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5 months ago
__all__: list[str] = []
import cv2
import cv2.typing
import typing as _typing
# Enumerations
FLANN_INDEX_TYPE_8U: int
FLANN_INDEX_TYPE_8S: int
FLANN_INDEX_TYPE_16U: int
FLANN_INDEX_TYPE_16S: int
FLANN_INDEX_TYPE_32S: int
FLANN_INDEX_TYPE_32F: int
FLANN_INDEX_TYPE_64F: int
FLANN_INDEX_TYPE_STRING: int
FLANN_INDEX_TYPE_BOOL: int
FLANN_INDEX_TYPE_ALGORITHM: int
LAST_VALUE_FLANN_INDEX_TYPE: int
FlannIndexType = int
"""One of [FLANN_INDEX_TYPE_8U, FLANN_INDEX_TYPE_8S, FLANN_INDEX_TYPE_16U, FLANN_INDEX_TYPE_16S, FLANN_INDEX_TYPE_32S, FLANN_INDEX_TYPE_32F, FLANN_INDEX_TYPE_64F, FLANN_INDEX_TYPE_STRING, FLANN_INDEX_TYPE_BOOL, FLANN_INDEX_TYPE_ALGORITHM, LAST_VALUE_FLANN_INDEX_TYPE]"""
# Classes
class Index:
# Functions
@_typing.overload
def __init__(self) -> None: ...
@_typing.overload
def __init__(self, features: cv2.typing.MatLike, params: cv2.typing.IndexParams, distType: int = ...) -> None: ...
@_typing.overload
def __init__(self, features: cv2.UMat, params: cv2.typing.IndexParams, distType: int = ...) -> None: ...
@_typing.overload
def build(self, features: cv2.typing.MatLike, params: cv2.typing.IndexParams, distType: int = ...) -> None: ...
@_typing.overload
def build(self, features: cv2.UMat, params: cv2.typing.IndexParams, distType: int = ...) -> None: ...
@_typing.overload
def knnSearch(self, query: cv2.typing.MatLike, knn: int, indices: cv2.typing.MatLike | None = ..., dists: cv2.typing.MatLike | None = ..., params: cv2.typing.SearchParams = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
@_typing.overload
def knnSearch(self, query: cv2.UMat, knn: int, indices: cv2.UMat | None = ..., dists: cv2.UMat | None = ..., params: cv2.typing.SearchParams = ...) -> tuple[cv2.UMat, cv2.UMat]: ...
@_typing.overload
def radiusSearch(self, query: cv2.typing.MatLike, radius: float, maxResults: int, indices: cv2.typing.MatLike | None = ..., dists: cv2.typing.MatLike | None = ..., params: cv2.typing.SearchParams = ...) -> tuple[int, cv2.typing.MatLike, cv2.typing.MatLike]: ...
@_typing.overload
def radiusSearch(self, query: cv2.UMat, radius: float, maxResults: int, indices: cv2.UMat | None = ..., dists: cv2.UMat | None = ..., params: cv2.typing.SearchParams = ...) -> tuple[int, cv2.UMat, cv2.UMat]: ...
def save(self, filename: str) -> None: ...
@_typing.overload
def load(self, features: cv2.typing.MatLike, filename: str) -> bool: ...
@_typing.overload
def load(self, features: cv2.UMat, filename: str) -> bool: ...
def release(self) -> None: ...
def getDistance(self) -> int: ...
def getAlgorithm(self) -> int: ...