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Commit 8e53eb5c authored by Maria Dimashova's avatar Maria Dimashova
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minor changes of feature2d documentation

parent b251136e
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Showing with 31 additions and 26 deletions
doc/cv_feature_detection.tex
View file @ 8e53eb5c
......@@ -1236,7 +1236,7 @@ protected:
Detect keypoints in an image.
\cvdefCpp{
void detect( const Mat\& image, vector<KeyPoint>\& keypoints, const Mat\& mask=Mat() ) const;
void FeatureDetector::detect( const Mat\& image, vector<KeyPoint>\& keypoints, const Mat\& mask=Mat() ) const;
}
\begin{description}
......@@ -1249,7 +1249,7 @@ void detect( const Mat\& image, vector<KeyPoint>\& keypoints, const Mat\& mask=M
Read feature detector from file node.
\cvdefCpp{
void read( const FileNode\& fn );
void FeatureDetector::read( const FileNode\& fn );
}
\begin{description}
......@@ -1260,7 +1260,7 @@ void read( const FileNode\& fn );
Write feature detector to file storage.
\cvdefCpp{
void write( FileStorage\& fs ) const;
void FeatureDetector::write( FileStorage\& fs ) const;
}
\begin{description}
......@@ -1276,7 +1276,7 @@ class FastFeatureDetector : public FeatureDetector
public:
FastFeatureDetector( int _threshold = 1, bool _nonmaxSuppression = true );
virtual void read (const FileNode& fn);
virtual void read (const FileNode& fn);
virtual void write (FileStorage& fs) const;
protected:
......@@ -1331,7 +1331,7 @@ class StarFeatureDetector : public FeatureDetector
{
public:
StarFeatureDetector( int maxSize=16, int responseThreshold=30,
int lineThresholdProjected = 10,
int lineThresholdProjected = 10,
int lineThresholdBinarized=8, int suppressNonmaxSize=5 );
virtual void read (const FileNode& fn);
......@@ -1409,7 +1409,7 @@ descriptors as a \cvCppCross{Mat}, where each row is one keypoint descriptor.
Compute the descriptors for a set of keypoints in an image. Must be implemented by the subclass.
\cvdefCpp{
void compute( const Mat\& image, vector<KeyPoint>\& keypoints, Mat\& descriptors ) const;
void DescriptorExtractor::compute( const Mat\& image, vector<KeyPoint>\& keypoints, Mat\& descriptors ) const;
}
\begin{description}
......@@ -1422,7 +1422,7 @@ void compute( const Mat\& image, vector<KeyPoint>\& keypoints, Mat\& descriptors
Read descriptor extractor from file node.
\cvdefCpp{
void read( const FileNode\& fn );
void DescriptorExtractor::read( const FileNode\& fn );
}
\begin{description}
......@@ -1433,7 +1433,7 @@ void read( const FileNode\& fn );
Write descriptor extractor to file storage.
\cvdefCpp{
void write( FileStorage\& fs ) const;
void DescriptorExtractor::write( FileStorage\& fs ) const;
}
\begin{description}
......@@ -1454,7 +1454,9 @@ public:
int nOctaveLayers=SIFT::CommonParams::DEFAULT_NOCTAVE_LAYERS,
int firstOctave=SIFT::CommonParams::DEFAULT_FIRST_OCTAVE,
int angleMode=SIFT::CommonParams::FIRST_ANGLE );
virtual void compute( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors) const;
virtual void read (const FileNode &fn);
virtual void write (FileStorage &fs) const;
protected:
......@@ -1471,7 +1473,9 @@ class SurfDescriptorExtractor : public DescriptorExtractor
public:
SurfDescriptorExtractor( int nOctaves=4,
int nOctaveLayers=2, bool extended=false );
virtual void compute( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors) const;
virtual void read (const FileNode &fn);
virtual void write (FileStorage &fs) const;
......@@ -1491,8 +1495,8 @@ public:
// Index the descriptors training set.
void index();
void match( const Mat& query, vector<int>& matches ) const;
void match( const Mat& query, const Mat& mask,
vector<int>& matches ) const;
void match( const Mat& query, const Mat& mask,
vector<int>& matches ) const;
virtual void clear();
protected:
...
......@@ -1503,7 +1507,7 @@ protected:
Add descriptors to the training set.
