Compare commits

...

10 Commits

Author SHA1 Message Date
e5c5a181d3 feat(config): 添加环境变量加载功能
- 集成 python-dotenv 库以支持 .env 文件
- 在主函数中添加 load_dotenv() 调用
- 实现环境配置的自动加载机制
2026-01-18 18:16:19 +08:00
f27490e9e1 feat(task): 支持图片素材类型的视频渲染
- 添加 IMAGE_EXTENSIONS 常量定义支持的图片格式
- 实现 get_material_type 方法优先使用服务端类型或根据URL后缀推断
- 添加 is_image_material 方法判断素材是否为图片类型
- 修改 RenderSegmentVideoHandler 支持图片转视频流程
- 实现 _convert_image_to_video 方法将静态图片转换为视频
- 更新下载步骤为先检测素材类型再确定输入文件扩展名
- 添加图片素材转换为视频的处理逻辑
- 重构步骤编号以匹配新的处理流程
- 优化错误提示信息支持HTTP/HTTPS协议检查
2026-01-18 13:52:46 +08:00
10c57a387f feat(config): 更新环境配置文件模板
- 修改 API_ENDPOINT 默认地址为本地开发地址
- 添加 WORKER_ID 配置项
- 新增硬件加速配置选项 HW_ACCEL
- 添加素材缓存配置 CACHE_ENABLED、CACHE_DIR、CACHE_MAX_SIZE_GB
- 新增下载 URL 映射配置 HTTP_REPLACE_MAP
- 更新上传方式配置选项和相关参数
- 重新组织配置项分组和注释说明
2026-01-17 17:43:36 +08:00
a72e1ef1a1 fix(video): 解决LUT路径中冒号转义问题
- 在LUT路径处理中添加冒号转义功能,避免FFmpeg filter语法冲突
- 保留原有的反斜杠转换逻辑
- 确保LUT文件路径在FFmpeg命令中正确解析
2026-01-17 16:57:16 +08:00
095e203fe6 feat(task): 增强素材URL处理和验证逻辑
- 添加详细的get_material_url方法文档说明优先级逻辑
- 新增get_source_ref方法用于获取素材源引用
- 新增get_bound_material_url方法用于获取绑定素材URL
- 在视频渲染处理器中添加HTTP URL格式验证检查
- 当素材URL格式无效时返回详细错误信息和调试日志
- 验证失败时返回E_SPEC_INVALID错误码并提示服务器需提供有效的boundMaterialUrl
2026-01-17 16:22:01 +08:00
fe757408b6 feat(cache): 添加素材缓存功能以避免重复下载
- 新增素材缓存配置选项包括启用状态、缓存目录和最大缓存大小
- 实现 MaterialCache 类提供缓存存储和检索功能
- 修改 download_file 方法支持缓存下载模式
- 添加缓存清理机制使用 LRU 策略管理磁盘空间
- 配置默认值优化本地开发体验
- 实现缓存统计和监控功能
2026-01-17 15:07:12 +08:00
d5cd0dca03 fix(api): 修复任务列表解析中的空值错误
- 将 data.get('data', {}).get('tasks', []) 修改为 data.get('data', {}).get('tasks') or []
- 防止当 tasks 字段为 None 时导致的解析异常
- 确保即使返回数据中没有 tasks 字段也能正常处理
2026-01-17 14:35:58 +08:00
2bded11a03 feat(task): 添加转场效果相关属性和方法
- 新增 get_transition_type、get_transition_ms、has_transition 方法用于处理转场类型和时长
- 新增 get_overlap_tail_ms、get_transition_in_type、get_transition_in_ms 等方法处理入场转场
- 新增 get_transition_out_type、get_transition_out_ms、has_transition_out 等方法处理出场转场
- 新增 get_overlap_head_ms、get_overlap_tail_ms_v2 方法计算头部和尾部重叠时长
- 更新渲染视频处理器中使用新的转场相关方法计算 overlap 时长
2026-01-14 09:30:09 +08:00
71bd2e59f9 feat(video): 添加硬件加速支持
- 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
2026-01-13 13:34:27 +08:00
a26c44a3cd feat(video): 添加视频特效处理功能
- 在常量模块中定义支持的特效类型(相机定格、缩放、模糊)
- 在任务域中创建Effect数据类,支持从字符串解析特效配置
- 实现cameraShot特效参数解析和默认值处理
- 扩展RenderSpec类,添加获取特效列表的方法
- 修改视频渲染处理器,集成特效滤镜构建逻辑
- 实现cameraShot特效的filter_complex滤镜图构建
- 添加fps参数支持和overlay检测逻辑优化
- 完成特效与转场overlap的兼容处理
2026-01-13 09:31:39 +08:00
11 changed files with 1238 additions and 56 deletions

