""" FFmpeg 工具模块 - 提供 FFmpeg 相关的工具函数,特别是硬件加速检测 """ import os import platform import subprocess from typing import Dict, List, Optional, Tuple, Union from loguru import logger # 全局变量,存储检测到的硬件加速信息 _FFMPEG_HW_ACCEL_INFO = { "available": False, "type": None, "encoder": None, "hwaccel_args": [], "message": "", "is_dedicated_gpu": False } def check_ffmpeg_installation() -> bool: """ 检查ffmpeg是否已安装 Returns: bool: 如果安装则返回True,否则返回False """ try: # 在Windows系统上使用UTF-8编码 is_windows = os.name == 'nt' if is_windows: subprocess.run(['ffmpeg', '-version'], stdout=subprocess.PIPE, stderr=subprocess.PIPE, encoding='utf-8', check=True) else: subprocess.run(['ffmpeg', '-version'], stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=True) return True except (subprocess.SubprocessError, FileNotFoundError): logger.error("ffmpeg未安装或不在系统PATH中,请安装ffmpeg") return False def detect_hardware_acceleration() -> Dict[str, Union[bool, str, List[str], None]]: """ 检测系统可用的硬件加速器,并存储结果到全局变量 Returns: Dict: 包含硬件加速信息的字典 """ global _FFMPEG_HW_ACCEL_INFO # 如果已经检测过,直接返回结果 if _FFMPEG_HW_ACCEL_INFO["type"] is not None: return _FFMPEG_HW_ACCEL_INFO # 检查ffmpeg是否已安装 if not check_ffmpeg_installation(): _FFMPEG_HW_ACCEL_INFO["message"] = "FFmpeg未安装或不在系统PATH中" return _FFMPEG_HW_ACCEL_INFO # 检测操作系统 system = platform.system().lower() logger.debug(f"检测硬件加速 - 操作系统: {system}") # 获取FFmpeg支持的硬件加速器列表 try: # 在Windows系统上使用UTF-8编码 is_windows = os.name == 'nt' if is_windows: hwaccels_cmd = subprocess.run( ['ffmpeg', '-hide_banner', '-hwaccels'], stdout=subprocess.PIPE, stderr=subprocess.PIPE, encoding='utf-8', text=True ) else: hwaccels_cmd = subprocess.run( ['ffmpeg', '-hide_banner', '-hwaccels'], stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True ) supported_hwaccels = hwaccels_cmd.stdout.lower() except Exception as e: logger.error(f"获取FFmpeg硬件加速器列表失败: {str(e)}") supported_hwaccels = "" # 根据操作系统检测不同的硬件加速器 if system == 'darwin': # macOS _detect_macos_acceleration(supported_hwaccels) elif system == 'windows': # Windows _detect_windows_acceleration(supported_hwaccels) elif system == 'linux': # Linux _detect_linux_acceleration(supported_hwaccels) else: logger.warning(f"不支持的操作系统: {system}") _FFMPEG_HW_ACCEL_INFO["message"] = f"不支持的操作系统: {system}" # 记录检测结果已经在启动时输出,这里不再重复输出 return _FFMPEG_HW_ACCEL_INFO def _detect_macos_acceleration(supported_hwaccels: str) -> None: """ 检测macOS系统的硬件加速 Args: supported_hwaccels: FFmpeg支持的硬件加速器列表 """ global _FFMPEG_HW_ACCEL_INFO if 'videotoolbox' in supported_hwaccels: # 测试videotoolbox try: test_cmd = subprocess.run( ["ffmpeg", "-hwaccel", "videotoolbox", "-i", "/dev/null", "-f", "null", "-"], stderr=subprocess.PIPE, stdout=subprocess.PIPE, text=True, check=False ) if test_cmd.returncode == 0: _FFMPEG_HW_ACCEL_INFO["available"] = True _FFMPEG_HW_ACCEL_INFO["type"] = "videotoolbox" _FFMPEG_HW_ACCEL_INFO["encoder"] = "h264_videotoolbox" _FFMPEG_HW_ACCEL_INFO["hwaccel_args"] = ["-hwaccel", "videotoolbox"] # macOS的Metal GPU加速通常是集成GPU _FFMPEG_HW_ACCEL_INFO["is_dedicated_gpu"] = False return except Exception as e: logger.debug(f"测试videotoolbox失败: {str(e)}") _FFMPEG_HW_ACCEL_INFO["message"] = "macOS系统未检测到可用的videotoolbox硬件加速" def _detect_windows_acceleration(supported_hwaccels: str) -> None: """ 检测Windows系统的硬件加速 Args: supported_hwaccels: FFmpeg支持的硬件加速器列表 """ global _FFMPEG_HW_ACCEL_INFO # 在Windows上,首先检查显卡信息 gpu_info = _get_windows_gpu_info() # 检查是否为AMD显卡 if 'amd' in gpu_info.lower() or 'radeon' in gpu_info.lower(): logger.info("检测到AMD显卡,为避免兼容性问题,将使用软件编码") _FFMPEG_HW_ACCEL_INFO["message"] = "检测到AMD显卡,为避免兼容性问题,将使用软件编码" return # 检查是否为Intel集成显卡 is_intel_integrated = False if 'intel' in gpu_info.lower() and ('hd graphics' in gpu_info.lower() or 'uhd graphics' in gpu_info.lower()): logger.info("检测到Intel集成显卡") is_intel_integrated = True # 检测NVIDIA CUDA支持 if 'cuda' in supported_hwaccels and 'nvidia' in gpu_info.lower(): # 添加调试日志 logger.debug(f"Windows检测到NVIDIA显卡,尝试CUDA加速") try: # 先检查NVENC编码器是否可用,使用UTF-8编码 encoders_cmd = subprocess.run( ["ffmpeg", "-hide_banner", "-encoders"], stderr=subprocess.PIPE, stdout=subprocess.PIPE, encoding='utf-8', text=True, check=False ) has_nvenc = "h264_nvenc" in encoders_cmd.stdout.lower() logger.debug(f"NVENC编码器检测结果: {'可用' if has_nvenc else '不可用'}") # 测试CUDA硬件加速,使用UTF-8编码 test_cmd = subprocess.run( ["ffmpeg", "-hwaccel", "cuda", "-i", "NUL", "-f", "null", "-t", "0.1", "-"], stderr=subprocess.PIPE, stdout=subprocess.PIPE, encoding='utf-8', text=True, check=False ) # 记录详细的返回信息以便调试 logger.debug(f"CUDA测试返回码: {test_cmd.returncode}") logger.debug(f"CUDA测试错误输出: {test_cmd.stderr[:200]}..." if len(test_cmd.stderr) > 200 else f"CUDA测试错误输出: {test_cmd.stderr}") if test_cmd.returncode == 0 or has_nvenc: _FFMPEG_HW_ACCEL_INFO["available"] = True _FFMPEG_HW_ACCEL_INFO["type"] = "cuda" _FFMPEG_HW_ACCEL_INFO["encoder"] = "h264_nvenc" _FFMPEG_HW_ACCEL_INFO["hwaccel_args"] = ["-hwaccel", "cuda"] _FFMPEG_HW_ACCEL_INFO["is_dedicated_gpu"] = True return # 如果上面的测试失败,尝试另一种方式,使用UTF-8编码 test_cmd2 = subprocess.run( ["ffmpeg", "-hide_banner", "-loglevel", "error", "-hwaccel", "cuda", "-hwaccel_output_format", "cuda", "-i", "NUL", "-f", "null", "-t", "0.1", "-"], stderr=subprocess.PIPE, stdout=subprocess.PIPE, encoding='utf-8', text=True, check=False ) if test_cmd2.returncode == 0: _FFMPEG_HW_ACCEL_INFO["available"] = True _FFMPEG_HW_ACCEL_INFO["type"] = "cuda" _FFMPEG_HW_ACCEL_INFO["encoder"] = "h264_nvenc" _FFMPEG_HW_ACCEL_INFO["hwaccel_args"] = ["-hwaccel", "cuda", "-hwaccel_output_format", "cuda"] _FFMPEG_HW_ACCEL_INFO["is_dedicated_gpu"] = True return except Exception as e: logger.debug(f"测试CUDA失败: {str(e)}") # 检测Intel QSV支持(如果是Intel显卡) if 'qsv' in supported_hwaccels and 'intel' in gpu_info.lower(): try: test_cmd = subprocess.run( ["ffmpeg", "-hwaccel", "qsv", "-i", "/dev/null", "-f", "null", "-"], stderr=subprocess.PIPE, stdout=subprocess.PIPE, text=True, check=False ) if test_cmd.returncode == 0: _FFMPEG_HW_ACCEL_INFO["available"] = True _FFMPEG_HW_ACCEL_INFO["type"] = "qsv" _FFMPEG_HW_ACCEL_INFO["encoder"] = "h264_qsv" _FFMPEG_HW_ACCEL_INFO["hwaccel_args"] = ["-hwaccel", "qsv"] _FFMPEG_HW_ACCEL_INFO["is_dedicated_gpu"] = not is_intel_integrated return except Exception as e: logger.debug(f"测试QSV失败: {str(e)}") # 检测D3D11VA支持 if 'd3d11va' in supported_hwaccels: logger.debug("Windows尝试D3D11VA加速") try: test_cmd = subprocess.run( ["ffmpeg", "-hwaccel", "d3d11va", "-i", "NUL", "-f", "null", "-t", "0.1", "-"], stderr=subprocess.PIPE, stdout=subprocess.PIPE, encoding='utf-8', text=True, check=False ) # 记录详细的返回信息以便调试 logger.debug(f"D3D11VA测试返回码: {test_cmd.returncode}") if test_cmd.returncode == 0: _FFMPEG_HW_ACCEL_INFO["available"] = True _FFMPEG_HW_ACCEL_INFO["type"] = "d3d11va" _FFMPEG_HW_ACCEL_INFO["encoder"] = "h264" # D3D11VA只用于解码,编码仍使用软件编码器 _FFMPEG_HW_ACCEL_INFO["hwaccel_args"] = ["-hwaccel", "d3d11va"] _FFMPEG_HW_ACCEL_INFO["is_dedicated_gpu"] = not is_intel_integrated return except Exception as e: logger.debug(f"测试D3D11VA失败: {str(e)}") # 检测DXVA2支持 if 'dxva2' in supported_hwaccels: logger.debug("Windows尝试DXVA2加速") try: test_cmd = subprocess.run( ["ffmpeg", "-hwaccel", "dxva2", "-i", "NUL", "-f", "null", "-t", "0.1", "-"], stderr=subprocess.PIPE, stdout=subprocess.PIPE, encoding='utf-8', text=True, check=False ) # 记录详细的返回信息以便调试 logger.debug(f"DXVA2测试返回码: {test_cmd.returncode}") if test_cmd.returncode == 0: _FFMPEG_HW_ACCEL_INFO["available"] = True _FFMPEG_HW_ACCEL_INFO["type"] = "dxva2" _FFMPEG_HW_ACCEL_INFO["encoder"] = "h264" # DXVA2只用于解码,编码仍使用软件编码器 _FFMPEG_HW_ACCEL_INFO["hwaccel_args"] = ["-hwaccel", "dxva2"] _FFMPEG_HW_ACCEL_INFO["is_dedicated_gpu"] = not is_intel_integrated return except Exception as e: logger.debug(f"测试DXVA2失败: {str(e)}") # 如果检测到NVIDIA显卡但前面的测试都失败,尝试直接使用NVENC编码器 if 'nvidia' in gpu_info.lower(): logger.debug("Windows检测到NVIDIA显卡,尝试直接使用NVENC编码器") try: # 检查NVENC编码器是否可用,使用UTF-8编码 encoders_cmd = subprocess.run( ["ffmpeg", "-hide_banner", "-encoders"], stderr=subprocess.PIPE, stdout=subprocess.PIPE, encoding='utf-8', text=True, check=False ) if "h264_nvenc" in encoders_cmd.stdout.lower(): logger.debug("NVENC编码器可用,尝试直接使用") # 测试NVENC编码器,使用UTF-8编码 test_cmd = subprocess.run( ["ffmpeg", "-f", "lavfi", "-i", "color=c=black:s=640x360:r=30", "-c:v", "h264_nvenc", "-t", "0.1", "-f", "null", "-"], stderr=subprocess.PIPE, stdout=subprocess.PIPE, encoding='utf-8', text=True, check=False ) logger.debug(f"NVENC编码器测试返回码: {test_cmd.returncode}") if test_cmd.returncode == 0: _FFMPEG_HW_ACCEL_INFO["available"] = True _FFMPEG_HW_ACCEL_INFO["type"] = "nvenc" _FFMPEG_HW_ACCEL_INFO["encoder"] = "h264_nvenc" _FFMPEG_HW_ACCEL_INFO["hwaccel_args"] = [] # 