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>
57 lines
1.7 KiB
Python
57 lines
1.7 KiB
Python
import uuid
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import cv2
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import numpy as np
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from fastapi import APIRouter, File, Form, HTTPException, UploadFile
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from engine.loader import get_engine, get_inference_lock
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from engine.annotator import annotate, to_base64
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from schema import DefectBoxSchema, DetectResponse
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router = APIRouter()
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@router.post("/detect", response_model=DetectResponse)
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async def detect(
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image: UploadFile = File(...),
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conf: float = Form(0.45),
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return_annotated: bool = Form(False),
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):
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raw = await image.read()
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arr = np.frombuffer(raw, dtype=np.uint8)
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img = cv2.imdecode(arr, cv2.IMREAD_COLOR)
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if img is None:
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raise HTTPException(status_code=400, detail="无法解码图像，请检查文件格式")
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engine = get_engine()
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async with get_inference_lock():
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result = engine.detect(img, conf=conf)
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annotated_b64 = None
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if return_annotated:
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annotated_b64 = to_base64(annotate(img, result))
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return DetectResponse(
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task_id=str(uuid.uuid4()),
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verdict=result.verdict,
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defect_count=result.defect_count,
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max_severity=result.max_severity,
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avg_confidence=result.avg_confidence,
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duration_ms=result.duration_ms,
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image_width=result.image_width,
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image_height=result.image_height,
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model_version=result.model_version,
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defects=[
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DefectBoxSchema(
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class_id=d.class_id,
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class_name=d.class_name,
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class_name_zh=d.class_name_zh,
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confidence=d.confidence,
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severity=d.severity,
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box_xyxy=d.box_xyxy,
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)
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for d in result.defects
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],
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annotated_image_base64=annotated_b64,
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)
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