View File

@@ -1,13 +1,59 @@
TEMPLATE_DIR=template/
API_ENDPOINT=https://zhentuai.com/task/v1
# ===================
# API 配置
# ===================
API_ENDPOINT=http://127.0.0.1:18084/api
ACCESS_KEY=TEST_ACCESS_KEY
WORKER_ID=1
# ===================
# 目录配置
# ===================
TEMP_DIR=tmp/
#REDIRECT_TO_URL=https://renderworker-deuvulkhes.cn-shanghai.fcapp.run/
# QSV
ENCODER_ARGS="-c:v h264_qsv -global_quality 28 -look_ahead 1"
# NVENC
#ENCODER_ARGS="-c:v h264_nvenc -cq:v 24 -preset:v p7 -tune:v hq -profile:v high"
# HEVC
#VIDEO_ARGS="-profile:v main
UPLOAD_METHOD="rclone"
RCLONE_REPLACE_MAP="https://oss.zhentuai.com|alioss://frametour-assets,https://frametour-assets.oss-cn-shanghai.aliyuncs.com|alioss://frametour-assets"
# ===================
# 并发与调度
# ===================
#MAX_CONCURRENCY=4 # 最大并发任务数
#HEARTBEAT_INTERVAL=5 # 心跳间隔(秒)
#LEASE_EXTENSION_THRESHOLD=60 # 租约续期阈值(秒),提前多久续期
#LEASE_EXTENSION_DURATION=300 # 租约续期时长(秒)
# ===================
# 能力配置
# ===================
# 支持的任务类型,逗号分隔,默认全部支持
#CAPABILITIES=RENDER_SEGMENT_VIDEO,PREPARE_JOB_AUDIO,PACKAGE_SEGMENT_TS,FINALIZE_MP4
# ===================
# 超时配置
# ===================
#FFMPEG_TIMEOUT=3600 # FFmpeg 执行超时(秒)
#DOWNLOAD_TIMEOUT=300 # 下载超时(秒)
#UPLOAD_TIMEOUT=600 # 上传超时(秒)
# ===================
# 硬件加速
# ===================
# 可选值: none, qsv, cuda
HW_ACCEL=none
# ===================
# 素材缓存
# ===================
#CACHE_ENABLED=true # 是否启用素材缓存
#CACHE_DIR= # 缓存目录,默认 TEMP_DIR/cache
#CACHE_MAX_SIZE_GB=0 # 最大缓存大小(GB),0 表示不限制
# ===================
# URL 映射(内网下载加速)
# ===================
# 格式: src1|dst1,src2|dst2
#HTTP_REPLACE_MAP="https://cdcdn.zhentuai.com|http://192.168.10.254:9000"
# ===================
# 上传配置
# ===================
# 上传方式: 默认 HTTP,可选 rclone
#UPLOAD_METHOD=rclone
#RCLONE_CONFIG_FILE= # rclone 配置文件路径
#RCLONE_REPLACE_MAP="https://oss.example.com|alioss://bucket"

View File

@@ -34,7 +34,21 @@ TRANSITION_TYPES = (
'slidedown', # 向下滑动
)
# 统一视频编码参数(来自集成文档)
# 支持的特效类型
EFFECT_TYPES = (
'cameraShot', # 相机定格效果:在指定时间点冻结画面
'zoom', # 缩放效果(预留)
'blur', # 模糊效果(预留)
)
# 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',
@@ -44,6 +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',

View File

@@ -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 +56,14 @@ 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
# 素材缓存配置
cache_enabled: bool = True # 是否启用素材缓存
cache_dir: str = "" # 缓存目录,默认为 temp_dir/cache
cache_max_size_gb: float = 0 # 最大缓存大小(GB),0 表示不限制
@classmethod
def from_env(cls) -> 'WorkerConfig':
"""从环境变量创建配置"""
@@ -98,6 +108,16 @@ 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
# 素材缓存配置
cache_enabled = os.getenv('CACHE_ENABLED', 'true').lower() in ('true', '1', 'yes')
cache_dir = os.getenv('CACHE_DIR', '') # 空字符串表示使用默认路径
cache_max_size_gb = float(os.getenv('CACHE_MAX_SIZE_GB', '0'))
return cls(
api_endpoint=api_endpoint,
access_key=access_key,
@@ -110,7 +130,11 @@ class WorkerConfig:
capabilities=capabilities,
ffmpeg_timeout=ffmpeg_timeout,
download_timeout=download_timeout,
upload_timeout=upload_timeout
upload_timeout=upload_timeout,
hw_accel=hw_accel,
cache_enabled=cache_enabled,
cache_dir=cache_dir if cache_dir else os.path.join(temp_dir, 'cache'),
cache_max_size_gb=cache_max_size_gb
)
def get_work_dir_path(self, task_id: str) -> str:
@@ -120,3 +144,15 @@ 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