不使用hwaccel参数,直接使用编码器 _FFMPEG_HW_ACCEL_INFO["is_dedicated_gpu"] = True return except Exception as e: logger.debug(f"测试NVENC编码器失败: {str(e)}") _FFMPEG_HW_ACCEL_INFO["message"] = f"Windows系统未检测到可用的硬件加速,显卡信息: {gpu_info}" def _detect_linux_acceleration(supported_hwaccels: str) -> None: """ 检测Linux系统的硬件加速 Args: supported_hwaccels: FFmpeg支持的硬件加速器列表 """ global _FFMPEG_HW_ACCEL_INFO # 获取Linux显卡信息 gpu_info = _get_linux_gpu_info() is_nvidia = 'nvidia' in gpu_info.lower() is_intel = 'intel' in gpu_info.lower() is_amd = 'amd' in gpu_info.lower() or 'radeon' in gpu_info.lower() # 检测NVIDIA CUDA支持 if 'cuda' in supported_hwaccels and is_nvidia: try: test_cmd = subprocess.run( ["ffmpeg", "-hwaccel", "cuda", "-i", "/dev/null", "-f", "null", "-"], stderr=subprocess.PIPE, stdout=subprocess.PIPE, text=True, check=False ) if test_cmd.returncode == 0: _FFMPEG_HW_ACCEL_INFO["available"] = True _FFMPEG_HW_ACCEL_INFO["type"] = "cuda" _FFMPEG_HW_ACCEL_INFO["encoder"] = "h264_nvenc" _FFMPEG_HW_ACCEL_INFO["hwaccel_args"] = ["-hwaccel", "cuda"] _FFMPEG_HW_ACCEL_INFO["is_dedicated_gpu"] = True return except Exception as e: logger.debug(f"测试CUDA失败: {str(e)}") # 检测VAAPI支持 if 'vaapi' in supported_hwaccels: # 检查是否存在渲染设备 render_devices = ['/dev/dri/renderD128', '/dev/dri/renderD129'] render_device = None for device in render_devices: if os.path.exists(device): render_device = device break if render_device: try: test_cmd = subprocess.run( ["ffmpeg", "-hwaccel", "vaapi", "-vaapi_device", render_device, "-i", "/dev/null", "-f", "null", "-"], stderr=subprocess.PIPE, stdout=subprocess.PIPE, text=True, check=False ) if test_cmd.returncode == 0: _FFMPEG_HW_ACCEL_INFO["available"] = True _FFMPEG_HW_ACCEL_INFO["type"] = "vaapi" _FFMPEG_HW_ACCEL_INFO["encoder"] = "h264_vaapi" _FFMPEG_HW_ACCEL_INFO["hwaccel_args"] = ["-hwaccel", "vaapi", "-vaapi_device", render_device] # 根据显卡类型判断是否为独立显卡 _FFMPEG_HW_ACCEL_INFO["is_dedicated_gpu"] = is_nvidia or (is_amd and not is_intel) return except Exception as e: logger.debug(f"测试VAAPI失败: {str(e)}") # 检测Intel QSV支持 if 'qsv' in supported_hwaccels and is_intel: try: test_cmd = subprocess.run( ["ffmpeg", "-hwaccel", "qsv", "-i", "/dev/null", "-f", "null", "-"], stderr=subprocess.PIPE, stdout=subprocess.PIPE, text=True, check=False ) if test_cmd.returncode == 0: _FFMPEG_HW_ACCEL_INFO["available"] = True _FFMPEG_HW_ACCEL_INFO["type"] = "qsv" _FFMPEG_HW_ACCEL_INFO["encoder"] = "h264_qsv" _FFMPEG_HW_ACCEL_INFO["hwaccel_args"] = ["-hwaccel", "qsv"] _FFMPEG_HW_ACCEL_INFO["is_dedicated_gpu"] = False # Intel QSV通常是集成GPU return except Exception as e: logger.debug(f"测试QSV失败: {str(e)}") _FFMPEG_HW_ACCEL_INFO["message"] = f"Linux系统未检测到可用的硬件加速,显卡信息: {gpu_info}" def _get_windows_gpu_info() -> str: """ 获取Windows系统的显卡信息 Returns: str: 显卡信息字符串 """ try: # 使用PowerShell获取更可靠的显卡信息,并使用UTF-8编码 