initial structure implemented

docs -> _docs

models/core/__init__.py

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+from .gps_point import GPSPoint
+from .camera_parameters import CameraParameters
+from .pose import Pose
+from .polygon import Polygon
+from .validation_result import ValidationResult
+
+__all__ = [
+    "GPSPoint",
+    "CameraParameters",
+    "Pose",
+    "Polygon",
+    "ValidationResult",
+]
+

models/core/camera_parameters.py

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+from typing import Optional
+from pydantic import BaseModel
+
+
+class CameraParameters(BaseModel):
+    focal_length: float
+    sensor_width: float
+    sensor_height: float
+    resolution_width: int
+    resolution_height: int
+    principal_point: tuple[float, float] | None = None
+    distortion_coefficients: list[float] | None = None
+
+    def get_principal_point(self) -> tuple[float, float]:
+        if self.principal_point:
+            return self.principal_point
+        return (self.resolution_width / 2.0, self.resolution_height / 2.0)
+

models/core/gps_point.py

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+from pydantic import BaseModel, field_validator
+
+
+class GPSPoint(BaseModel):
+    lat: float
+    lon: float
+
+    @field_validator("lat")
+    @classmethod
+    def validate_lat(cls, v: float) -> float:
+        if not -90 <= v <= 90:
+            raise ValueError("Latitude must be between -90 and 90")
+        return v
+
+    @field_validator("lon")
+    @classmethod
+    def validate_lon(cls, v: float) -> float:
+        if not -180 <= v <= 180:
+            raise ValueError("Longitude must be between -180 and 180")
+        return v
+

models/core/polygon.py

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+from pydantic import BaseModel
+from .gps_point import GPSPoint
+
+
+class Polygon(BaseModel):
+    north_west: GPSPoint
+    south_east: GPSPoint
+

models/core/pose.py

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+from datetime import datetime
+from typing import Optional
+import numpy as np
+from pydantic import BaseModel, ConfigDict
+
+
+class Pose(BaseModel):
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+    frame_id: int
+    position: np.ndarray
+    orientation: np.ndarray
+    timestamp: datetime
+    covariance: Optional[np.ndarray] = None
+

models/core/validation_result.py

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+from pydantic import BaseModel
+
+
+class ValidationResult(BaseModel):
+    valid: bool
+    errors: list[str] = []
+