View File

@@ -9,6 +9,12 @@ from enum import Enum
from dataclasses import dataclass, field
from typing import Dict, Any, Optional, List
from datetime import datetime
from urllib.parse import urlparse, unquote
import os
# 支持的图片扩展名
IMAGE_EXTENSIONS = {'.jpg', '.jpeg', '.png', '.webp', '.bmp', '.gif'}
class TaskType(Enum):
@@ -34,6 +40,13 @@ TRANSITION_TYPES = {
'slidedown': 'slidedown', # 向下滑动
}
# 支持的特效类型
EFFECT_TYPES = {
'cameraShot', # 相机定格效果
'zoom', # 缩放效果(预留)
'blur', # 模糊效果(预留)
}
class TaskStatus(Enum):
"""任务状态枚举"""
@@ -76,6 +89,70 @@ class TransitionConfig:
return TRANSITION_TYPES.get(self.type, 'fade')
@dataclass
class Effect:
"""
特效配置
格式:type:params
例如:cameraShot:3,1 表示在第3秒定格1秒
"""
effect_type: str # 效果类型
params: str = "" # 参数字符串
@classmethod
def from_string(cls, effect_str: str) -> Optional['Effect']:
"""
从字符串解析 Effect
格式:type:params 或 type(无参数时)
"""
if not effect_str:
return None
parts = effect_str.split(':', 1)
effect_type = parts[0].strip()
if effect_type not in EFFECT_TYPES:
return None
params = parts[1].strip() if len(parts) > 1 else ""
return cls(effect_type=effect_type, params=params)
@classmethod
def parse_effects(cls, effects_str: Optional[str]) -> List['Effect']:
"""
解析效果字符串
格式:effect1|effect2|effect3
例如:cameraShot:3,1|blur:5
"""
if not effects_str:
return []
effects = []
for part in effects_str.split('|'):
effect = cls.from_string(part.strip())
if effect:
effects.append(effect)
return effects
def get_camera_shot_params(self) -> tuple:
"""
获取 cameraShot 效果参数
Returns:
(start_sec, duration_sec): 开始时间和持续时间(秒)
"""
if self.effect_type != 'cameraShot':
return (0, 0)
if not self.params:
return (3, 1) # 默认值
parts = self.params.split(',')
try:
start = int(parts[0]) if len(parts) >= 1 else 3
duration = int(parts[1]) if len(parts) >= 2 else 1
return (start, duration)
except ValueError:
return (3, 1)
@dataclass
class RenderSpec:
"""
@@ -137,6 +214,10 @@ class RenderSpec:
return self.transition_out.get_overlap_ms()
return 0
def get_effects(self) -> List['Effect']:
"""获取解析后的特效列表"""
return Effect.parse_effects(self.effects)
@dataclass
class OutputSpec:
@@ -275,9 +356,56 @@ class Task:
return int(self.payload.get('durationMs', 5000))
def get_material_url(self) -> Optional[str]:
"""获取素材 URL"""
"""
获取素材 URL
优先使用 boundMaterialUrl(实际可下载的 HTTP URL),
如果不存在则回退到 sourceRef(可能是 slot 引用)。
Returns:
素材 URL,如果都不存在返回 None
"""
return self.payload.get('boundMaterialUrl') or self.payload.get('sourceRef')
def get_source_ref(self) -> Optional[str]:
"""获取素材源引用(slot 标识符,如 device:xxx)"""
return self.payload.get('sourceRef')
def get_bound_material_url(self) -> Optional[str]:
"""获取绑定的素材 URL(实际可下载的 HTTP URL)"""
return self.payload.get('boundMaterialUrl')
def get_material_type(self) -> str:
"""
获取素材类型
优先使用服务端下发的 materialType 字段,
如果不存在则根据 URL 后缀自动推断。
Returns:
素材类型:"video""image"
"""
# 优先使用服务端下发的类型
material_type = self.payload.get('materialType')
if material_type in ('video', 'image'):
return material_type
# 降级:根据 URL 后缀推断
material_url = self.get_material_url()
if material_url:
parsed = urlparse(material_url)
path = unquote(parsed.path)
_, ext = os.path.splitext(path)
if ext.lower() in IMAGE_EXTENSIONS:
return 'image'
# 默认视频类型
return 'video'
def is_image_material(self) -> bool:
"""判断素材是否为图片类型"""
return self.get_material_type() == 'image'
def get_render_spec(self) -> RenderSpec:
"""获取渲染规格"""
return RenderSpec.from_dict(self.payload.get('renderSpec'))
@@ -286,6 +414,69 @@ class Task:
"""获取输出规格"""
return OutputSpec.from_dict(self.payload.get('output'))
def get_transition_type(self) -> Optional[str]:
"""获取转场类型(来自 TaskPayload 顶层)"""
return self.payload.get('transitionType')
def get_transition_ms(self) -> int:
"""获取转场时长(毫秒,来自 TaskPayload 顶层)"""
return int(self.payload.get('transitionMs', 0))
def has_transition(self) -> bool:
"""是否有转场效果"""
return self.get_transition_ms() > 0
def get_overlap_tail_ms(self) -> int:
"""
获取尾部 overlap 时长(毫秒)
转场发生在当前片段与下一片段之间,当前片段需要在尾部多渲染 overlap 帧。
overlap = transitionMs / 2
"""
return self.get_transition_ms() // 2
def get_transition_in_type(self) -> Optional[str]:
"""获取入场转场类型(来自前一片段的出场转场)"""
return self.payload.get('transitionInType')
def get_transition_in_ms(self) -> int:
"""获取入场转场时长(毫秒)"""
return int(self.payload.get('transitionInMs', 0))
def get_transition_out_type(self) -> Optional[str]:
"""获取出场转场类型(当前片段的转场配置)"""
return self.payload.get('transitionOutType')
def get_transition_out_ms(self) -> int:
"""获取出场转场时长(毫秒)"""
return int(self.payload.get('transitionOutMs', 0))
def has_transition_in(self) -> bool:
"""是否有入场转场"""
return self.get_transition_in_ms() > 0
def has_transition_out(self) -> bool:
"""是否有出场转场"""
return self.get_transition_out_ms() > 0
def get_overlap_head_ms(self) -> int:
"""
获取头部 overlap 时长(毫秒)
入场转场来自前一个片段,当前片段需要在头部多渲染 overlap 帧。
overlap = transitionInMs / 2
"""
return self.get_transition_in_ms() // 2
def get_overlap_tail_ms_v2(self) -> int:
"""
获取尾部 overlap 时长(毫秒)- 使用新的字段名
出场转场用于当前片段与下一片段之间,当前片段需要在尾部多渲染 overlap 帧。
overlap = transitionOutMs / 2
"""
return self.get_transition_out_ms() // 2
def get_bgm_url(self) -> Optional[str]:
"""获取 BGM URL"""
return self.payload.get('bgmUrl')

