提交 4e60deca 编写于 作者: M Maria Dimashova

added GridAdaptedFeatureDetector, PyramidAdaptedFeatureDetector and funcs to...

added GridAdaptedFeatureDetector, PyramidAdaptedFeatureDetector and funcs to draw keypoints and matches
上级 9c94a96c
......@@ -1477,6 +1477,44 @@ protected:
CV_EXPORTS Ptr<FeatureDetector> createDetector( const string& detectorType );
/*
* Adapts a detector to partition the source image into a grid and detect
* points in each cell.
*/
class CV_EXPORTS GridAdaptedFeatureDetector : public FeatureDetector
{
public:
GridAdaptedFeatureDetector( const Ptr<FeatureDetector>& _detector, int _maxTotalKeypoints,
int _gridRows=4, int _gridCols=4 );
// todo read/write
protected:
Ptr<FeatureDetector> detector;
int maxTotalKeypoints;
int gridRows;
int gridCols;
virtual void detectImpl( const Mat& image, const Mat& mask, vector<KeyPoint>& keypoints ) const;
};
/*
* Adapts a detector to detect points over multiple levels of a Gaussian
* pyramid. Useful for detectors that are not inherently scaled.
*/
class PyramidAdaptedFeatureDetector : public FeatureDetector
{
public:
PyramidAdaptedFeatureDetector( const Ptr<FeatureDetector>& _detector, int _levels=2 );
// todo read/write
protected:
Ptr<FeatureDetector> detector;
int levels;
virtual void detectImpl( const Mat& image, const Mat& mask, vector<KeyPoint>& keypoints ) const;
};
/****************************************************************************************\
* DescriptorExtractor *
\****************************************************************************************/
......@@ -2273,18 +2311,38 @@ struct CV_EXPORTS DrawMatchesFlags
enum{ DEFAULT = 0, // Output image matrix will be created (Mat::create),
// i.e. existing memory of output image may be reused.
// Two source image, matches and single keypoints will be drawn.
// For each keypoint only the center point will be drawn (without
// the circle around keypoint with keypoint size and orientation).
DRAW_OVER_OUTIMG = 1, // Output image matrix will not be created (Mat::create).
// Matches will be drawn on existing content of output image.
NOT_DRAW_SINGLE_POINTS = 2 // Single keypoints will not be drawn.
NOT_DRAW_SINGLE_POINTS = 2, // Single keypoints will not be drawn.
DRAW_RICH_KEYPOINTS = 4 // For each keypoint the circle around keypoint with keypoint size and
// orientation will be drawn.
};
};
// Draw keypoints.
CV_EXPORTS void drawKeypoints( const Mat& image, const vector<KeyPoint>& keypoints, Mat& outImg,
const Scalar& color=Scalar::all(-1), int flags=DrawMatchesFlags::DEFAULT );
// Draws matches of keypints from two images on output image.
CV_EXPORTS void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1,
const Mat& img2, const vector<KeyPoint>& keypoints2,
const vector<int>& matches, Mat& outImg,
const Scalar& matchColor = Scalar::all(-1), const Scalar& singlePointColor = Scalar::all(-1),
const vector<char>& matchesMask = vector<char>(), int flags = DrawMatchesFlags::DEFAULT );
const vector<int>& matches1to2, Mat& outImg,
const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1),
const vector<char>& matchesMask=vector<char>(), int flags=DrawMatchesFlags::DEFAULT );
CV_EXPORTS void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1,
const Mat& img2, const vector<KeyPoint>& keypoints2,
const vector<DMatch>& matches1to2, Mat& outImg,
const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1),
const vector<char>& matchesMask=vector<char>(), int flags=DrawMatchesFlags::DEFAULT );
CV_EXPORTS void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1,
const Mat& img2, const vector<KeyPoint>& keypoints2,
const vector<vector<DMatch> >& matches1to2, Mat& outImg,
const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1),
const vector<vector<char> >& matchesMask=vector<vector<char> >(), int flags=DrawMatchesFlags::DEFAULT );
}
......
