2025-08-11 12:24:21 +08:00

143 lines
5.4 KiB
Python

__all__: list[str] = []
import cv2
import cv2.typing
import typing as _typing
# Enumerations
HAAR: int
TransformTypes = int
"""One of [HAAR]"""
BM3D_STEPALL: int
BM3D_STEP1: int
BM3D_STEP2: int
Bm3dSteps = int
"""One of [BM3D_STEPALL, BM3D_STEP1, BM3D_STEP2]"""
INPAINT_SHIFTMAP: int
INPAINT_FSR_BEST: int
INPAINT_FSR_FAST: int
InpaintTypes = int
"""One of [INPAINT_SHIFTMAP, INPAINT_FSR_BEST, INPAINT_FSR_FAST]"""
# Classes
class TonemapDurand(cv2.Tonemap):
# Functions
def getSaturation(self) -> float: ...
def setSaturation(self, saturation: float) -> None: ...
def getContrast(self) -> float: ...
def setContrast(self, contrast: float) -> None: ...
def getSigmaSpace(self) -> float: ...
def setSigmaSpace(self, sigma_space: float) -> None: ...
def getSigmaColor(self) -> float: ...
def setSigmaColor(self, sigma_color: float) -> None: ...
class WhiteBalancer(cv2.Algorithm):
# Functions
@_typing.overload
def balanceWhite(self, src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def balanceWhite(self, src: cv2.UMat, dst: cv2.UMat | None = ...) -> cv2.UMat: ...
class SimpleWB(WhiteBalancer):
# Functions
def getInputMin(self) -> float: ...
def setInputMin(self, val: float) -> None: ...
def getInputMax(self) -> float: ...
def setInputMax(self, val: float) -> None: ...
def getOutputMin(self) -> float: ...
def setOutputMin(self, val: float) -> None: ...
def getOutputMax(self) -> float: ...
def setOutputMax(self, val: float) -> None: ...
def getP(self) -> float: ...
def setP(self, val: float) -> None: ...
class GrayworldWB(WhiteBalancer):
# Functions
def getSaturationThreshold(self) -> float: ...
def setSaturationThreshold(self, val: float) -> None: ...
class LearningBasedWB(WhiteBalancer):
# Functions
@_typing.overload
def extractSimpleFeatures(self, src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def extractSimpleFeatures(self, src: cv2.UMat, dst: cv2.UMat | None = ...) -> cv2.UMat: ...
def getRangeMaxVal(self) -> int: ...
def setRangeMaxVal(self, val: int) -> None: ...
def getSaturationThreshold(self) -> float: ...
def setSaturationThreshold(self, val: float) -> None: ...
def getHistBinNum(self) -> int: ...
def setHistBinNum(self, val: int) -> None: ...
# Functions
@_typing.overload
def applyChannelGains(src: cv2.typing.MatLike, gainB: float, gainG: float, gainR: float, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def applyChannelGains(src: cv2.UMat, gainB: float, gainG: float, gainR: float, dst: cv2.UMat | None = ...) -> cv2.UMat: ...
@_typing.overload
def bm3dDenoising(src: cv2.typing.MatLike, dstStep1: cv2.typing.MatLike, dstStep2: cv2.typing.MatLike | None = ..., h: float = ..., templateWindowSize: int = ..., searchWindowSize: int = ..., blockMatchingStep1: int = ..., blockMatchingStep2: int = ..., groupSize: int = ..., slidingStep: int = ..., beta: float = ..., normType: int = ..., step: int = ..., transformType: int = ...) -> tuple[cv2.typing.MatLike, cv2.typing.MatLike]: ...
@_typing.overload
def bm3dDenoising(src: cv2.UMat, dstStep1: cv2.UMat, dstStep2: cv2.UMat | None = ..., h: float = ..., templateWindowSize: int = ..., searchWindowSize: int = ..., blockMatchingStep1: int = ..., blockMatchingStep2: int = ..., groupSize: int = ..., slidingStep: int = ..., beta: float = ..., normType: int = ..., step: int = ..., transformType: int = ...) -> tuple[cv2.UMat, cv2.UMat]: ...
@_typing.overload
def bm3dDenoising(src: cv2.typing.MatLike, dst: cv2.typing.MatLike | None = ..., h: float = ..., templateWindowSize: int = ..., searchWindowSize: int = ..., blockMatchingStep1: int = ..., blockMatchingStep2: int = ..., groupSize: int = ..., slidingStep: int = ..., beta: float = ..., normType: int = ..., step: int = ..., transformType: int = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def bm3dDenoising(src: cv2.UMat, dst: cv2.UMat | None = ..., h: float = ..., templateWindowSize: int = ..., searchWindowSize: int = ..., blockMatchingStep1: int = ..., blockMatchingStep2: int = ..., groupSize: int = ..., slidingStep: int = ..., beta: float = ..., normType: int = ..., step: int = ..., transformType: int = ...) -> cv2.UMat: ...
def createGrayworldWB() -> GrayworldWB: ...
def createLearningBasedWB(path_to_model: str = ...) -> LearningBasedWB: ...
def createSimpleWB() -> SimpleWB: ...
def createTonemapDurand(gamma: float = ..., contrast: float = ..., saturation: float = ..., sigma_color: float = ..., sigma_space: float = ...) -> TonemapDurand: ...
def dctDenoising(src: cv2.typing.MatLike, dst: cv2.typing.MatLike, sigma: float, psize: int = ...) -> None: ...
def inpaint(src: cv2.typing.MatLike, mask: cv2.typing.MatLike, dst: cv2.typing.MatLike, algorithmType: int) -> None: ...
@_typing.overload
def oilPainting(src: cv2.typing.MatLike, size: int, dynRatio: int, code: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def oilPainting(src: cv2.UMat, size: int, dynRatio: int, code: int, dst: cv2.UMat | None = ...) -> cv2.UMat: ...
@_typing.overload
def oilPainting(src: cv2.typing.MatLike, size: int, dynRatio: int, dst: cv2.typing.MatLike | None = ...) -> cv2.typing.MatLike: ...
@_typing.overload
def oilPainting(src: cv2.UMat, size: int, dynRatio: int, dst: cv2.UMat | None = ...) -> cv2.UMat: ...