View File

@@ -19,6 +19,11 @@ from domain.task import Task
from domain.result import TaskResult, ErrorCode
from domain.config import WorkerConfig
from services import storage
from services.cache import MaterialCache
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 +31,94 @@ 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 = [
@@ -177,6 +261,38 @@ class BaseHandler(TaskHandler, ABC):
"""
self.config = config
self.api_client = api_client
self.material_cache = MaterialCache(
cache_dir=config.cache_dir,
enabled=config.cache_enabled,
max_size_gb=config.cache_max_size_gb
)
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"""
@@ -223,14 +339,15 @@ class BaseHandler(TaskHandler, ABC):
except Exception as e:
logger.warning(f"Failed to cleanup work directory {work_dir}: {e}")
def download_file(self, url: str, dest: str, timeout: int = None) -> bool:
def download_file(self, url: str, dest: str, timeout: int = None, use_cache: bool = True) -> bool:
"""
下载文件
下载文件(支持缓存)
Args:
url: 文件 URL
dest: 目标路径
timeout: 超时时间(秒)
use_cache: 是否使用缓存(默认 True)
Returns:
是否成功
@@ -239,7 +356,13 @@ class BaseHandler(TaskHandler, ABC):
timeout = self.config.download_timeout
try:
if use_cache:
# 使用缓存下载
result = self.material_cache.get_or_download(url, dest, timeout=timeout)
else:
# 直接下载(不走缓存)
result = storage.download_file(url, dest, timeout=timeout)
if result:
file_size = os.path.getsize(dest) if os.path.exists(dest) else 0
logger.debug(f"Downloaded: {url} -> {dest} ({file_size} bytes)")