......@@ -48,6 +48,10 @@
//#define _KDTREE
using namespace std;
const int draw_shift_bits = 4;
const int draw_multiplier = 1 << draw_shift_bits;
namespace cv
{
......@@ -69,63 +73,190 @@ Mat windowedMatchingMask( const vector<KeyPoint>& keypoints1, const vector<KeyPo
return mask;
}
void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1,
const Mat& img2,const vector<KeyPoint>& keypoints2,
const vector<int>& matches, Mat& outImg,
const Scalar& matchColor, const Scalar& singlePointColor,
const vector<char>& matchesMask, int flags )
/*
* Drawing functions
*/
static inline void _drawKeypoint( Mat& img, const KeyPoint& p, const Scalar& color, int flags )
{
Point center( p.pt.x * draw_multiplier, p.pt.y * draw_multiplier );
if( flags & DrawMatchesFlags::DRAW_RICH_KEYPOINTS )
{
int radius = p.size/2 * draw_multiplier; // KeyPoint::size is a diameter
// draw the circles around keypoints with the keypoints size
circle( img, center, radius, color, 1, CV_AA, draw_shift_bits );
// draw orientation of the keypoint, if it is applicable
if( p.angle != -1 )
{
float srcAngleRad = p.angle*CV_PI/180;
Point orient(cos(srcAngleRad)*radius, sin(srcAngleRad)*radius);
line( img, center, center+orient, color, 1, CV_AA, draw_shift_bits );
}
#if 0
else
{
// draw center with R=1
int radius = 1 * draw_multiplier;
circle( img, center, radius, color, 1, CV_AA, draw_shift_bits );
}
#endif
}
else
{
// draw center with R=3
int radius = 3 * draw_multiplier;
circle( img, center, radius, color, 1, CV_AA, draw_shift_bits );
}
}
void drawKeypoints( const Mat& image, const vector<KeyPoint>& keypoints, Mat& outImg,
const Scalar& _color, int flags )
{
if( !(flags & DrawMatchesFlags::DRAW_OVER_OUTIMG) )
cvtColor( image, outImg, CV_GRAY2BGR );
RNG& rng=theRNG();
bool isRandColor = _color == Scalar::all(-1);
for( vector<KeyPoint>::const_iterator i = keypoints.begin(), ie = keypoints.end(); i != ie; ++i )
{
Scalar color = isRandColor ? Scalar(rng(256), rng(256), rng(256)) : _color;
_drawKeypoint( outImg, *i, color, flags );
}
}
static void _prepareImgAndDrawKeypoints( const Mat& img1, const vector<KeyPoint>& keypoints1,
const Mat& img2, const vector<KeyPoint>& keypoints2,
Mat& outImg, Mat& outImg1, Mat& outImg2,
const Scalar& singlePointColor, int flags )
{
Size size( img1.cols + img2.cols, MAX(img1.rows, img2.rows) );
if( flags & DrawMatchesFlags::DRAW_OVER_OUTIMG )
{
if( size.width > outImg.cols || size.height > outImg.rows )
CV_Error( CV_StsBadSize, "outImg has size less than need to draw img1 and img2 together" );
outImg1 = outImg( Rect(0, 0, img1.cols, img1.rows) );
outImg2 = outImg( Rect(img1.cols, 0, img2.cols, img2.rows) );
}
else
{
outImg.create( size, CV_MAKETYPE(img1.depth(), 3) );
Mat outImg1 = outImg( Rect(0, 0, img1.cols, img1.rows) );
outImg1 = outImg( Rect(0, 0, img1.cols, img1.rows) );
outImg2 = outImg( Rect(img1.cols, 0, img2.cols, img2.rows) );
cvtColor( img1, outImg1, CV_GRAY2RGB );
Mat outImg2 = outImg( Rect(img1.cols, 0, img2.cols, img2.rows) );
cvtColor( img2, outImg2, CV_GRAY2RGB );
}
RNG rng;
// draw keypoints
if( !(flags & DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS) )
{
bool isRandSinglePointColor = singlePointColor == Scalar::all(-1);
for( vector<KeyPoint>::const_iterator it = keypoints1.begin(); it < keypoints1.end(); ++it )
Mat outImg1 = outImg( Rect(0, 0, img1.cols, img1.rows) );
drawKeypoints( outImg1, keypoints1, outImg1, singlePointColor, flags + DrawMatchesFlags::DRAW_OVER_OUTIMG );
Mat outImg2 = outImg( Rect(img1.cols, 0, img2.cols, img2.rows) );
drawKeypoints( outImg2, keypoints2, outImg2, singlePointColor, flags + DrawMatchesFlags::DRAW_OVER_OUTIMG );
}
}
static inline void _drawMatch( Mat& outImg, Mat& outImg1, Mat& outImg2 ,
const KeyPoint& kp1, const KeyPoint& kp2, const Scalar& matchColor, int flags )
{
RNG& rng = theRNG();
bool isRandMatchColor = matchColor == Scalar::all(-1);
Scalar color = isRandMatchColor ? Scalar( rng(256), rng(256), rng(256) ) : matchColor;
_drawKeypoint( outImg1, kp1, color, flags );
_drawKeypoint( outImg2, kp2, color, flags );
Point2f pt1 = kp1.pt,
pt2 = kp2.pt,
dpt2 = Point2f( std::min(pt2.x+outImg1.cols, float(outImg.cols-1)), pt2.y );
line( outImg, Point(pt1.x*draw_multiplier, pt1.y*draw_multiplier), Point(dpt2.x*draw_multiplier, dpt2.y*draw_multiplier),
