75 lines
3.0 KiB
Python
75 lines
3.0 KiB
Python
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from pydantic import BaseModel, Field
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from typing import Optional, List
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# ===================================================================
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# 基础模型 (Base Models)
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# ===================================================================
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class UserInfo(BaseModel):
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"""用户的基本信息"""
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id: int = Field(..., description="用户的唯一ID", example=1001)
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name: str = Field(..., description="用户的姓名", example="张三")
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registered_faces_count: int = Field(..., description="该用户已注册的人脸数量", example=2)
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class FaceLocation(BaseModel):
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"""人脸在图片中的位置和尺寸"""
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x: int = Field(..., description="人脸框左上角的X坐标")
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y: int = Field(..., description="人脸框左上角的Y坐标")
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width: int = Field(..., description="人脸框的宽度")
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height: int = Field(..., description="人脸框的高度")
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# ===================================================================
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# API 请求模型 (Request Models)
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# ===================================================================
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class ImageSource(BaseModel):
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"""图片来源，可以是URL或Base64编码的数据"""
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url: Optional[str] = Field(None, description="图片的URL地址", example="http://example.com/image.jpg")
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face_data: Optional[str] = Field(None, description="图片的Base64编码字符串")
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class RegisterRequest(ImageSource):
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"""注册新用户的请求体"""
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id: int = Field(..., description="要注册用户的唯一ID", example=1001)
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name: str = Field(..., description="要注册用户的姓名", example="张三")
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class VerifyRequest(ImageSource):
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"""1:1人脸认证的请求体"""
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id: int = Field(..., description="要验证的用户ID", example=1001)
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# ===================================================================
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# API 响应模型 (Response Models)
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# ===================================================================
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class StandardResponse(BaseModel):
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"""标准API响应模型"""
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code: int = Field(0, description="响应码，0为成功，非0为失败", example=0)
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message: str = Field("success", description="响应消息", example="操作成功")
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data: Optional[dict] = None
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class UserListResponse(StandardResponse):
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"""获取用户列表的响应"""
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data: List[UserInfo]
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class RegisterResponse(StandardResponse):
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"""注册成功后的响应"""
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data: UserInfo
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class VerificationResult(BaseModel):
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"""1:1认证结果"""
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match: bool = Field(..., description="是否匹配")
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confidence: float = Field(..., description="置信度 (0.0 to 1.0)")
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class VerifyResponse(StandardResponse):
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"""1:1人脸认证的响应"""
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data: VerificationResult
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class DetectedFace(UserInfo):
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"""1:N识别结果中的单个人脸信息"""
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location: FaceLocation
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confidence: float = Field(..., description="识别的置信度")
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class DetectResponse(StandardResponse):
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"""1:N人脸识别的响应"""
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data: List[DetectedFace]
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