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feat(video): 添加硬件加速支持

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- 定义硬件加速类型常量（none、qsv、cuda）
- 配置QSV和CUDA编码参数及预设
- 在WorkerConfig中添加硬件加速配置选项
- 实现基于硬件加速类型的编码参数动态获取
- 添加FFmpeg硬件加速解码和滤镜参数
- 检测并报告系统硬件加速支持信息
- 在API客户端中上报硬件加速配置和支持状态
This commit is contained in:
Jerry Yan
2026-01-13 13:34:27 +08:00
parent a26c44a3cd
commit 71bd2e59f9
7 changed files with 364 additions and 22 deletions
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31
constant/__init__.py
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@@ -41,7 +41,14 @@ EFFECT_TYPES = (
'blur', # 模糊效果（预留）
)
# 统一视频编码参数（来自集成文档）
# 硬件加速类型
HW_ACCEL_NONE = 'none' # 纯软件编解码
HW_ACCEL_QSV = 'qsv' # Intel Quick Sync Video (核显/独显)
HW_ACCEL_CUDA = 'cuda' # NVIDIA NVENC/NVDEC
HW_ACCEL_TYPES = (HW_ACCEL_NONE, HW_ACCEL_QSV, HW_ACCEL_CUDA)
# 统一视频编码参数（软件编码，来自集成文档）
VIDEO_ENCODE_PARAMS = {
'codec': 'libx264',
'preset': 'medium',
@@ -51,6 +58,28 @@ VIDEO_ENCODE_PARAMS = {
'pix_fmt': 'yuv420p',
}
# QSV 硬件加速视频编码参数（Intel Quick Sync）
VIDEO_ENCODE_PARAMS_QSV = {
'codec': 'h264_qsv',
'preset': 'medium', # QSV 支持: veryfast, faster, fast, medium, slow, slower, veryslow
'profile': 'main',
'level': '4.0',
'global_quality': '23', # QSV 使用 global_quality 代替 crf（1-51，值越低质量越高）
'look_ahead': '1', # 启用前瞻分析提升质量
'pix_fmt': 'nv12', # QSV 硬件表面格式
}
# CUDA 硬件加速视频编码参数（NVIDIA NVENC）
VIDEO_ENCODE_PARAMS_CUDA = {
'codec': 'h264_nvenc',
'preset': 'p4', # NVENC 预设 p1-p7（p1 最快，p7 最慢/质量最高），p4 ≈ medium
'profile': 'main',
'level': '4.0',
'rc': 'vbr', # 码率控制模式：vbr 可变码率
'cq': '23', # 恒定质量模式的质量值（0-51）
'pix_fmt': 'yuv420p', # NVENC 输入格式（会自动转换）
}
# 统一音频编码参数
AUDIO_ENCODE_PARAMS = {
'codec': 'aac',

25
domain/config.py
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@@ -9,6 +9,8 @@ import os
from dataclasses import dataclass, field
from typing import List, Optional
from constant import HW_ACCEL_NONE, HW_ACCEL_QSV, HW_ACCEL_CUDA, HW_ACCEL_TYPES
# 默认支持的任务类型
DEFAULT_CAPABILITIES = [
@@ -54,6 +56,9 @@ class WorkerConfig:
download_timeout: int = 300 # 秒，下载超时
upload_timeout: int = 600 # 秒，上传超时
# 硬件加速配置
hw_accel: str = HW_ACCEL_NONE # 硬件加速类型: none, qsv, cuda
@classmethod
def from_env(cls) -> 'WorkerConfig':
"""从环境变量创建配置"""
@@ -98,6 +103,11 @@ class WorkerConfig:
download_timeout = int(os.getenv('DOWNLOAD_TIMEOUT', '300'))
upload_timeout = int(os.getenv('UPLOAD_TIMEOUT', '600'))
# 硬件加速配置
hw_accel = os.getenv('HW_ACCEL', HW_ACCEL_NONE).lower()
if hw_accel not in HW_ACCEL_TYPES:
hw_accel = HW_ACCEL_NONE
return cls(
api_endpoint=api_endpoint,
access_key=access_key,
@@ -110,7 +120,8 @@ class WorkerConfig:
capabilities=capabilities,
ffmpeg_timeout=ffmpeg_timeout,
download_timeout=download_timeout,
