initial structure implemented

docs -> _docs

models/processing/__init__.py

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+from .relative_pose import RelativePose
+from .motion import Motion
+from .matches import Matches
+from .alignment_result import AlignmentResult, ChunkAlignmentResult
+from .rotation_result import RotationResult
+
+__all__ = [
+    "RelativePose",
+    "Motion",
+    "Matches",
+    "AlignmentResult",
+    "ChunkAlignmentResult",
+    "RotationResult",
+]
+

models/processing/alignment_result.py

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+import numpy as np
+from pydantic import BaseModel, ConfigDict
+from ..core.gps_point import GPSPoint
+from ..chunks.sim3_transform import Sim3Transform
+
+
+class AlignmentResult(BaseModel):
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+    matched: bool
+    homography: np.ndarray
+    gps_center: GPSPoint
+    confidence: float
+    inlier_count: int
+    total_correspondences: int
+    reprojection_error: float = 0.0
+
+
+class ChunkAlignmentResult(BaseModel):
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+    matched: bool
+    chunk_id: str
+    chunk_center_gps: GPSPoint
+    rotation_angle: float
+    confidence: float
+    inlier_count: int
+    transform: Sim3Transform
+    reprojection_error: float = 0.0
+

models/processing/matches.py

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+import numpy as np
+from pydantic import BaseModel, ConfigDict
+
+
+class Matches(BaseModel):
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+    matches: np.ndarray
+    scores: np.ndarray
+    keypoints1: np.ndarray
+    keypoints2: np.ndarray
+

models/processing/motion.py

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+import numpy as np
+from pydantic import BaseModel, ConfigDict
+
+
+class Motion(BaseModel):
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+    translation: np.ndarray
+    rotation: np.ndarray
+    inliers: np.ndarray
+    inlier_count: int
+

models/processing/relative_pose.py

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+from typing import Optional
+import numpy as np
+from pydantic import BaseModel, ConfigDict
+
+
+class RelativePose(BaseModel):
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+    translation: np.ndarray
+    rotation: np.ndarray
+    confidence: float
+    inlier_count: int
+    total_matches: int
+    tracking_good: bool
+    scale_ambiguous: bool = True
+    chunk_id: Optional[str] = None
+

models/processing/rotation_result.py

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+import numpy as np
+from pydantic import BaseModel, ConfigDict
+
+
+class RotationResult(BaseModel):
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+    matched: bool
+    initial_angle: float
+    precise_angle: float
+    confidence: float
+    homography: np.ndarray
+    inlier_count: int = 0
+