102 lines
3.6 KiB
Python
102 lines
3.6 KiB
Python
#!/usr/bin/env python3
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"""
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视频拆分服务命令行接口
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"""
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from typing import Dict, Any
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from dataclasses import asdict
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from .types import DetectionConfig, DetectorType
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from .service import VideoSplitterService
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from python_core.utils.commander import JSONRPCCommander
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class VideoSplitterCommander(JSONRPCCommander):
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"""视频拆分服务命令行接口"""
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def __init__(self):
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self.service = None
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super().__init__("video_splitter")
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def _register_commands(self) -> None:
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"""注册命令"""
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# 注册analyze命令
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self.register_command(
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name="analyze",
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description="分析视频场景",
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required_args=["video_path"],
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optional_args={
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"threshold": {"type": float, "default": 30.0, "description": "检测阈值"},
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"detector": {"type": str, "default": "content", "choices": ["content", "threshold"], "description": "检测器类型"},
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"min-scene-length": {"type": float, "default": 1.0, "description": "最小场景长度（秒）"},
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"output-base": {"type": str, "default": None, "description": "输出基础目录"}
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}
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)
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# 注册detect_scenes命令
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self.register_command(
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name="detect_scenes",
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description="检测视频场景（仅返回场景信息）",
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required_args=["video_path"],
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optional_args={
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"threshold": {"type": float, "default": 30.0, "description": "检测阈值"},
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"detector": {"type": str, "default": "content", "choices": ["content", "threshold"], "description": "检测器类型"},
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"min-scene-length": {"type": float, "default": 1.0, "description": "最小场景长度（秒）"},
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"output-base": {"type": str, "default": None, "description": "输出基础目录"}
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}
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)
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def _setup_service(self, output_base: str = None) -> None:
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"""设置服务"""
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if self.service is None:
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self.service = VideoSplitterService(output_base_dir=output_base)
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def execute_command(self, command: str, args: Dict[str, Any]) -> Any:
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"""执行命令"""
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# 设置服务
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self._setup_service(args.get("output_base"))
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# 创建配置
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config = DetectionConfig(
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threshold=args.get("threshold", 30.0),
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detector_type=DetectorType(args.get("detector", "content")),
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min_scene_length=args.get("min_scene_length", 1.0)
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)
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video_path = args["video_path"]
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if command == "analyze":
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# 完整的视频分析
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result = self.service.analyze_video(video_path, config)
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return result.to_dict()
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elif command == "detect_scenes":
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# 仅检测场景
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result = self.service.analyze_video(video_path, config)
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# 只返回场景信息
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scenes_result = {
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"success": result.success,
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"video_path": result.video_path,
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"total_scenes": result.total_scenes,
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"scenes": [asdict(scene) for scene in result.scenes],
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"detection_settings": asdict(config),
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"detection_time": result.analysis_time
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}
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if not result.success:
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scenes_result["error"] = result.error
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return scenes_result
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else:
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raise ValueError(f"Unknown command: {command}")
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def main():
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"""主函数"""
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commander = VideoSplitterCommander()
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commander.run()
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if __name__ == "__main__":
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main()
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