upload_timeout=upload_timeout
upload_timeout=upload_timeout,
hw_accel=hw_accel
)
def get_work_dir_path(self, task_id: str) -> str:
@@ -120,3 +131,15 @@ class WorkerConfig:
def ensure_temp_dir(self) -> None:
"""确保临时目录存在"""
os.makedirs(self.temp_dir, exist_ok=True)
def is_hw_accel_enabled(self) -> bool:
"""是否启用了硬件加速"""
return self.hw_accel != HW_ACCEL_NONE
def is_qsv(self) -> bool:
"""是否使用 QSV 硬件加速"""
return self.hw_accel == HW_ACCEL_QSV
def is_cuda(self) -> bool:
"""是否使用 CUDA 硬件加速"""
return self.hw_accel == HW_ACCEL_CUDA

128
handlers/base.py
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@@ -19,6 +19,10 @@ from domain.task import Task
from domain.result import TaskResult, ErrorCode
from domain.config import WorkerConfig
from services import storage
from constant import (
HW_ACCEL_NONE, HW_ACCEL_QSV, HW_ACCEL_CUDA,
VIDEO_ENCODE_PARAMS, VIDEO_ENCODE_PARAMS_QSV, VIDEO_ENCODE_PARAMS_CUDA
)
if TYPE_CHECKING:
from services.api_client import APIClientV2
@@ -26,15 +30,94 @@ if TYPE_CHECKING:
logger = logging.getLogger(__name__)
# v2 统一视频编码参数（来自集成文档）
VIDEO_ENCODE_ARGS = [
'-c:v', 'libx264',
'-preset', 'medium',
'-profile:v', 'main',
'-level', '4.0',
'-crf', '23',
'-pix_fmt', 'yuv420p',
]
def get_video_encode_args(hw_accel: str = HW_ACCEL_NONE) -> List[str]:
"""
根据硬件加速配置获取视频编码参数
Args:
hw_accel: 硬件加速类型 (none, qsv, cuda)
Returns:
FFmpeg 视频编码参数列表
"""
if hw_accel == HW_ACCEL_QSV:
params = VIDEO_ENCODE_PARAMS_QSV
return [
'-c:v', params['codec'],
'-preset', params['preset'],
'-profile:v', params['profile'],
'-level', params['level'],
'-global_quality', params['global_quality'],
'-look_ahead', params['look_ahead'],
]
elif hw_accel == HW_ACCEL_CUDA:
params = VIDEO_ENCODE_PARAMS_CUDA
return [
'-c:v', params['codec'],
'-preset', params['preset'],
'-profile:v', params['profile'],
'-level', params['level'],
'-rc', params['rc'],
'-cq', params['cq'],
'-b:v', '0', # 配合 vbr 模式使用 cq
]
else:
# 软件编码（默认）
params = VIDEO_ENCODE_PARAMS
return [
'-c:v', params['codec'],
'-preset', params['preset'],
'-profile:v', params['profile'],
'-level', params['level'],
'-crf', params['crf'],
'-pix_fmt', params['pix_fmt'],
]
def get_hwaccel_decode_args(hw_accel: str = HW_ACCEL_NONE) -> List[str]:
"""
获取硬件加速解码参数（输入文件之前使用）
Args:
hw_accel: 硬件加速类型 (none, qsv, cuda)
Returns:
FFmpeg 硬件加速解码参数列表
"""
if hw_accel == HW_ACCEL_CUDA:
# CUDA 硬件加速解码
# 注意：使用 cuda 作为 hwaccel，但输出到系统内存以便 CPU 滤镜处理
return ['-hwaccel', 'cuda', '-hwaccel_output_format', 'cuda']
elif hw_accel == HW_ACCEL_QSV:
# QSV 硬件加速解码
return ['-hwaccel', 'qsv', '-hwaccel_output_format', 'qsv']
else:
return []
def get_hwaccel_filter_prefix(hw_accel: str = HW_ACCEL_NONE) -> str:
"""
获取硬件加速滤镜前缀（用于 hwdownload 从 GPU 到 CPU）
注意：由于大多数复杂滤镜（如 lut3d, overlay, crop 等）不支持硬件表面，
