Add existing to tracked

@sideCards/tools/.venv/lib/python3.9/site-packages/cv2/mcc/__init__.pyi

@@ -0,0 +1,118 @@
+__all__: list[str] = []
+
+import cv2
+import cv2.dnn
+import cv2.typing
+import typing as _typing
+
+
+# Enumerations
+MCC24: int
+SG140: int
+VINYL18: int
+ColorChart = int
+"""One of [MCC24, SG140, VINYL18]"""
+
+
+
+# Classes
+class CChecker(cv2.Algorithm):
+    # Functions
+    @classmethod
+    def create(cls) -> CChecker: ...
+
+    def setTarget(self, _target: ColorChart) -> None: ...
+
+    def setBox(self, _box: _typing.Sequence[cv2.typing.Point2f]) -> None: ...
+
+    def setChartsRGB(self, _chartsRGB: cv2.typing.MatLike) -> None: ...
+
+    def setChartsYCbCr(self, _chartsYCbCr: cv2.typing.MatLike) -> None: ...
+
+    def setCost(self, _cost: float) -> None: ...
+
+    def setCenter(self, _center: cv2.typing.Point2f) -> None: ...
+
+    def getTarget(self) -> ColorChart: ...
+
+    def getBox(self) -> _typing.Sequence[cv2.typing.Point2f]: ...
+
+    def getColorCharts(self) -> _typing.Sequence[cv2.typing.Point2f]: ...
+
+    def getChartsRGB(self, getStats: bool = ...) -> cv2.typing.MatLike: ...
+
+    def getChartsYCbCr(self) -> cv2.typing.MatLike: ...
+
+    def getCost(self) -> float: ...
+
+    def getCenter(self) -> cv2.typing.Point2f: ...
+
+
+class DetectorParametersMCC:
+    adaptiveThreshWinSizeMin: int
+    adaptiveThreshWinSizeMax: int
+    adaptiveThreshWinSizeStep: int
+    adaptiveThreshConstant: float
+    minContoursAreaRate: float
+    minContoursArea: float
+    confidenceThreshold: float
+    minContourSolidity: float
+    findCandidatesApproxPolyDPEpsMultiplier: float
+    borderWidth: int
+    B0factor: float
+    maxError: float
+    minContourPointsAllowed: int
+    minContourLengthAllowed: int
+    minInterContourDistance: int
+    minInterCheckerDistance: int
+    minImageSize: int
+    minGroupSize: int
+
+    # Functions
+    def __init__(self) -> None: ...
+
+
+class CCheckerDetector(cv2.Algorithm):
+    # Functions
+    @_typing.overload
+    def processWithROI(self, image: cv2.typing.MatLike, regionsOfInterest: _typing.Sequence[cv2.typing.Rect], nc: int = ...) -> bool: ...
+    @_typing.overload
+    def processWithROI(self, image: cv2.UMat, regionsOfInterest: _typing.Sequence[cv2.typing.Rect], nc: int = ...) -> bool: ...
+
+    @_typing.overload
+    def process(self, image: cv2.typing.MatLike, nc: int = ...) -> bool: ...
+    @_typing.overload
+    def process(self, image: cv2.UMat, nc: int = ...) -> bool: ...
+
+    def getBestColorChecker(self) -> CChecker: ...
+
+    def getListColorChecker(self) -> _typing.Sequence[CChecker]: ...
+
+    @classmethod
+    @_typing.overload
+    def create(cls) -> CCheckerDetector: ...
+    @classmethod
+    @_typing.overload
+    def create(cls, net: cv2.dnn.Net) -> CCheckerDetector: ...
+
+    @_typing.overload
+    def draw(self, checkers: _typing.Sequence[CChecker], img: cv2.typing.MatLike, color: cv2.typing.Scalar = ..., thickness: int = ...) -> cv2.typing.MatLike: ...
+    @_typing.overload
+    def draw(self, checkers: _typing.Sequence[CChecker], img: cv2.UMat, color: cv2.typing.Scalar = ..., thickness: int = ...) -> cv2.UMat: ...
+
+    def getRefColors(self) -> cv2.typing.MatLike: ...
+
+    def setDetectionParams(self, params: DetectorParametersMCC) -> None: ...
+
+    def setColorChartType(self, chartType: ColorChart) -> None: ...
+
+    def setUseDnnModel(self, useDnn: bool) -> None: ...
+
+    def getUseDnnModel(self) -> bool: ...
+
+    def getDetectionParams(self) -> DetectorParametersMCC: ...
+
+    def getColorChartType(self) -> ColorChart: ...
+
+
+