color, 1, CV_AA, draw_shift_bits );
}
void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1,
const Mat& img2,const vector<KeyPoint>& keypoints2,
const vector<int>& matches1to2, Mat& outImg,
const Scalar& matchColor, const Scalar& singlePointColor,
const vector<char>& matchesMask, int flags )
{
if( matches1to2.size() != keypoints1.size() )
CV_Error( CV_StsBadSize, "matches1to2 must have the same size as keypoints1" );
if( !matchesMask.empty() && matchesMask.size() != matches1to2.size() )
CV_Error( CV_StsBadSize, "matchesMask must have the same size as matches1to2" );
Mat outImg1, outImg2;
_prepareImgAndDrawKeypoints( img1, keypoints1, img2, keypoints2,
outImg, outImg1, outImg2, singlePointColor, flags );
// draw matches
for( size_t i1 = 0; i1 < keypoints1.size(); i1++ )
{
int i2 = matches1to2[i1];
if( (matchesMask.empty() || matchesMask[i1] ) && i2 >= 0 )
{
circle( outImg, it->pt, 3, isRandSinglePointColor ?
Scalar(rng.uniform(0, 256), rng.uniform(0, 256), rng.uniform(0, 256)) : singlePointColor );
const KeyPoint &kp1 = keypoints1[i1], &kp2 = keypoints2[i2];
_drawMatch( outImg, outImg1, outImg2, kp1, kp2, matchColor, flags );
}
for( vector<KeyPoint>::const_iterator it = keypoints2.begin(); it < keypoints2.end(); ++it )
}
}
void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1,
const Mat& img2, const vector<KeyPoint>& keypoints2,
const vector<DMatch>& matches1to2, Mat& outImg,
const Scalar& matchColor, const Scalar& singlePointColor,
const vector<char>& matchesMask, int flags )
{
if( !matchesMask.empty() && matchesMask.size() != matches1to2.size() )
CV_Error( CV_StsBadSize, "matchesMask must have the same size as matches1to2" );
Mat outImg1, outImg2;
_prepareImgAndDrawKeypoints( img1, keypoints1, img2, keypoints2,
outImg, outImg1, outImg2, singlePointColor, flags );
// draw matches
for( size_t m = 0; m < matches1to2.size(); m++ )
{
int i1 = matches1to2[m].indexQuery;
int i2 = matches1to2[m].indexTrain;
if( matchesMask.empty() || matchesMask[m] )
{
Point p = it->pt;
circle( outImg, Point(p.x+img1.cols, p.y), 3, isRandSinglePointColor ?
Scalar(rng.uniform(0, 256), rng.uniform(0, 256), rng.uniform(0, 256)) : singlePointColor );
const KeyPoint &kp1 = keypoints1[i1], &kp2 = keypoints2[i2];
_drawMatch( outImg, outImg1, outImg2, kp1, kp2, matchColor, flags );
}
}
}
}
void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1,
const Mat& img2, const vector<KeyPoint>& keypoints2,
const vector<vector<DMatch> >& matches1to2, Mat& outImg,
const Scalar& matchColor, const Scalar& singlePointColor,
const vector<vector<char> >& matchesMask, int flags )
{
if( !matchesMask.empty() && matchesMask.size() != matches1to2.size() )
CV_Error( CV_StsBadSize, "matchesMask must have the same size as matches1to2" );
Mat outImg1, outImg2;
_prepareImgAndDrawKeypoints( img1, keypoints1, img2, keypoints2,
outImg, outImg1, outImg2, singlePointColor, flags );
// draw matches
bool isRandMatchColor = matchColor == Scalar::all(-1);
if( matches.size() != keypoints1.size() )
CV_Error( CV_StsBadSize, "matches must have the same size as keypoints1" );
if( !matchesMask.empty() && matchesMask.size() != keypoints1.size() )
CV_Error( CV_StsBadSize, "mask must have the same size as keypoints1" );
vector<int>::const_iterator mit = matches.begin();
for( int i1 = 0; mit != matches.end(); ++mit, i1++ )
{
if( (matchesMask.empty() || matchesMask[i1] ) && *mit >= 0 )
for( size_t i = 0; i < matches1to2.size(); i++ )
{
for( size_t j = 0; j < matches1to2[i].size(); j++ )
{
Point2f pt1 = keypoints1[i1].pt,
pt2 = keypoints2[*mit].pt,
dpt2 = Point2f( std::min(pt2.x+img1.cols, float(outImg.cols-1)), pt2.y );
Scalar randColor( rng.uniform(0, 256), rng.uniform(0, 256), rng.uniform(0, 256) );
circle( outImg, pt1, 3, isRandMatchColor ? randColor : matchColor );
circle( outImg, dpt2, 3, isRandMatchColor ? randColor : matchColor );
line( outImg, pt1, dpt2, isRandMatchColor ? randColor : matchColor );
int i1 = matches1to2[i][j].indexQuery;
int i2 = matches1to2[i][j].indexTrain;
if( matchesMask.empty() || matchesMask[i][j] )
{
const KeyPoint &kp1 = keypoints1[i1], &kp2 = keypoints2[i2];
_drawMatch( outImg, outImg1, outImg2, kp1, kp2, matchColor, flags );
}
}
}
}
......