View File

@@ -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

View File

@@ -9,14 +9,23 @@
import os
import logging
from typing import List, Optional, Tuple
from urllib.parse import urlparse, unquote
from handlers.base import BaseHandler, VIDEO_ENCODE_ARGS
from domain.task import Task, TaskType, RenderSpec, OutputSpec
from handlers.base import BaseHandler
from domain.task import Task, TaskType, RenderSpec, OutputSpec, Effect, IMAGE_EXTENSIONS
from domain.result import TaskResult, ErrorCode
logger = logging.getLogger(__name__)
def _get_extension_from_url(url: str) -> str:
"""从 URL 提取文件扩展名"""
parsed = urlparse(url)
path = unquote(parsed.path)
_, ext = os.path.splitext(path)
return ext.lower() if ext else ''
class RenderSegmentVideoHandler(BaseHandler):
"""
视频片段渲染处理器
@@ -46,19 +55,63 @@ class RenderSegmentVideoHandler(BaseHandler):
"Missing material URL (boundMaterialUrl or sourceRef)"
)
# 检查 URL 格式:必须是 HTTP 或 HTTPS 协议
if not material_url.startswith(('http://', 'https://')):
source_ref = task.get_source_ref()
bound_url = task.get_bound_material_url()
logger.error(
f"[task:{task.task_id}] Invalid material URL format: '{material_url}'. "
f"boundMaterialUrl={bound_url}, sourceRef={source_ref}. "
f"Server should provide boundMaterialUrl with HTTP/HTTPS URL."
)
return TaskResult.fail(
ErrorCode.E_SPEC_INVALID,
f"Invalid material URL: '{material_url}' is not a valid HTTP/HTTPS URL. "
f"Server must provide boundMaterialUrl."
)
render_spec = task.get_render_spec()
output_spec = task.get_output_spec()
duration_ms = task.get_duration_ms()
# 1. 下载素材
# 1. 检测素材类型并确定输入文件扩展名
is_image = task.is_image_material()
if is_image:
# 图片素材:根据 URL 确定扩展名
ext = _get_extension_from_url(material_url)
if not ext or ext not in IMAGE_EXTENSIONS:
ext = '.jpg' # 默认扩展名
input_file = os.path.join(work_dir, f'input{ext}')
else:
input_file = os.path.join(work_dir, 'input.mp4')
# 2. 下载素材
if not self.download_file(material_url, input_file):
return TaskResult.fail(
ErrorCode.E_INPUT_UNAVAILABLE,
f"Failed to download material: {material_url}"
)
# 2. 下载 LUT(如有)
# 3. 图片素材转换为视频
if is_image:
video_input_file = os.path.join(work_dir, 'input_video.mp4')
if not self._convert_image_to_video(
image_file=input_file,
output_file=video_input_file,
duration_ms=duration_ms,
output_spec=output_spec,
render_spec=render_spec,
task_id=task.task_id
):
return TaskResult.fail(
ErrorCode.E_FFMPEG_FAILED,
"Failed to convert image to video"
)
# 使用转换后的视频作为输入
input_file = video_input_file
logger.info(f"[task:{task.task_id}] Image converted to video successfully")
# 4. 下载 LUT(如有)
lut_file = None
if render_spec.lut_url:
lut_file = os.path.join(work_dir, 'lut.cube')
@@ -66,7 +119,7 @@ class RenderSegmentVideoHandler(BaseHandler):
logger.warning(f"[task:{task.task_id}] Failed to download LUT, continuing without it")
lut_file = None
# 3. 下载叠加层(如有)
# 5. 下载叠加层(如有)
overlay_file = None
if render_spec.overlay_url:
# 根据 URL 后缀确定文件扩展名
@@ -78,11 +131,13 @@ class RenderSegmentVideoHandler(BaseHandler):
logger.warning(f"[task:{task.task_id}] Failed to download overlay, continuing without it")
overlay_file = None
# 4. 计算 overlap 时长
overlap_head_ms = render_spec.get_overlap_head_ms()
overlap_tail_ms = render_spec.get_overlap_tail_ms()
# 6. 计算 overlap 时长(用于转场帧冻结)
# 头部 overlap: 来自前一片段的出场转场
overlap_head_ms = task.get_overlap_head_ms()
# 尾部 overlap: 当前片段的出场转场
overlap_tail_ms = task.get_overlap_tail_ms_v2()
# 5. 构建 FFmpeg 命令
# 7. 构建 FFmpeg 命令
output_file = os.path.join(work_dir, 'output.mp4')
cmd = self._build_command(
input_file=input_file,
@@ -96,25 +151,25 @@ class RenderSegmentVideoHandler(BaseHandler):
overlap_tail_ms=overlap_tail_ms