我们需要在滤镜链开始时将硬件表面下载到系统内存。
Args:
hw_accel: 硬件加速类型
Returns:
需要添加到滤镜链开头的 hwdownload 滤镜字符串
"""
if hw_accel == HW_ACCEL_CUDA:
return 'hwdownload,format=nv12,'
elif hw_accel == HW_ACCEL_QSV:
return 'hwdownload,format=nv12,'
else:
return ''
# v2 统一视频编码参数（兼容旧代码，使用软件编码）
VIDEO_ENCODE_ARGS = get_video_encode_args(HW_ACCEL_NONE)
# v2 统一音频编码参数
AUDIO_ENCODE_ARGS = [
@@ -178,6 +261,33 @@ class BaseHandler(TaskHandler, ABC):
self.config = config
self.api_client = api_client
def get_video_encode_args(self) -> List[str]:
"""
获取当前配置的视频编码参数
Returns:
FFmpeg 视频编码参数列表
"""
return get_video_encode_args(self.config.hw_accel)
def get_hwaccel_decode_args(self) -> List[str]:
"""
获取硬件加速解码参数（在输入文件之前使用）
Returns:
FFmpeg 硬件加速解码参数列表
"""
return get_hwaccel_decode_args(self.config.hw_accel)
def get_hwaccel_filter_prefix(self) -> str:
"""
获取硬件加速滤镜前缀
Returns:
需要添加到滤镜链开头的 hwdownload 滤镜字符串
"""
return get_hwaccel_filter_prefix(self.config.hw_accel)
def before_handle(self, task: Task) -> None:
"""处理前钩子"""
logger.debug(f"[task:{task.task_id}] Before handle: {task.task_type.value}")

6
handlers/compose_transition.py
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@@ -10,7 +10,7 @@ import os
import logging
from typing import List, Optional
from handlers.base import BaseHandler, VIDEO_ENCODE_ARGS
from handlers.base import BaseHandler
from domain.task import Task, TaskType, TransitionConfig, TRANSITION_TYPES
from domain.result import TaskResult, ErrorCode
@@ -235,8 +235,8 @@ class ComposeTransitionHandler(BaseHandler):
'-map', '[outv]',
]
# 编码参数（与片段视频一致）
cmd.extend(VIDEO_ENCODE_ARGS)
# 编码参数（根据硬件加速配置动态获取）
cmd.extend(self.get_video_encode_args())
# 帧率
fps = output_spec.fps

24
handlers/render_video.py
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@@ -10,7 +10,7 @@ import os
import logging
from typing import List, Optional, Tuple
from handlers.base import BaseHandler, VIDEO_ENCODE_ARGS
from handlers.base import BaseHandler
from domain.task import Task, TaskType, RenderSpec, OutputSpec, Effect
from domain.result import TaskResult, ErrorCode
@@ -170,6 +170,11 @@ class RenderSegmentVideoHandler(BaseHandler):
"""
cmd = ['ffmpeg', '-y', '-hide_banner']
# 硬件加速解码参数（在输入文件之前）
hwaccel_args = self.get_hwaccel_decode_args()
if hwaccel_args:
cmd.extend(hwaccel_args)
# 输入文件
cmd.extend(['-i', input_file])
@@ -196,8 +201,8 @@ class RenderSegmentVideoHandler(BaseHandler):
elif filters:
cmd.extend(['-vf', filters])
# 编码参数（v2 统一参数）
cmd.extend(VIDEO_ENCODE_ARGS)
# 编码参数（根据硬件加速配置动态获取）
cmd.extend(self.get_video_encode_args())
# 帧率
fps = output_spec.fps
@@ -253,6 +258,12 @@ class RenderSegmentVideoHandler(BaseHandler):
effects = render_spec.get_effects()
has_camera_shot = any(e.effect_type == 'cameraShot' for e in effects)
