智能体加检测

main.py

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+import io
+import os
+import tempfile
+from contextlib import asynccontextmanager
+
+import requests
+import uvicorn
+from PIL import Image
+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel, HttpUrl
+
+from config import DetectionResponse
+from process import detect_large_image_from_url
+
+# 全局检测管理器
+detector_manager = None
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    global detector_manager
+    try:
+        from manager import UnifiedDetectionManager
+        detector_manager = UnifiedDetectionManager()
+        print("检测管理器初始化成功")
+    except Exception as e:
+        print(f"初始化失败：{str(e)}")
+        raise
+    yield
+
+
+app = FastAPI(lifespan=lifespan, title="目标检测API", version="1.0.0")
+
+# 配置跨域请求
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+class DetectionRequest(BaseModel):
+    type: str
+    url: HttpUrl
+
+
+class DetectionProcessRequest(BaseModel):
+    url: HttpUrl
+
+
+@app.post("/detect_image", response_model=DetectionResponse)
+async def run_detection_image(request: DetectionRequest):
+    # 解析检测类型
+    requested_types = {t.strip().lower() for t in request.type.split(',') if t.strip()}
+    print(f"请求的检测类型: {requested_types}")
+    if not requested_types:
+        raise HTTPException(status_code=400, detail="未指定检测类型")
+
+    # 下载图片
+    try:
+        response = requests.get(str(request.url), timeout=15)
+        response.raise_for_status()
+
+        # 获取图片尺寸
+        with Image.open(io.BytesIO(response.content)) as img:
+            img_size = [img.width, img.height]
+
+        # 创建临时文件
+        with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as temp_file:
+            temp_file.write(response.content)
+            temp_path = temp_file.name
+
+    except Exception as e:
+        raise HTTPException(status_code=400, detail=f"图片处理失败：{str(e)}")
+
+    # 执行检测
+    results = []
+    errors = []
+
+    try:
+        detection_results = detector_manager.detect(temp_path, ",".join(requested_types))
+        if detection_results:
+            results = detection_results
+    except Exception as e:
+        errors.append(f"检测失败：{str(e)}")
+    finally:
+        # 清理临时文件
+        if os.path.exists(temp_path):
+            os.remove(temp_path)
+
+    return {
+        "hasTarget": 1 if results else 0,
+        "originalImgSize": img_size,
+        "targets": results,
+        "processing_errors": errors
+    }
+
+
+@app.post("/detect_process", response_model=DetectionResponse)
+async def run_detection_process(request: DetectionProcessRequest):
+    return detect_large_image_from_url(str(request.url))
+
+
+@app.get("/supported_types")
+async def get_supported_types():
+    if detector_manager:
+        info = detector_manager.get_available_info()
+        return {
+            "supported_types": info["supported_types"],
+        }
+    return {"supported_types": []}
+
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--host", default="0.0.0.0")
+    parser.add_argument("--port", type=int, default=8000)
+    parser.add_argument("--reload", action="store_true")
+    args = parser.parse_args()
+    uvicorn.run("main:app", host=args.host, port=args.port, reload=args.reload)