initial structure implemented

docs -> _docs

helpers/__init__.py

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+from .camera_model import CameraModel
+from .gsd_calculator import GSDCalculator
+from .robust_kernels import RobustKernels
+from .faiss_index_manager import FaissIndexManager
+from .performance_monitor import PerformanceMonitor
+from .web_mercator_utils import WebMercatorUtils
+from .image_rotation_utils import ImageRotationUtils
+from .batch_validator import BatchValidator
+
+__all__ = [
+    "CameraModel",
+    "GSDCalculator",
+    "RobustKernels",
+    "FaissIndexManager",
+    "PerformanceMonitor",
+    "WebMercatorUtils",
+    "ImageRotationUtils",
+    "BatchValidator",
+]
+

helpers/batch_validator.py

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+from typing import Optional
+import numpy as np
+
+from models.core import ValidationResult
+from models.images import ImageBatch
+
+
+class BatchValidator:
+    @staticmethod
+    def validate_batch(batch: ImageBatch) -> ValidationResult:
+        raise NotImplementedError
+
+    @staticmethod
+    def validate_image_format(image_bytes: bytes) -> ValidationResult:
+        raise NotImplementedError
+
+    @staticmethod
+    def validate_sequence_continuity(
+        current_batch: ImageBatch,
+        expected_start: int,
+    ) -> ValidationResult:
+        raise NotImplementedError
+
+    @staticmethod
+    def validate_image_dimensions(
+        image: np.ndarray,
+        expected_width: int,
+        expected_height: int,
+    ) -> ValidationResult:
+        raise NotImplementedError
+
+    @staticmethod
+    def validate_batch_size(
+        batch: ImageBatch,
+        max_size: int = 100,
+    ) -> ValidationResult:
+        raise NotImplementedError
+

helpers/camera_model.py

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+import numpy as np
+
+from models.core import CameraParameters
+
+
+class CameraModel:
+    def __init__(self, params: CameraParameters):
+        self._params = params
+        self._K: np.ndarray | None = None
+
+    @property
+    def intrinsic_matrix(self) -> np.ndarray:
+        if self._K is None:
+            fx = self._params.focal_length * self._params.resolution_width / self._params.sensor_width
+            fy = self._params.focal_length * self._params.resolution_height / self._params.sensor_height
+            cx, cy = self._params.get_principal_point()
+            self._K = np.array([
+                [fx, 0, cx],
+                [0, fy, cy],
+                [0, 0, 1]
+            ], dtype=np.float64)
+        return self._K
+
+    def project(self, points_3d: np.ndarray) -> np.ndarray:
+        raise NotImplementedError
+
+    def unproject(self, points_2d: np.ndarray, depth: float) -> np.ndarray:
+        raise NotImplementedError
+
+    def undistort_points(self, points: np.ndarray) -> np.ndarray:
+        raise NotImplementedError
+
+    def get_fov(self) -> tuple[float, float]:
+        raise NotImplementedError
+

helpers/faiss_index_manager.py

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+from typing import Optional
+import numpy as np
+
+
+class FaissIndexManager:
+    def __init__(self, dimension: int, index_type: str = "IVF"):
+        self._dimension = dimension
+        self._index_type = index_type
+        self._index = None
+        self._id_map: dict[int, str] = {}
+
+    def build_index(self, vectors: np.ndarray, ids: list[str]) -> bool:
+        raise NotImplementedError
+
+    def add_vectors(self, vectors: np.ndarray, ids: list[str]) -> bool:
+        raise NotImplementedError
+
+    def search(
+        self, query: np.ndarray, top_k: int = 10
+    ) -> list[tuple[str, float]]:
+        raise NotImplementedError
+
+    def remove_vectors(self, ids: list[str]) -> bool:
+        raise NotImplementedError
+
+    def save_index(self, path: str) -> bool:
+        raise NotImplementedError
+
+    def load_index(self, path: str) -> bool:
+        raise NotImplementedError
+
+    def get_vector_count(self) -> int:
+        raise NotImplementedError
+

helpers/gsd_calculator.py

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+from models.core import CameraParameters
+
+
+class GSDCalculator:
+    @staticmethod
+    def calculate_gsd(
+        altitude: float,
+        focal_length: float,
+        sensor_width: float,
+        image_width: int,
+    ) -> float:
+        raise NotImplementedError
+
+    @staticmethod
+    def calculate_footprint(
+        altitude: float,
+        camera_params: CameraParameters,
+    ) -> tuple[float, float]:
+        raise NotImplementedError
+
+    @staticmethod
+    def altitude_for_gsd(
+        target_gsd: float,
+        focal_length: float,
+        sensor_width: float,
+        image_width: int,
+    ) -> float:
+        raise NotImplementedError
+
+    @staticmethod
+    def calculate_coverage_radius(
+        altitude: float,
+        camera_params: CameraParameters,
+    ) -> float:
+        raise NotImplementedError
+