......@@ -46,8 +46,8 @@ using namespace std;
namespace cv
{
/*
FeatureDetector
*/
* FeatureDetector
*/
struct MaskPredicate
{
MaskPredicate( const Mat& _mask ) : mask(_mask)
......@@ -70,8 +70,8 @@ void FeatureDetector::removeInvalidPoints( const Mat& mask, vector<KeyPoint>& ke
};
/*
FastFeatureDetector
*/
* FastFeatureDetector
*/
FastFeatureDetector::FastFeatureDetector( int _threshold, bool _nonmaxSuppression )
: threshold(_threshold), nonmaxSuppression(_nonmaxSuppression)
{}
......@@ -95,8 +95,8 @@ void FastFeatureDetector::detectImpl( const Mat& image, const Mat& mask, vector<
}
/*
GoodFeaturesToTrackDetector
*/
* GoodFeaturesToTrackDetector
*/
GoodFeaturesToTrackDetector::GoodFeaturesToTrackDetector( int _maxCorners, double _qualityLevel, \
double _minDistance, int _blockSize,
bool _useHarrisDetector, double _k )
......@@ -140,8 +140,8 @@ void GoodFeaturesToTrackDetector::detectImpl( const Mat& image, const Mat& mask,
}
/*
MserFeatureDetector
*/
* MserFeatureDetector
*/
MserFeatureDetector::MserFeatureDetector( int delta, int minArea, int maxArea,
double maxVariation, double minDiversity,
int maxEvolution, double areaThreshold,
......@@ -204,8 +204,8 @@ void MserFeatureDetector::detectImpl( const Mat& image, const Mat& mask, vector<
}
/*
StarFeatureDetector
*/
* StarFeatureDetector
*/
StarFeatureDetector::StarFeatureDetector(int maxSize, int responseThreshold,
int lineThresholdProjected,
int lineThresholdBinarized,
......@@ -244,8 +244,8 @@ void StarFeatureDetector::detectImpl( const Mat& image, const Mat& mask, vector<
}
/*
SiftFeatureDetector
*/
* SiftFeatureDetector
*/
SiftFeatureDetector::SiftFeatureDetector(double threshold, double edgeThreshold,
int nOctaves, int nOctaveLayers, int firstOctave, int angleMode) :
sift(threshold, edgeThreshold, nOctaves, nOctaveLayers, firstOctave, angleMode)
......@@ -286,8 +286,8 @@ void SiftFeatureDetector::detectImpl( const Mat& image, const Mat& mask,
}
/*
SurfFeatureDetector
*/
* SurfFeatureDetector
*/
SurfFeatureDetector::SurfFeatureDetector( double hessianThreshold, int octaves, int octaveLayers)
: surf(hessianThreshold, octaves, octaveLayers)
{}
......@@ -360,4 +360,98 @@ Ptr<FeatureDetector> createDetector( const string& detectorType )
return fd;
}
/*
* GridAdaptedFeatureDetector
*/
GridAdaptedFeatureDetector::GridAdaptedFeatureDetector( const Ptr<FeatureDetector>& _detector,
int _maxTotalKeypoints, int _gridRows, int _gridCols )
: detector(_detector), maxTotalKeypoints(_maxTotalKeypoints), gridRows(_gridRows), gridCols(_gridCols)
{}
struct ResponseComparator
{
bool operator() (const KeyPoint& a, const KeyPoint& b)
{
return std::abs(a.response) > std::abs(b.response);
}
};
void keepStrongest( int N, vector<KeyPoint>& keypoints )
{
if( (int)keypoints.size() > N )
{
vector<KeyPoint>::iterator nth = keypoints.begin() + N;
std::nth_element( keypoints.begin(), nth, keypoints.end(), ResponseComparator() );
keypoints.erase( nth, keypoints.end() );
}
}
void GridAdaptedFeatureDetector::detectImpl( const Mat &image, const Mat &mask,
