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Issue #2540 : Python bindings for various "detectMultiScale()"

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abidrahmank
2014-05-21 08:26:16 +05:30
parent cafcfc4d0f
commit 31291ced11
2 changed files with 7 additions and 3 deletions
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modules/objdetect/doc/cascade_classification.rst
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@@ -86,9 +86,11 @@ Detects objects of different sizes in the input image. The detected objects are
.. ocv:function:: void CascadeClassifier::detectMultiScale( InputArray image, vector<Rect>& objects, double scaleFactor=1.1, int minNeighbors=3, int flags=0, Size minSize=Size(), Size maxSize=Size())
.. ocv:function:: void CascadeClassifier::detectMultiScale( InputArray image, vector<Rect>& objects, vector<int>& numDetections, double scaleFactor=1.1, int minNeighbors=3, int flags=0, Size minSize=Size(), Size maxSize=Size())
.. ocv:function:: void CascadeClassifier::detectMultiScale( InputArray image, std::vector<Rect>& objects, std::vector<int>& rejectLevels, std::vector<double>& levelWeights, double scaleFactor = 1.1, int minNeighbors = 3, int flags = 0, Size minSize = Size(), Size maxSize = Size(), bool outputRejectLevels = false )
.. ocv:pyfunction:: cv2.CascadeClassifier.detectMultiScale(image[, scaleFactor[, minNeighbors[, flags[, minSize[, maxSize]]]]]) -> objects
.. ocv:pyfunction:: cv2.CascadeClassifier.detectMultiScale(image[, scaleFactor[, minNeighbors[, flags[, minSize[, maxSize[, outputRejectLevels]]]]]]) -> objects, rejectLevels, levelWeights
.. ocv:pyfunction:: cv2.CascadeClassifier.detectMultiScale2(image[, scaleFactor[, minNeighbors[, flags[, minSize[, maxSize]]]]]) -> objects, numDetections
.. ocv:pyfunction:: cv2.CascadeClassifier.detectMultiScale3(image[, scaleFactor[, minNeighbors[, flags[, minSize[, maxSize[, outputRejectLevels]]]]]]) -> objects, rejectLevels, levelWeights
.. ocv:cfunction:: CvSeq* cvHaarDetectObjects( const CvArr* image, CvHaarClassifierCascade* cascade, CvMemStorage* storage, double scale_factor=1.1, int min_neighbors=3, int flags=0, CvSize min_size=cvSize(0,0), CvSize max_size=cvSize(0,0) )
@@ -110,6 +112,8 @@ Detects objects of different sizes in the input image. The detected objects are
:param maxSize: Maximum possible object size. Objects larger than that are ignored.
:param outputRejectLevels: Boolean. If ``True``, it returns the rejectLevels and levelWeights. Default value is ``False``.
The function is parallelized with the TBB library.
.. note::