gpu_info = subprocess.run( ['powershell', '-Command', "Get-WmiObject Win32_VideoController | Select-Object Name | Format-List"], stdout=subprocess.PIPE, stderr=subprocess.PIPE, encoding='utf-8', text=True, check=False ) # 如果PowerShell失败,尝试使用wmic if not gpu_info.stdout.strip(): gpu_info = subprocess.run( ['wmic', 'path', 'win32_VideoController', 'get', 'name'], stdout=subprocess.PIPE, stderr=subprocess.PIPE, encoding='utf-8', text=True, check=False ) # 记录详细的显卡信息以便调试 logger.debug(f"Windows显卡信息: {gpu_info.stdout}") return gpu_info.stdout except Exception as e: logger.warning(f"获取Windows显卡信息失败: {str(e)}") return "Unknown GPU" def _get_linux_gpu_info() -> str: """ 获取Linux系统的显卡信息 Returns: str: 显卡信息字符串 """ try: # 尝试使用lspci命令 gpu_info = subprocess.run( ['lspci', '-v', '-nn', '|', 'grep', '-i', 'vga\\|display'], stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True, shell=True, check=False ) if gpu_info.stdout: return gpu_info.stdout # 如果lspci命令失败,尝试使用glxinfo gpu_info = subprocess.run( ['glxinfo', '|', 'grep', '-i', 'vendor\\|renderer'], stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True, shell=True, check=False ) if gpu_info.stdout: return gpu_info.stdout return "Unknown GPU" except Exception as e: logger.warning(f"获取Linux显卡信息失败: {str(e)}") return "Unknown GPU" def get_ffmpeg_hwaccel_args() -> List[str]: """ 获取FFmpeg硬件加速参数 Returns: List[str]: FFmpeg硬件加速参数列表 """ # 如果还没有检测过,先进行检测 if _FFMPEG_HW_ACCEL_INFO["type"] is None: detect_hardware_acceleration() return _FFMPEG_HW_ACCEL_INFO["hwaccel_args"] def get_ffmpeg_hwaccel_type() -> Optional[str]: """ 获取FFmpeg硬件加速类型 Returns: Optional[str]: 硬件加速类型,如果不支持则返回None """ # 如果还没有检测过,先进行检测 if _FFMPEG_HW_ACCEL_INFO["type"] is None: detect_hardware_acceleration() return _FFMPEG_HW_ACCEL_INFO["type"] if _FFMPEG_HW_ACCEL_INFO["available"] else None def get_ffmpeg_hwaccel_encoder() -> Optional[str]: """ 获取FFmpeg硬件加速编码器 Returns: Optional[str]: 硬件加速编码器,如果不支持则返回None """ # 如果还没有检测过,先进行检测 if _FFMPEG_HW_ACCEL_INFO["type"] is None: detect_hardware_acceleration() return _FFMPEG_HW_ACCEL_INFO["encoder"] if _FFMPEG_HW_ACCEL_INFO["available"] else None def get_ffmpeg_hwaccel_info() -> Dict[str, Union[bool, str, List[str], None]]: """ 获取FFmpeg硬件加速信息 Returns: Dict: 包含硬件加速信息的字典 """ # 如果还没有检测过,先进行检测 if _FFMPEG_HW_ACCEL_INFO["type"] is None: detect_hardware_acceleration() return _FFMPEG_HW_ACCEL_INFO def is_ffmpeg_hwaccel_available() -> bool: """ 检查是否有可用的FFmpeg硬件加速 Returns: bool: 如果有可用的硬件加速则返回True,否则返回False """ # 如果还没有检测过,先进行检测 if _FFMPEG_HW_ACCEL_INFO["type"] is None: detect_hardware_acceleration() return _FFMPEG_HW_ACCEL_INFO["available"] def is_dedicated_gpu() -> bool: """ 检查是否使用独立显卡进行硬件加速 Returns: bool: 如果使用独立显卡则返回True,否则返回False """ # 如果还没有检测过,先进行检测 if _FFMPEG_HW_ACCEL_INFO["type"] is None: detect_hardware_acceleration() return _FFMPEG_HW_ACCEL_INFO["is_dedicated_gpu"]