回到我的频道！《庆余年 2》刚开播就给了我们一个王炸！范闲在北齐"死"了？这怎么可能！上集片尾那个巨大的悬念，这一集就立刻揭晓了！范闲假死归来，他面临的第一个，也是最大的难关，就是如何面对他最敬爱的，同时也是最可怕的那个人——庆帝！'},
|
||
{'timestamp': '00:01:15-00:04:40',
|
||
'audio_file': '/Users/apple/Desktop/home/NarratoAI/storage/tasks/qyn2-2-demo/audio_00_01_15-00_04_40.mp3',
|
||
'subtitle_file': '/Users/apple/Desktop/home/NarratoAI/storage/tasks/qyn2-2-demo/subtitle_00_01_15-00_04_40.srt',
|
||
'duration': 13.488,
|
||
'text': '但我们都知道，他绝不可能就这么轻易退场！第二集一开场，范闲就已经秘密回到了京都。他的生死传闻，可不像我们想象中那样只是小范围流传，而是…'},
|
||
{'timestamp': '00:04:58-00:05:45',
|
||
'audio_file': '/Users/apple/Desktop/home/NarratoAI/storage/tasks/qyn2-2-demo/audio_00_04_58-00_05_45.mp3',
|
||
'subtitle_file': '/Users/apple/Desktop/home/NarratoAI/storage/tasks/qyn2-2-demo/subtitle_00_04_58-00_05_45.srt',
|
||
'duration': 21.363,
|
||
'text': '"欺君之罪"！在封建王朝，这可是抄家灭族的大罪！搁一般人，肯定脚底抹油溜之大吉了。但范闲是谁啊？他偏要反其道而行之！他竟然决定，直接去见庆帝！冒着天大的风险，用"假死"这个事实去赌庆帝的态度！'},
|
||
{'timestamp': '00:05:45-00:06:00',
|
||
'audio_file': '/Users/apple/Desktop/home/NarratoAI/storage/tasks/qyn2-2-demo/audio_00_05_45-00_06_00.mp3',
|
||
'subtitle_file': '/Users/apple/Desktop/home/NarratoAI/storage/tasks/qyn2-2-demo/subtitle_00_05_45-00_06_00.srt',
|
||
'duration': 7.675, 'text': '但想见庆帝，哪有那么容易？范闲艺高人胆大，竟然选择了最激进的方式——闯宫！'}]
|
||
subclip_path_videos = {
|
||
'00:00:00-00:01:15': '/Users/apple/Desktop/home/NarratoAI/storage/temp/clip_video/6e7e343c7592c7d6f9a9636b55000f23/vid-00-00-00-00-01-15.mp4',
|
||
'00:01:15-00:04:40': '/Users/apple/Desktop/home/NarratoAI/storage/temp/clip_video/6e7e343c7592c7d6f9a9636b55000f23/vid-00-01-15-00-04-40.mp4',
|
||
'00:04:41-00:04:58': '/Users/apple/Desktop/home/NarratoAI/storage/temp/clip_video/6e7e343c7592c7d6f9a9636b55000f23/vid-00-04-41-00-04-58.mp4',
|
||
'00:04:58-00:05:45': '/Users/apple/Desktop/home/NarratoAI/storage/temp/clip_video/6e7e343c7592c7d6f9a9636b55000f23/vid-00-04-58-00-05-45.mp4',
|
||
'00:05:45-00:06:00': '/Users/apple/Desktop/home/NarratoAI/storage/temp/clip_video/6e7e343c7592c7d6f9a9636b55000f23/vid-00-05-45-00-06-00.mp4',
|
||
'00:06:00-00:06:03': '/Users/apple/Desktop/home/NarratoAI/storage/temp/clip_video/6e7e343c7592c7d6f9a9636b55000f23/vid-00-06-00-00-06-03.mp4',
|
||
}
|
||
|
||
# 使用方法示例
|
||
try:
|
||
result = clip_video(video_origin_path, tts_result, subclip_path_videos)
|
||
print("裁剪结果:")
|
||
print(json.dumps(result, indent=4, ensure_ascii=False))
|
||
except Exception as e:
|
||
print(f"发生错误: {e}")
|