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>
43 lines
860 B
Python
43 lines
860 B
Python
from typing import List, Optional
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from pydantic import BaseModel # pydantic v1
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class DefectBoxSchema(BaseModel):
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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
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box_xyxy: List[float]
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class DetectResponse(BaseModel):
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task_id: str
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verdict: str # pass | fail
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defect_count: int
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max_severity: str
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avg_confidence: float
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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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defects: List[DefectBoxSchema]
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annotated_image_base64: Optional[str] = None
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class ReloadRequest(BaseModel):
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model_path: str
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runtime: str = "ultralytics"
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class ReloadResponse(BaseModel):
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status: str
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model_version: str
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class HealthResponse(BaseModel):
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status: str
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model_version: str
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runtime: str
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device: str
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