# 硬件加速时需要先 hwdownload（将 GPU 表面下载到系统内存）
hwaccel_prefix = self.get_hwaccel_filter_prefix()
if hwaccel_prefix:
# 去掉末尾的逗号，作为第一个滤镜
filters.append(hwaccel_prefix.rstrip(','))
# 1. 变速处理
speed = float(render_spec.speed) if render_spec.speed else 1.0
if speed != 1.0 and speed > 0:
@@ -304,7 +315,8 @@ class RenderSegmentVideoHandler(BaseHandler):
fps=fps,
has_overlay=has_overlay,
overlap_head_ms=overlap_head_ms,
overlap_tail_ms=overlap_tail_ms
overlap_tail_ms=overlap_tail_ms,
use_hwdownload=bool(hwaccel_prefix)
)
# 6. 帧冻结（tpad）- 用于转场 overlap 区域
@@ -337,7 +349,8 @@ class RenderSegmentVideoHandler(BaseHandler):
fps: int,
has_overlay: bool = False,
overlap_head_ms: int = 0,
overlap_tail_ms: int = 0
overlap_tail_ms: int = 0,
use_hwdownload: bool = False
) -> str:
"""
构建包含特效的 filter_complex 滤镜图
@@ -351,6 +364,7 @@ class RenderSegmentVideoHandler(BaseHandler):
has_overlay: 是否有叠加层
overlap_head_ms: 头部 overlap 时长
overlap_tail_ms: 尾部 overlap 时长
use_hwdownload: 是否使用了硬件加速解码（已在 base_filters 中包含 hwdownload）
Returns:
filter_complex 格式的滤镜字符串

5
services/api_client.py
View File

@@ -12,6 +12,7 @@ from typing import Dict, List, Optional, Any
from domain.task import Task
from domain.config import WorkerConfig
from util.system import get_hw_accel_info_str
logger = logging.getLogger(__name__)
@@ -338,7 +339,9 @@ class APIClientV2:
'cpu': f"{psutil.cpu_count()} cores",
'memory': f"{psutil.virtual_memory().total // (1024**3)}GB",
'cpuUsage': f"{psutil.cpu_percent()}%",
'memoryAvailable': f"{psutil.virtual_memory().available // (1024**3)}GB"
'memoryAvailable': f"{psutil.virtual_memory().available // (1024**3)}GB",
'hwAccelConfig': self.config.hw_accel, # 当前配置的硬件加速
'hwAccelSupport': get_hw_accel_info_str(), # 系统支持的硬件加速
}
# 尝试获取 GPU 信息

167
util/system.py
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@@ -8,10 +8,10 @@
import os
import platform
import subprocess
from typing import Optional
from typing import Optional, Dict, Any
import psutil
from constant import SOFTWARE_VERSION, DEFAULT_CAPABILITIES
from constant import SOFTWARE_VERSION, DEFAULT_CAPABILITIES, HW_ACCEL_NONE, HW_ACCEL_QSV, HW_ACCEL_CUDA
def get_sys_info():
@@ -101,3 +101,166 @@ def get_ffmpeg_version() -> str:
pass
return 'unknown'
def check_ffmpeg_encoder(encoder: str) -> bool:
"""
检查 FFmpeg 是否支持指定的编码器
Args:
encoder: 编码器名称，如 'h264_nvenc', 'h264_qsv'
Returns:
bool: 是否支持该编码器
"""
try:
result = subprocess.run(
['ffmpeg', '-hide_banner', '-encoders'],
capture_output=True,
text=True,
timeout=5
)
if result.returncode == 0:
return encoder in result.stdout
except Exception:
pass
return False
def check_ffmpeg_decoder(decoder: str) -> bool:
"""
检查 FFmpeg 是否支持指定的解码器
Args:
decoder: 解码器名称，如 'h264_cuvid', 'h264_qsv'
Returns:
