WaldBoost object detector from [112] .
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#include "xobjdetect.hpp"
Inheritance diagram for cv::xobjdetect::WaldBoost:
Public Member Functions
Predict objects class given object that can compute object features.
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virtual std::vector< int >
train (
Mat &data, const
Mat &labels, bool use_fast_log=false)=0
Clears the algorithm state.
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virtual bool
empty () const
Returns true if the
Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
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Reads algorithm parameters from a file storage.
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Stores algorithm parameters in a file storage.
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Additional Inherited Members
template<typename _Tp >
Loads algorithm from the file.
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template<typename _Tp >
template<typename _Tp >
Reads algorithm from the file node.
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Detailed Description
Member Function Documentation
virtual float cv::xobjdetect::WaldBoost::predict
(
const
Ptr<
FeatureEvaluator > &
feature_evaluator )
const
Predict objects class given object that can compute object features.
Returns unnormed confidence value — measure of confidence that object is from class +1.
- Parameters
-
feature_evaluator object that can compute features by demand
virtual std::vector<int> cv::xobjdetect::WaldBoost::train
(
Mat &
data,
bool
use_fast_log = false
)
pure virtual
Train WaldBoost cascade for given data.
Returns feature indices chosen for cascade. Feature enumeration starts from 0.
- Parameters
-
data matrix of feature values, size M x N, one feature per row
labels matrix of samples class labels, size 1 x N. Labels can be from {-1, +1}
use_fast_log
The documentation for this class was generated from the following file:
- /builds/master-contrib_docs-mac/opencv_contrib/modules/xobjdetect/include/opencv2/xobjdetect.hpp