"""Metric Refinement schemas (Component F09)."""

from typing import Optional

import numpy as np
from pydantic import BaseModel

from gps_denied.schemas import GPSPoint


class AlignmentResult(BaseModel):
    """Result of aligning a UAV image to a single satellite tile."""
    model_config = {"arbitrary_types_allowed": True}

    matched: bool
    homography: np.ndarray  # (3, 3)
    gps_center: GPSPoint
    confidence: float
    inlier_count: int
    total_correspondences: int
    reprojection_error: float  # Mean error in pixels


class Sim3Transform(BaseModel):
    """Sim(3) transformation: scale, rotation, translation."""
    model_config = {"arbitrary_types_allowed": True}

    translation: np.ndarray  # (3,)
    rotation: np.ndarray  # (3, 3) rotation matrix
    scale: float


class ChunkAlignmentResult(BaseModel):
    """Result of aligning a chunk array of UAV images to a satellite tile."""
    model_config = {"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


class LiteSAMConfig(BaseModel):
    """Configuration for LiteSAM alignment."""
    model_path: str = "mock_path"
    confidence_threshold: float = 0.7
    min_inliers: int = 15
    max_reprojection_error: float = 2.0  # pixels
    multi_scale_levels: int = 3
    chunk_min_inliers: int = 30