)
# 6. 执行 FFmpeg
# 8. 执行 FFmpeg
if not self.run_ffmpeg(cmd, task.task_id):
return TaskResult.fail(
ErrorCode.E_FFMPEG_FAILED,
"FFmpeg rendering failed"
)
# 7. 验证输出文件
# 9. 验证输出文件
if not self.ensure_file_exists(output_file, min_size=4096):
return TaskResult.fail(
ErrorCode.E_FFMPEG_FAILED,
"Output file is missing or too small"
)
# 8. 获取实际时长
# 10. 获取实际时长
actual_duration = self.probe_duration(output_file)
actual_duration_ms = int(actual_duration * 1000) if actual_duration else duration_ms
# 9. 上传产物
# 11. 上传产物
video_url = self.upload_file(task.task_id, 'video', output_file)
if not video_url:
return TaskResult.fail(
@@ -122,7 +177,7 @@ class RenderSegmentVideoHandler(BaseHandler):
"Failed to upload video"
)
# 10. 构建结果(包含 overlap 信息)
# 12. 构建结果(包含 overlap 信息)
result_data = {
'videoUrl': video_url,
'actualDurationMs': actual_duration_ms,
@@ -139,6 +194,96 @@ class RenderSegmentVideoHandler(BaseHandler):
finally:
self.cleanup_work_dir(work_dir)
def _convert_image_to_video(
self,
image_file: str,
output_file: str,
duration_ms: int,
output_spec: OutputSpec,
render_spec: RenderSpec,
task_id: str
) -> bool:
"""
将图片转换为视频
使用 FFmpeg 将静态图片转换为指定时长的视频,
同时应用缩放填充和变速处理。
Args:
image_file: 输入图片文件路径
output_file: 输出视频文件路径
duration_ms: 目标时长(毫秒)
output_spec: 输出规格
render_spec: 渲染规格
task_id: 任务 ID(用于日志)
Returns:
是否成功
"""
width = output_spec.width
height = output_spec.height
fps = output_spec.fps
# 计算实际时长(考虑变速)
speed = float(render_spec.speed) if render_spec.speed else 1.0
if speed <= 0:
speed = 1.0
# 变速后的实际播放时长
actual_duration_sec = (duration_ms / 1000.0) / speed
# 构建 FFmpeg 命令
cmd = [
'ffmpeg', '-y', '-hide_banner',
'-loop', '1', # 循环输入图片
'-i', image_file,
'-t', str(actual_duration_sec), # 输出时长
]
# 构建滤镜:缩放填充到目标尺寸
filters = []
# 裁切处理(与视频相同逻辑)
if render_spec.crop_enable and render_spec.face_pos:
try:
fx, fy = map(float, render_spec.face_pos.split(','))
target_ratio = width / height
filters.append(
f"crop='min(iw,ih*{target_ratio})':'min(ih,iw/{target_ratio})':"
f"'(iw-min(iw,ih*{target_ratio}))*{fx}':"
f"'(ih-min(ih,iw/{target_ratio}))*{fy}'"
)
except (ValueError, ZeroDivisionError):
logger.warning(f"[task:{task_id}] Invalid face position: {render_spec.face_pos}")
elif render_spec.zoom_cut:
target_ratio = width / height
filters.append(
f"crop='min(iw,ih*{target_ratio})':'min(ih,iw/{target_ratio})'"
)
# 缩放填充
filters.append(
f"scale={width}:{height}:force_original_aspect_ratio=decrease,"
f"pad={width}:{height}:(ow-iw)/2:(oh-ih)/2:black"
)
# 格式转换(确保兼容性)
filters.append("format=yuv420p")
cmd.extend(['-vf', ','.join(filters)])
# 编码参数
cmd.extend([
'-c:v', 'libx264',
'-preset', 'fast',
'-crf', '18',
'-r', str(fps),
'-an', # 无音频
output_file
])
logger.info(f"[task:{task_id}] Converting image to video: {actual_duration_sec:.2f}s at {fps}fps")
return self.run_ffmpeg(cmd, task_id)
def _build_command(
self,
input_file: str,
@@ -170,6 +315,11 @@ 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])
@@ -188,14 +338,16 @@ class RenderSegmentVideoHandler(BaseHandler):
)
# 应用滤镜
if overlay_file:
# 使用 filter_complex 处理叠加
# 检测是否为 filter_complex 格式(包含分号或方括号标签)
is_filter_complex = ';' in filters or (filters.startswith('[') and ']' in filters)
if is_filter_complex or overlay_file:
# 使用 filter_complex 处理
cmd.extend(['-filter_complex', filters])
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
@@ -245,6 +397,17 @@ class RenderSegmentVideoHandler(BaseHandler):
filters = []
width = output_spec.width
height = output_spec.height
fps = output_spec.fps
# 解析 effects
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
@@ -255,8 +418,8 @@ class RenderSegmentVideoHandler(BaseHandler):
# 2. LUT 调色
if lut_file:
# 路径中的反斜杠需要转
lut_path = lut_file.replace('\\', '/')
# 路径中的反斜杠需要转换,冒号需要转义(FFmpeg filter语法中冒号是特殊字符)
lut_path = lut_file.replace('\\', '/').replace(':', r'\:')
filters.append(f"lut3d='{lut_path}'")
# 3. 裁切处理
@@ -288,7 +451,20 @@ class RenderSegmentVideoHandler(BaseHandler):
)
filters.append(scale_filter)
# 5. 帧冻结(tpad)- 用于转场 overlap 区域
# 5. 特效处理(cameraShot 需要特殊处理)
if has_camera_shot:
# cameraShot 需要使用 filter_complex 格式
return self._build_filter_complex_with_effects(
base_filters=filters,
effects=effects,
fps=fps,
has_overlay=has_overlay,
overlap_head_ms=overlap_head_ms,
overlap_tail_ms=overlap_tail_ms,
use_hwdownload=bool(hwaccel_prefix)
)
# 6. 帧冻结(tpad)- 用于转场 overlap 区域
# 注意:tpad 必须在缩放之后应用
tpad_parts = []
if overlap_head_ms > 0:
@@ -303,10 +479,122 @@ class RenderSegmentVideoHandler(BaseHandler):
if tpad_parts:
filters.append(f"tpad={':'.join(tpad_parts)}")
# 6. 构建最终滤镜
# 7. 构建最终滤镜
if has_overlay:
# 使用 filter_complex 格式
base_filters = ','.join(filters) if filters else 'copy'
return f"[0:v]{base_filters}[base];[base][1:v]overlay=0:0"
else:
return ','.join(filters) if filters else ''
def _build_filter_complex_with_effects(
self,
base_filters: List[str],
effects: List[Effect],
fps: int,
has_overlay: bool = False,
overlap_head_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
cameraShot 效果需要使用 split/freezeframes/concat 滤镜组合。
Args:
base_filters: 基础滤镜列表
effects: 特效列表
fps: 帧率
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
"""
filter_parts = []
# 基础滤镜链
base_chain = ','.join(base_filters) if base_filters else 'copy'
# 当前输出标签
current_output = '[v_base]'
filter_parts.append(f"[0:v]{base_chain}{current_output}")
# 处理每个特效
effect_idx = 0
for effect in effects:
if effect.effect_type == 'cameraShot':
start_sec, duration_sec = effect.get_camera_shot_params()
if start_sec <= 0 or duration_sec <= 0:
continue
# cameraShot 实现:
# 1. fps + split 分割
# 2. 第一路:trim(0, start+duration) + freezeframes
# 3. 第二路:trim(start, end)
# 4. concat 拼接
start_frame = start_sec * fps
split_out_a = f'[eff{effect_idx}_a]'
split_out_b = f'[eff{effect_idx}_b]'
effect_output = f'[v_eff{effect_idx}]'
# fps + split
filter_parts.append(
f"{current_output}fps=fps={fps},split{split_out_a}{split_out_b}"
)
# 第一路:trim + freezeframes(在 start 帧处冻结 duration 秒)
# freezeframes: 从 first 帧开始,用 replace 帧替换后续帧
# 这样实现定格效果:在 start_frame 位置冻结
filter_parts.append(
f"{split_out_a}trim=start=0:end={start_sec + duration_sec},"
f"setpts=PTS-STARTPTS,"
f"freezeframes=first={start_frame}:last={start_frame + duration_sec * fps - 1}:replace={start_frame}"
f"{split_out_a}"
)
# 第二路:trim 从 start 开始
filter_parts.append(
f"{split_out_b}trim=start={start_sec},setpts=PTS-STARTPTS{split_out_b}"
)
# concat 拼接
filter_parts.append(
f"{split_out_a}{split_out_b}concat=n=2:v=1:a=0{effect_output}"
)
current_output = effect_output
effect_idx += 1
# 帧冻结(tpad)- 用于转场 overlap 区域
tpad_parts = []
if overlap_head_ms > 0:
head_duration_sec = overlap_head_ms / 1000.0
tpad_parts.append(f"start_mode=clone:start_duration={head_duration_sec}")
if overlap_tail_ms > 0:
tail_duration_sec = overlap_tail_ms / 1000.0
tpad_parts.append(f"stop_mode=clone:stop_duration={tail_duration_sec}")
if tpad_parts:
tpad_output = '[v_tpad]'
filter_parts.append(f"{current_output}tpad={':'.join(tpad_parts)}{tpad_output}")
current_output = tpad_output
# 最终输出
if has_overlay:
# 叠加层处理
filter_parts.append(f"{current_output}[1:v]overlay=0:0")
else:
# 移除最后一个标签,直接输出
# 将最后一个滤镜的输出标签替换为空(直接输出)
if filter_parts:
last_filter = filter_parts[-1]
# 移除末尾的输出标签
if last_filter.endswith(current_output):
filter_parts[-1] = last_filter[:-len(current_output)]
return ';'.join(filter_parts)

