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trying to eliminate compile problems

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Vadim Pisarevsky
2013-12-04 21:56:35 +04:00
parent ff87385201
commit fe11ca886a
4 changed files with 43 additions and 69 deletions
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modules/objdetect/doc/cascade_classification.rst
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@@ -221,44 +221,6 @@ The function is parallelized with the TBB library.
* (Python) A face detection example using cascade classifiers can be found at opencv_source_code/samples/python2/facedetect.py
CascadeClassifier::setImage
-------------------------------
Sets an image for detection.
.. ocv:function:: bool CascadeClassifier::setImage( Ptr<FeatureEvaluator>& feval, const Mat& image )
.. ocv:cfunction:: void cvSetImagesForHaarClassifierCascade( CvHaarClassifierCascade* cascade, const CvArr* sum, const CvArr* sqsum, const CvArr* tilted_sum, double scale )
:param cascade: Haar classifier cascade (OpenCV 1.x API only). See :ocv:func:`CascadeClassifier::detectMultiScale` for more information.
:param feval: Pointer to the feature evaluator used for computing features.
:param image: Matrix of the type ``CV_8UC1`` containing an image where the features are computed.
The function is automatically called by :ocv:func:`CascadeClassifier::detectMultiScale` at every image scale. But if you want to test various locations manually using :ocv:func:`CascadeClassifier::runAt`, you need to call the function before, so that the integral images are computed.
.. note:: in the old API you need to supply integral images (that can be obtained using :ocv:cfunc:`Integral`) instead of the original image.
CascadeClassifier::runAt
----------------------------
Runs the detector at the specified point.
.. ocv:function:: int CascadeClassifier::runAt( Ptr<FeatureEvaluator>& feval, Point pt, double& weight )
.. ocv:cfunction:: int cvRunHaarClassifierCascade( const CvHaarClassifierCascade* cascade, CvPoint pt, int start_stage=0 )
:param cascade: Haar classifier cascade (OpenCV 1.x API only). See :ocv:func:`CascadeClassifier::detectMultiScale` for more information.
:param feval: Feature evaluator used for computing features.
:param pt: Upper left point of the window where the features are computed. Size of the window is equal to the size of training images.
The function returns 1 if the cascade classifier detects an object in the given location.
Otherwise, it returns negated index of the stage at which the candidate has been rejected.
Use :ocv:func:`CascadeClassifier::setImage` to set the image for the detector to work with.
groupRectangles
-------------------
Groups the object candidate rectangles.