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Add a variant of detectMultiScale with an argument 'weights' that

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receives the number of neighbors joined into each detected object
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Peter Minin
2013-06-06 19:00:55 +04:00
parent 99340b5613
commit ab6be9b7b7
3 changed files with 36 additions and 2 deletions
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modules/objdetect/doc/cascade_classification.rst
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@@ -189,6 +189,7 @@ CascadeClassifier::detectMultiScale
Detects objects of different sizes in the input image. The detected objects are returned as a list of rectangles.
.. ocv:function:: void CascadeClassifier::detectMultiScale( const Mat& 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( const Mat& image, vector<Rect>& objects, vector<int>& weights, double scaleFactor=1.1, int minNeighbors=3, int flags=0, Size minSize=Size(), Size maxSize=Size())
.. ocv:pyfunction:: cv2.CascadeClassifier.detectMultiScale(image[, scaleFactor[, minNeighbors[, flags[, minSize[, maxSize]]]]]) -> objects
.. ocv:pyfunction:: cv2.CascadeClassifier.detectMultiScale(image, rejectLevels, levelWeights[, scaleFactor[, minNeighbors[, flags[, minSize[, maxSize[, outputRejectLevels]]]]]]) -> objects
@@ -203,6 +204,8 @@ Detects objects of different sizes in the input image. The detected objects are
:param objects: Vector of rectangles where each rectangle contains the detected object.
:param weights: Vector of weights of the corresponding objects. Weight is the number of neighboring positively classified rectangles that were joined into one object.
:param scaleFactor: Parameter specifying how much the image size is reduced at each image scale.
:param minNeighbors: Parameter specifying how many neighbors each candidate rectangle should have to retain it.