View File

@@ -26,6 +26,8 @@ import time
import signal
import logging
from dotenv import load_dotenv
from domain.config import WorkerConfig
from services.api_client import APIClientV2
from services.task_executor import TaskExecutor
@@ -166,6 +168,9 @@ class WorkerV2:
def main():
"""主函数"""
# 加载 .env 文件(如果存在)
load_dotenv()
logger.info(f"RenderWorker v{SOFTWARE_VERSION}")
# 创建并运行 Worker

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__)
@@ -80,7 +81,7 @@ class APIClientV2:
# 解析任务列表
tasks = []
for task_data in data.get('data', {}).get('tasks', []):
for task_data in data.get('data', {}).get('tasks') or []:
try:
task = Task.from_dict(task_data)
tasks.append(task)
@@ -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

291
services/cache.py Normal file
View File

@@ -0,0 +1,291 @@
# -*- coding: utf-8 -*-
"""
素材缓存服务
提供素材下载缓存功能,避免相同素材重复下载。
"""
import os
import hashlib
import logging
import shutil
import time
from typing import Optional, Tuple
from urllib.parse import urlparse, unquote
from services import storage
logger = logging.getLogger(__name__)
def _extract_cache_key(url: str) -> str:
"""
从 URL 提取缓存键
去除签名等查询参数,保留路径作为唯一标识。
Args:
url: 完整的素材 URL
Returns:
缓存键(URL 路径的 MD5 哈希)
"""
parsed = urlparse(url)
# 使用 scheme + host + path 作为唯一标识(忽略签名等查询参数)
cache_key_source = f"{parsed.scheme}://{parsed.netloc}{unquote(parsed.path)}"
return hashlib.md5(cache_key_source.encode('utf-8')).hexdigest()
def _get_file_extension(url: str) -> str:
"""
从 URL 提取文件扩展名
Args:
url: 素材 URL
Returns:
文件扩展名(如 .mp4, .png),无法识别时返回空字符串
"""
parsed = urlparse(url)
path = unquote(parsed.path)
_, ext = os.path.splitext(path)
return ext.lower() if ext else ''
class MaterialCache:
"""
素材缓存管理器
负责素材文件的缓存存储和检索。
"""
def __init__(self, cache_dir: str, enabled: bool = True, max_size_gb: float = 0):
"""
初始化缓存管理器
Args:
cache_dir: 缓存目录路径
enabled: 是否启用缓存
max_size_gb: 最大缓存大小(GB),0 表示不限制
"""
self.cache_dir = cache_dir
self.enabled = enabled
self.max_size_bytes = int(max_size_gb * 1024 * 1024 * 1024) if max_size_gb > 0 else 0
if self.enabled:
os.makedirs(self.cache_dir, exist_ok=True)
logger.info(f"Material cache initialized: {cache_dir}")
def get_cache_path(self, url: str) -> str:
"""
获取素材的缓存文件路径
Args:
url: 素材 URL
Returns:
缓存文件的完整路径
"""
cache_key = _extract_cache_key(url)
ext = _get_file_extension(url)
filename = f"{cache_key}{ext}"
return os.path.join(self.cache_dir, filename)
def is_cached(self, url: str) -> Tuple[bool, str]:
"""
检查素材是否已缓存
Args:
url: 素材 URL
Returns:
(是否已缓存, 缓存文件路径)
"""
if not self.enabled:
return False, ''
cache_path = self.get_cache_path(url)
exists = os.path.exists(cache_path) and os.path.getsize(cache_path) > 0
return exists, cache_path
def get_or_download(
self,
url: str,
dest: str,
timeout: int = 300,
max_retries: int = 5
) -> bool:
"""
从缓存获取素材,若未缓存则下载并缓存
Args:
url: 素材 URL
dest: 目标文件路径(任务工作目录中的路径)
timeout: 下载超时时间(秒)
max_retries: 最大重试次数
Returns:
是否成功
"""
# 确保目标目录存在
dest_dir = os.path.dirname(dest)
if dest_dir:
os.makedirs(dest_dir, exist_ok=True)
# 缓存未启用时直接下载
if not self.enabled:
return storage.download_file(url, dest, max_retries=max_retries, timeout=timeout)
# 检查缓存
cached, cache_path = self.is_cached(url)
if cached:
# 命中缓存,复制到目标路径
try:
shutil.copy2(cache_path, dest)
# 更新访问时间(用于 LRU 清理)
os.utime(cache_path, None)
file_size = os.path.getsize(dest)
logger.info(f"Cache hit: {url[:80]}... -> {dest} ({file_size} bytes)")
return True
except Exception as e:
logger.warning(f"Failed to copy from cache: {e}, will re-download")
# 缓存复制失败,删除可能损坏的缓存文件
try:
os.remove(cache_path)
except Exception:
pass
# 未命中缓存,下载到缓存目录
logger.debug(f"Cache miss: {url[:80]}...")
# 先下载到临时文件
temp_cache_path = cache_path + '.downloading'
try:
if not storage.download_file(url, temp_cache_path, max_retries=max_retries, timeout=timeout):
# 下载失败,清理临时文件
if os.path.exists(temp_cache_path):
os.remove(temp_cache_path)
return False
# 下载成功,移动到正式缓存路径
if os.path.exists(cache_path):
os.remove(cache_path)
os.rename(temp_cache_path, cache_path)
# 复制到目标路径
shutil.copy2(cache_path, dest)
file_size = os.path.getsize(dest)
logger.info(f"Downloaded and cached: {url[:80]}... ({file_size} bytes)")
# 检查是否需要清理缓存
if self.max_size_bytes > 0:
self._cleanup_if_needed()
return True
except Exception as e:
logger.error(f"Cache download error: {e}")
# 清理临时文件
if os.path.exists(temp_cache_path):
try:
os.remove(temp_cache_path)
except Exception:
pass
return False
def _cleanup_if_needed(self) -> None:
"""
检查并清理缓存(LRU 策略)
当缓存大小超过限制时,删除最久未访问的文件。
"""
if self.max_size_bytes <= 0:
return
try:
# 获取所有缓存文件及其信息
cache_files = []
total_size = 0
for filename in os.listdir(self.cache_dir):
if filename.endswith('.downloading'):
continue
file_path = os.path.join(self.cache_dir, filename)
if os.path.isfile(file_path):
stat = os.stat(file_path)
cache_files.append({
'path': file_path,
'size': stat.st_size,
'atime': stat.st_atime
})
total_size += stat.st_size
# 如果未超过限制,无需清理
if total_size <= self.max_size_bytes:
return
# 按访问时间排序(最久未访问的在前)
cache_files.sort(key=lambda x: x['atime'])
# 删除文件直到低于限制的 80%
target_size = int(self.max_size_bytes * 0.8)
deleted_count = 0
for file_info in cache_files:
if total_size <= target_size:
break
try:
os.remove(file_info['path'])
total_size -= file_info['size']
deleted_count += 1
except Exception as e:
logger.warning(f"Failed to delete cache file: {e}")
if deleted_count > 0:
logger.info(f"Cache cleanup: deleted {deleted_count} files, current size: {total_size / (1024*1024*1024):.2f} GB")
except Exception as e:
logger.warning(f"Cache cleanup error: {e}")
def clear(self) -> None:
"""清空所有缓存"""
if not self.enabled:
return
try:
if os.path.exists(self.cache_dir):
shutil.rmtree(self.cache_dir)
os.makedirs(self.cache_dir, exist_ok=True)
logger.info("Cache cleared")
except Exception as e:
logger.error(f"Failed to clear cache: {e}")
def get_stats(self) -> dict:
"""
获取缓存统计信息
Returns:
包含缓存统计的字典
"""
if not self.enabled or not os.path.exists(self.cache_dir):
return {'enabled': False, 'file_count': 0, 'total_size_mb': 0}
file_count = 0
total_size = 0
for filename in os.listdir(self.cache_dir):
if filename.endswith('.downloading'):
continue
file_path = os.path.join(self.cache_dir, filename)
if os.path.isfile(file_path):
file_count += 1
total_size += os.path.getsize(file_path)
return {
'enabled': True,
'cache_dir': self.cache_dir,
'file_count': file_count,
'total_size_mb': round(total_size / (1024 * 1024), 2),
'max_size_gb': self.max_size_bytes / (1024 * 1024 * 1024) if self.max_size_bytes > 0 else 0
}

View File

@@ -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']}]"