vector<KeyPoint> &keypoints ) const
{
keypoints.clear();
keypoints.reserve(maxTotalKeypoints);
int maxPerCell = maxTotalKeypoints / (gridRows * gridCols);
for( int i = 0; i < gridRows; ++i )
{
Range row_range((i*image.rows)/gridRows, ((i+1)*image.rows)/gridRows);
for( int j = 0; j < gridCols; ++j )
{
Range col_range((j*image.cols)/gridCols, ((j+1)*image.cols)/gridCols);
Mat sub_image = image(row_range, col_range);
Mat sub_mask;
if( !mask.empty() )
sub_mask = mask(row_range, col_range);
vector<KeyPoint> sub_keypoints;
detector->detect( sub_image, sub_keypoints, sub_mask );
keepStrongest( maxPerCell, sub_keypoints );
for( std::vector<cv::KeyPoint>::iterator it = sub_keypoints.begin(), end = sub_keypoints.end();
it != end; ++it )
{
it->pt.x += col_range.start;
it->pt.y += row_range.start;
}
keypoints.insert( keypoints.end(), sub_keypoints.begin(), sub_keypoints.end() );
}
}
}
/*
* GridAdaptedFeatureDetector
*/
PyramidAdaptedFeatureDetector::PyramidAdaptedFeatureDetector( const Ptr<FeatureDetector>& _detector, int _levels )
: detector(_detector), levels(_levels)
{}
void PyramidAdaptedFeatureDetector::detectImpl( const Mat& image, const Mat& mask, vector<KeyPoint>& keypoints ) const
{
Mat src = image;
for( int l = 0, multiplier = 1; l <= levels; ++l, multiplier *= 2 )
{
// Detect on current level of the pyramid
vector<KeyPoint> new_pts;
detector->detect(src, new_pts);
for( vector<KeyPoint>::iterator it = new_pts.begin(), end = new_pts.end(); it != end; ++it)
{
it->pt.x *= multiplier;
it->pt.y *= multiplier;
it->size *= multiplier;
it->octave = l;
}
removeInvalidPoints( mask, new_pts );
keypoints.insert( keypoints.end(), new_pts.begin(), new_pts.end() );
// Downsample
if( l < levels )
{
Mat dst;
pyrDown(src, dst);
src = dst;
}
}
}
}
......@@ -8,6 +8,9 @@
using namespace cv;
using namespace std;
#define DRAW_RICH_KEYPOINTS_MODE 0
#define DRAW_OUTLIERS_MODE 0
void warpPerspectiveRand( const Mat& src, Mat& dst, Mat& H, RNG& rng )
{
H.create(3, 3, CV_32FC1);
......@@ -79,12 +82,18 @@ void doIteration( const Mat& img1, Mat& img2, bool isWarpPerspective,
matchesMask[i1] = 1;
}
// draw inliers
drawMatches( img1, keypoints1, img2, keypoints2, matches, drawImg, CV_RGB(0, 255, 0), CV_RGB(0, 0, 255), matchesMask );
#if 0 // draw outliers
drawMatches( img1, keypoints1, img2, keypoints2, matches, drawImg, CV_RGB(0, 255, 0), CV_RGB(0, 0, 255), matchesMask
#if DRAW_RICH_KEYPOINTS_MODE
, DrawMatchesFlags::DRAW_RICH_KEYPOINTS
#endif
);
#if DRAW_OUTLIERS_MODE
// draw outliers
for( size_t i1 = 0; i1 < matchesMask.size(); i1++ )
matchesMask[i1] = !matchesMask[i1];
drawMatches( img1, keypoints1, img2, keypoints2, matches, drawImg, CV_RGB(0, 0, 255), CV_RGB(255, 0, 0), matchesMask,
DrawMatchesFlags::DRAW_OVER_OUTIMG | DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS )
DrawMatchesFlags::DRAW_OVER_OUTIMG | DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
#endif
}
else
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册