ilaandClaude Sonnet 4.6
68e4f444c5
- engine/defect_classes: HRIPCB 6类缺陷定义 + 4类扩展 + severity排序 - engine/base: DefectBox / DetectResult 数据类 + BaseInferenceEngine 抽象基类 - engine/ultralytics_adapter: YOLOv8 .pt 推理适配器 + warmup - engine/annotator: 按 severity 着色的标注图生成 + base64 编码 - engine/loader: 单例管理 + asyncio.Lock 推理串行化 + 热重载支持 - config: Pydantic v1 BaseSettings，读取 .env - schema: DetectResponse / HealthResponse / ReloadRequest 等响应模型 - api/detect: POST /api/detect，内存读图，推理锁保护 - api/health: GET /api/health - api/model: POST /api/model/reload 热重载接口 - main: FastAPI lifespan 启动加载模型 测试通过：/api/health 200，/api/detect 空图返回 pass，标注图 base64 正常 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
60 lines
1.3 KiB
Python
60 lines
1.3 KiB
Python
from abc import ABC, abstractmethod
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from dataclasses import dataclass
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from typing import List
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import numpy as np
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from .defect_classes import max_severity
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@dataclass
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class DefectBox:
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class_id: int
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class_name: str
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class_name_zh: str
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confidence: float
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severity: str # fatal / major / minor / rework / none
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box_xyxy: List[float]
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@dataclass
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class DetectResult:
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defects: List[DefectBox]
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duration_ms: float
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image_width: int
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image_height: int
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model_version: str
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@property
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def defect_count(self) -> int:
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return len(self.defects)
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@property
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def max_severity(self) -> str:
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return max_severity([d.severity for d in self.defects]) if self.defects else "none"
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@property
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def avg_confidence(self) -> float:
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if not self.defects:
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return 0.0
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return round(sum(d.confidence for d in self.defects) / len(self.defects), 4)
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@property
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def verdict(self) -> str:
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return "fail" if self.defects else "pass"
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class BaseInferenceEngine(ABC):
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@abstractmethod
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def detect(self, image: np.ndarray, conf: float = 0.45) -> DetectResult:
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...
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@abstractmethod
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def warmup(self) -> None:
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...
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@property
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@abstractmethod
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def model_version(self) -> str:
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...
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