bool: 是否支持该解码器
"""
try:
result = subprocess.run(
['ffmpeg', '-hide_banner', '-decoders'],
capture_output=True,
text=True,
timeout=5
)
if result.returncode == 0:
return decoder in result.stdout
except Exception:
pass
return False
def check_ffmpeg_hwaccel(hwaccel: str) -> bool:
"""
检查 FFmpeg 是否支持指定的硬件加速方法
Args:
hwaccel: 硬件加速方法，如 'cuda', 'qsv', 'dxva2', 'd3d11va'
Returns:
bool: 是否支持该硬件加速方法
"""
try:
result = subprocess.run(
['ffmpeg', '-hide_banner', '-hwaccels'],
capture_output=True,
text=True,
timeout=5
)
if result.returncode == 0:
return hwaccel in result.stdout
except Exception:
pass
return False
def detect_hw_accel_support() -> Dict[str, Any]:
"""
检测系统的硬件加速支持情况
Returns:
dict: 硬件加速支持信息
{
'cuda': {
'available': bool,
'gpu': str or None,
'encoder': bool, # h264_nvenc
'decoder': bool, # h264_cuvid
},
'qsv': {
'available': bool,
'encoder': bool, # h264_qsv
'decoder': bool, # h264_qsv
},
'recommended': str # 推荐的加速方式: 'cuda', 'qsv', 'none'
}
"""
result = {
'cuda': {
'available': False,
'gpu': None,
'encoder': False,
'decoder': False,
},
'qsv': {
'available': False,
'encoder': False,
'decoder': False,
},
'recommended': HW_ACCEL_NONE
}
# 检测 CUDA/NVENC 支持
gpu_info = get_gpu_info()
if gpu_info:
result['cuda']['gpu'] = gpu_info
result['cuda']['available'] = check_ffmpeg_hwaccel('cuda')
result['cuda']['encoder'] = check_ffmpeg_encoder('h264_nvenc')
result['cuda']['decoder'] = check_ffmpeg_decoder('h264_cuvid')
# 检测 QSV 支持
result['qsv']['available'] = check_ffmpeg_hwaccel('qsv')
result['qsv']['encoder'] = check_ffmpeg_encoder('h264_qsv')
result['qsv']['decoder'] = check_ffmpeg_decoder('h264_qsv')
# 推荐硬件加速方式（优先 CUDA，其次 QSV）
if result['cuda']['available'] and result['cuda']['encoder']:
result['recommended'] = HW_ACCEL_CUDA
elif result['qsv']['available'] and result['qsv']['encoder']:
result['recommended'] = HW_ACCEL_QSV
return result
def get_hw_accel_info_str() -> str:
"""
获取硬件加速支持信息的可读字符串
Returns:
str: 硬件加速支持信息描述
"""
support = detect_hw_accel_support()
parts = []
if support['cuda']['available']:
gpu = support['cuda']['gpu'] or 'Unknown GPU'
status = 'encoder+decoder' if support['cuda']['encoder'] and support['cuda']['decoder'] else (
'encoder only' if support['cuda']['encoder'] else 'decoder only' if support['cuda']['decoder'] else 'hwaccel only'
)
parts.append(f"CUDA({gpu}, {status})")
if support['qsv']['available']:
status = 'encoder+decoder' if support['qsv']['encoder'] and support['qsv']['decoder'] else (
'encoder only' if support['qsv']['encoder'] else 'decoder only' if support['qsv']['decoder'] else 'hwaccel only'
)
parts.append(f"QSV({status})")
if not parts:
return "No hardware acceleration available"
return ', '.join(parts) + f" [recommended: {support['recommended']}]"