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Revert "Add a variant of detectMultiScale with an argument 'weights'"

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It was merged by mistake.

This reverts commit ab6be9b7b7.
This commit is contained in:
Roman Donchenko
2013-06-10 17:06:34 +04:00
parent 52e9974431
commit d583a79869
3 changed files with 2 additions and 36 deletions
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modules/objdetect/doc/cascade_classification.rst
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@@ -189,7 +189,6 @@ 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
@@ -204,8 +203,6 @@ 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.