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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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3
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.

11
modules/objdetect/include/opencv2/objdetect/objdetect.hpp
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@ -382,14 +382,6 @@ public:
Size minSize=Size(),
Size maxSize=Size() );
CV_WRAP virtual void detectMultiScale( const Mat& image,
CV_OUT vector<Rect>& objects,
vector<int>& weights,
double scaleFactor=1.1,
int minNeighbors=3, int flags=0,
Size minSize=Size(),
Size maxSize=Size() );
CV_WRAP virtual void detectMultiScale( const Mat& image,
CV_OUT vector<Rect>& objects,
vector<int>& rejectLevels,
@ -398,8 +390,7 @@ public:
int minNeighbors=3, int flags=0,
Size minSize=Size(),
Size maxSize=Size(),
bool outputRejectLevels=false,
bool outputWeights=false );
bool outputRejectLevels=false );
bool isOldFormatCascade() const;

24
modules/objdetect/src/cascadedetect.cpp
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@ -1023,7 +1023,6 @@ public:
};
struct getRect { Rect operator ()(const CvAvgComp& e) const { return e.rect; } };
struct getNeighbors { int operator ()(const CvAvgComp& e) const { return e.neighbors; } };
bool CascadeClassifier::detectSingleScale( const Mat& image, int stripCount, Size processingRectSize,
@ -1093,12 +1092,11 @@ void CascadeClassifier::detectMultiScale( const Mat& image, vector<Rect>& object
vector<double>& levelWeights,
double scaleFactor, int minNeighbors,
int flags, Size minObjectSize, Size maxObjectSize,
bool outputRejectLevels, bool outputWeights )
bool outputRejectLevels )
{
const double GROUP_EPS = 0.2;
CV_Assert( scaleFactor > 1 && image.depth() == CV_8U );
CV_Assert( !( outputRejectLevels && outputWeights ) );
if( empty() )
return;
@ -1113,12 +1111,6 @@ void CascadeClassifier::detectMultiScale( const Mat& image, vector<Rect>& object
Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
objects.resize(vecAvgComp.size());
std::transform(vecAvgComp.begin(), vecAvgComp.end(), objects.begin(), getRect());
if( outputWeights )
{
rejectLevels.resize(vecAvgComp.size());
std::transform(vecAvgComp.begin(), vecAvgComp.end(), rejectLevels.begin(),
getNeighbors());
}
return;
}
@ -1191,10 +1183,6 @@ void CascadeClassifier::detectMultiScale( const Mat& image, vector<Rect>& object
{
groupRectangles( objects, rejectLevels, levelWeights, minNeighbors, GROUP_EPS );
}
else if( outputWeights )
{
groupRectangles( objects, rejectLevels, minNeighbors, GROUP_EPS );
}
else
{
groupRectangles( objects, minNeighbors, GROUP_EPS );
@ -1211,16 +1199,6 @@ void CascadeClassifier::detectMultiScale( const Mat& image, vector<Rect>& object
minNeighbors, flags, minObjectSize, maxObjectSize, false );
}
void CascadeClassifier::detectMultiScale( const Mat& image, CV_OUT vector<Rect>& objects,
vector<int>& weights, double scaleFactor,
int minNeighbors, int flags, Size minObjectSize,
Size maxObjectSize )
{
vector<double> fakeLevelWeights;
detectMultiScale( image, objects, weights, fakeLevelWeights, scaleFactor,
minNeighbors, flags, minObjectSize, maxObjectSize, false, true );
}
bool CascadeClassifier::Data::read(const FileNode &root)
{
static const float THRESHOLD_EPS = 1e-5f;