helpers/image_rotation_utils.py

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+import numpy as np
+
+
+class ImageRotationUtils:
+    @staticmethod
+    def rotate_image(
+        image: np.ndarray,
+        angle: float,
+        center: tuple[float, float] | None = None,
+    ) -> np.ndarray:
+        raise NotImplementedError
+
+    @staticmethod
+    def get_rotation_matrix(
+        angle: float,
+        center: tuple[float, float],
+    ) -> np.ndarray:
+        raise NotImplementedError
+
+    @staticmethod
+    def rotate_points(
+        points: np.ndarray,
+        angle: float,
+        center: tuple[float, float],
+    ) -> np.ndarray:
+        raise NotImplementedError
+
+    @staticmethod
+    def normalize_angle(angle: float) -> float:
+        raise NotImplementedError
+
+    @staticmethod
+    def angle_difference(angle1: float, angle2: float) -> float:
+        raise NotImplementedError
+
+    @staticmethod
+    def interpolate_angles(
+        angles: list[float],
+        weights: list[float] | None = None,
+    ) -> float:
+        raise NotImplementedError
+

helpers/performance_monitor.py

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+import time
+from typing import Optional
+from contextlib import contextmanager
+
+
+class PerformanceMonitor:
+    def __init__(self):
+        self._timings: dict[str, list[float]] = {}
+        self._counters: dict[str, int] = {}
+
+    @contextmanager
+    def measure(self, operation: str):
+        start = time.perf_counter()
+        try:
+            yield
+        finally:
+            elapsed = time.perf_counter() - start
+            if operation not in self._timings:
+                self._timings[operation] = []
+            self._timings[operation].append(elapsed)
+
+    def increment(self, counter: str, value: int = 1) -> None:
+        if counter not in self._counters:
+            self._counters[counter] = 0
+        self._counters[counter] += value
+
+    def get_average(self, operation: str) -> Optional[float]:
+        if operation not in self._timings or not self._timings[operation]:
+            return None
+        return sum(self._timings[operation]) / len(self._timings[operation])
+
+    def get_statistics(self, operation: str) -> Optional[dict]:
+        raise NotImplementedError
+
+    def get_counter(self, counter: str) -> int:
+        return self._counters.get(counter, 0)
+
+    def reset(self) -> None:
+        self._timings.clear()
+        self._counters.clear()
+
+    def get_report(self) -> dict:
+        raise NotImplementedError
+

helpers/robust_kernels.py

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+import numpy as np
+
+
+class RobustKernels:
+    @staticmethod
+    def huber(residual: float, delta: float = 1.0) -> float:
+        raise NotImplementedError
+
+    @staticmethod
+    def cauchy(residual: float, c: float = 1.0) -> float:
+        raise NotImplementedError
+
+    @staticmethod
+    def tukey(residual: float, c: float = 4.685) -> float:
+        raise NotImplementedError
+
+    @staticmethod
+    def huber_weight(residual: float, delta: float = 1.0) -> float:
+        raise NotImplementedError
+
+    @staticmethod
+    def cauchy_weight(residual: float, c: float = 1.0) -> float:
+        raise NotImplementedError
+
+    @staticmethod
+    def compute_robust_covariance(
+        residuals: np.ndarray,
+        kernel: str = "huber",
+        **kwargs,
+    ) -> np.ndarray:
+        raise NotImplementedError
+

helpers/web_mercator_utils.py

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+import math
+
+from models.core import GPSPoint
+from models.satellite import TileCoords, TileBounds
+
+
+class WebMercatorUtils:
+    EARTH_RADIUS = 6378137.0
+    TILE_SIZE = 256
+
+    @classmethod
+    def gps_to_tile(cls, gps: GPSPoint, zoom: int) -> TileCoords:
+        raise NotImplementedError
+
+    @classmethod
+    def tile_to_gps(cls, coords: TileCoords) -> GPSPoint:
+        raise NotImplementedError
+
+    @classmethod
+    def get_tile_bounds(cls, coords: TileCoords) -> TileBounds:
+        raise NotImplementedError
+
+    @classmethod
+    def gps_to_pixel(
+        cls, gps: GPSPoint, zoom: int
+    ) -> tuple[float, float]:
+        raise NotImplementedError
+
+    @classmethod
+    def pixel_to_gps(
+        cls, pixel: tuple[float, float], zoom: int
+    ) -> GPSPoint:
+        raise NotImplementedError
+
+    @classmethod
+    def meters_per_pixel(cls, lat: float, zoom: int) -> float:
+        raise NotImplementedError
+
+    @classmethod
+    def get_tiles_in_bounds(
+        cls, nw: GPSPoint, se: GPSPoint, zoom: int
+    ) -> list[TileCoords]:
+        raise NotImplementedError
+