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object --+ | ??.instance --+ | CascadeClassifier
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Inherited from Inherited from |
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BOOST = 0
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DO_CANNY_PRUNING = 1
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DO_ROUGH_SEARCH = 8
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FIND_BIGGEST_OBJECT = 4
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SCALE_IMAGE = 2
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__instance_size__ = 292
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classifiers | |||
featureType | |||
feval | |||
is_stump_based | |||
leaves | |||
ncategories | |||
nodes | |||
oldCascade | |||
origWinSize | |||
stageType | |||
stages | |||
subsets | |||
this | |||
Inherited from |
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__init__( (object)arg1) -> None : C++ signature : void __init__(_object*) __init__( (object)arg1, (object)filename) -> None : C++ signature : void __init__(_object*,std::string)
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helper for pickle
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detectMultiScale( (CascadeClassifier)inst, (Mat)image [, (object)scaleFactor=1.1000000000000001 [, (object)minNeighbors=3 [, (object)flags=0 [, (Size2i)minSize=Size2i(width=0, height=0)]]]]) -> object : Argument 'objects': C/C++ type: ::std::vector< cv::Rect_<int> > &. Python type: Mat. Invoke asMat() to convert a 1D Python sequence into a Mat, e.g. asMat([0,1,2]) or asMat((0,1,2)). Output argument: omitted from the function's calling sequence, and is returned along with the function's return value (if any). C++ signature : boost::python::api::object detectMultiScale(cv::CascadeClassifier {lvalue},cv::Mat [,double=1.1000000000000001 [,int=3 [,int=0 [,cv::Size_<int>=Size2i(width=0, height=0)]]]]) |
empty( (CascadeClassifier)arg1) -> bool : C++ signature : bool empty(cv::CascadeClassifier {lvalue}) |
load( (CascadeClassifier)arg1, (object)filename) -> bool : C++ signature : bool load(cv::CascadeClassifier {lvalue},std::string) |
read( (CascadeClassifier)arg1, (FileNode)node) -> bool : C++ signature : bool read(cv::CascadeClassifier {lvalue},cv::FileNode) |
runAt( (CascadeClassifier)arg1, (Ptr_FeatureEvaluator)_feval, (Point2i)pt) -> int : C++ signature : int runAt(CascadeClassifier_wrapper {lvalue},cv::Ptr<cv::FeatureEvaluator> {lvalue},cv::Point_<int>) |
setImage( (CascadeClassifier)arg1, (Ptr_FeatureEvaluator)_feval, (Mat)image) -> bool : C++ signature : bool setImage(CascadeClassifier_wrapper {lvalue},cv::Ptr<cv::FeatureEvaluator> {lvalue},cv::Mat) |
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classifiers
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featureType
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feval
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is_stump_based
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leaves
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ncategories
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nodes
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oldCascade
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origWinSize
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stageType
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stages
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subsets
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this
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