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added tests for some detectors; made features2d object create functions as static classes methods; fixed OpponentColorDescriptorExtractor, BriefDescriptorExtractor (on rgb); renamed DynamicDetector

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Maria Dimashova
2010-11-25 15:59:37 +00:00
parent 9ad7a1c927
commit 7e5c11a920
13 changed files with 400 additions and 322 deletions
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115
modules/features2d/src/dynamic.cpp
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@@ -41,14 +41,16 @@
//M*/
#include "precomp.hpp"
namespace cv {
DynamicDetector::DynamicDetector(int min_features,
int max_features, int max_iters, const Ptr<AdjusterAdapter>& a) :
escape_iters_(max_iters), min_features_(min_features), max_features_(
max_features), adjuster_(a) {
}
void DynamicDetector::detectImpl(const cv::Mat& image, std::vector<
cv::KeyPoint>& keypoints, const cv::Mat& mask) const {
namespace cv
{
DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector(const Ptr<AdjusterAdapter>& a,
int min_features, int max_features, int max_iters ) :
escape_iters_(max_iters), min_features_(min_features), max_features_(max_features), adjuster_(a)
{}
void DynamicAdaptedFeatureDetector::detectImpl(const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask) const
{
//for oscillation testing
bool down = false;
bool up = false;
@@ -62,88 +64,131 @@ void DynamicDetector::detectImpl(const cv::Mat& image, std::vector<
//break if the desired number hasn't been reached.
int iter_count = escape_iters_;
do {
do
{
keypoints.clear();
//the adjuster takes care of calling the detector with updated parameters
adjuster.detect(image, keypoints,mask);
if (int(keypoints.size()) < min_features_) {
if (int(keypoints.size()) < min_features_)
{
down = true;
adjuster.tooFew(min_features_, keypoints.size());
} else if (int(keypoints.size()) > max_features_) {
}
else if (int(keypoints.size()) > max_features_)
{
up = true;
adjuster.tooMany(max_features_, keypoints.size());
} else
}
else
thresh_good = true;
} while (--iter_count >= 0 && !(down && up) && !thresh_good
&& adjuster.good());
}
while (--iter_count >= 0 && !(down && up) && !thresh_good && adjuster.good());
}
FastAdjuster::FastAdjuster(int init_thresh, bool nonmax) :
thresh_(init_thresh), nonmax_(nonmax) {
}
void FastAdjuster::detectImpl(const cv::Mat& image,
std::vector<cv::KeyPoint>& keypoints, const cv::Mat& mask) const {
thresh_(init_thresh), nonmax_(nonmax)
{}
void FastAdjuster::detectImpl(const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask) const
{
FastFeatureDetector(thresh_, nonmax_).detect(image, keypoints, mask);
}
void FastAdjuster::tooFew(int min, int n_detected) {
void FastAdjuster::tooFew(int min, int n_detected)
{
//fast is easy to adjust
thresh_--;
}
void FastAdjuster::tooMany(int max, int n_detected) {
void FastAdjuster::tooMany(int max, int n_detected)
{
//fast is easy to adjust
thresh_++;
}
//return whether or not the threshhold is beyond
//a useful point
bool FastAdjuster::good() const {
bool FastAdjuster::good() const
{
return (thresh_ > 1) && (thresh_ < 200);
}
StarAdjuster::StarAdjuster(double initial_thresh) :
thresh_(initial_thresh) {
}
void StarAdjuster::detectImpl(const cv::Mat& image,
std::vector<cv::KeyPoint>& keypoints, const cv::Mat& mask) const {
thresh_(initial_thresh)
{}
void StarAdjuster::detectImpl(const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask) const
{
StarFeatureDetector detector_tmp(16, thresh_, 10, 8, 3);
detector_tmp.detect(image, keypoints, mask);
}
void StarAdjuster::tooFew(int min, int n_detected) {
void StarAdjuster::tooFew(int min, int n_detected)
{
thresh_ *= 0.9;
if (thresh_ < 1.1)
thresh_ = 1.1;
}
void StarAdjuster::tooMany(int max, int n_detected) {
void StarAdjuster::tooMany(int max, int n_detected)
{
thresh_ *= 1.1;
}
bool StarAdjuster::good() const {
bool StarAdjuster::good() const
{
return (thresh_ > 2) && (thresh_ < 200);
}
SurfAdjuster::SurfAdjuster() :
thresh_(400.0) {
}
void SurfAdjuster::detectImpl(const cv::Mat& image,
std::vector<cv::KeyPoint>& keypoints, const cv::Mat& mask) const {
thresh_(400.0)
{}
void SurfAdjuster::detectImpl(const Mat& image, vector<KeyPoint>& keypoints, const cv::Mat& mask) const
{
SurfFeatureDetector detector_tmp(thresh_);
detector_tmp.detect(image, keypoints, mask);
}
void SurfAdjuster::tooFew(int min, int n_detected) {
void SurfAdjuster::tooFew(int min, int n_detected)
{
thresh_ *= 0.9;
if (thresh_ < 1.1)
thresh_ = 1.1;
}
void SurfAdjuster::tooMany(int max, int n_detected) {
void SurfAdjuster::tooMany(int max, int n_detected)
{
thresh_ *= 1.1;
}
//return whether or not the threshhold is beyond
//a useful point
bool SurfAdjuster::good() const {
bool SurfAdjuster::good() const
{
return (thresh_ > 2) && (thresh_ < 1000);
}
Ptr<AdjusterAdapter> AdjusterAdapter::create( const string& detectorType )
{
Ptr<AdjusterAdapter> adapter;
if( !detectorType.compare( "FAST" ) )
{
adapter = new FastAdjuster();
}
else if( !detectorType.compare( "STAR" ) )
{
adapter = new StarAdjuster();
}
else if( !detectorType.compare( "SURF" ) )
{
adapter = new SurfAdjuster();
}
return adapter;
}
}