\cvdefCpp{
void add( const Mat\& descriptors );
void DescriptorMatcher::add( const Mat\& descriptors );
}
\begin{description}
......@@ -1516,10 +1520,10 @@ of this method the mask is used to describe which descriptors can be matched.
\texttt{descriptors\_1[i]} can be matched with \texttt{descriptors\_2[j]} only if \texttt{mask.at<char>(i,j)} is non-zero.
\cvdefCpp{
void match( const Mat\& query, vector<int>\& matches ) const;
void DescriptorMatcher::match( const Mat\& query, vector<int>\& matches ) const;
}
\cvdefCpp{
void match( const Mat\& query, const Mat\& mask,
void DescriptorMatcher::match( const Mat\& query, const Mat\& mask,
vector<int>\& matches ) const;
}
......@@ -1533,7 +1537,7 @@ void match( const Mat\& query, const Mat\& mask,
Clear training keypoints.
\cvdefCpp{
void clear();
void DescriptorMatcher::clear();
}
\cvclass{BruteForceMatcher}
......@@ -1546,6 +1550,7 @@ class BruteForceMatcher : public DescriptorMatcher
{
public:
BruteForceMatcher( Distance d = Distance() ) : distance(d) {}
protected:
...
}
......@@ -1641,7 +1646,7 @@ public:
vector<int>& indices ) = 0;
virtual void clear();
virtual void read( const FileNode& fn );
virtual void read( const FileNode& fn );
virtual void write( FileStorage& fs ) const;
protected:
......@@ -1654,7 +1659,7 @@ Adds keypoints to the training set (descriptors are supposed to be calculated he
Keypoints can be passed using \cvCppCross{KeyPointCollection} (with with corresponding images) or as a vector of \cvCppCross{KeyPoint} from a single image.
\cvdefCpp{
void add( KeyPointCollection\& keypoints );
void GenericDescriptorMatch::add( KeyPointCollection\& keypoints );
}
\begin{description}
......@@ -1663,7 +1668,7 @@ void add( KeyPointCollection\& keypoints );
\cvdefCpp{
void add( const Mat\& image, vector<KeyPoint>\& points );
void GenericDescriptorMatch::add( const Mat\& image, vector<KeyPoint>\& points );
}
\begin{description}
......@@ -1675,7 +1680,7 @@ void add( const Mat\& image, vector<KeyPoint>\& points );
Classifies test keypoints.
\cvdefCpp{
void classify( const Mat\& image, vector<KeyPoint>\& points );
void GenericDescriptorMatch::classify( const Mat\& image, vector<KeyPoint>\& points );
}
\begin{description}
......@@ -1687,7 +1692,7 @@ void classify( const Mat\& image, vector<KeyPoint>\& points );
Matches test keypoints to the training set.
\cvdefCpp{
void match( const Mat\& image, vector<KeyPoint>\& points, vector<int>\& indices );
void GenericDescriptorMatch::match( const Mat\& image, vector<KeyPoint>\& points, vector<int>\& indices );
}
\begin{description}
......@@ -1700,21 +1705,21 @@ void match( const Mat\& image, vector<KeyPoint>\& points, vector<int>\& indices
Clears keypoints storing in collection
\cvdefCpp{
void clear();
void GenericDescriptorMatch::clear();
}
\cvCppFunc{GenericDescriptorMatch::read}
Reads match object from a file node
\cvdefCpp{
void read( const FileNode\& fn );
void GenericDescriptorMatch::read( const FileNode\& fn );
}
\cvCppFunc{GenericDescriptorMatch::write}
Writes match object to a file storage
\cvdefCpp{
virtual void write( FileStorage\& fs ) const;
void GenericDescriptorMatch::write( FileStorage\& fs ) const;
}
\cvclass{VectorDescriptorMatch}
......@@ -1729,20 +1734,20 @@ public:
const Matcher& _matcher = Matcher() );
~VectorDescriptorMatch();
// Builds flann index
// Builds flann index
void index();
// Calculates descriptors for a set of keypoints from a single image
// Calculates descriptors for a set of keypoints from a single image
virtual void add( const Mat& image, vector<KeyPoint>& keypoints );
// Matches a set of keypoints with the training set
virtual void match( const Mat& image, vector<KeyPoint>& points,
vector<int>& keypointIndices );
// Clears object (i.e. storing keypoints)
// Clears object (i.e. storing keypoints)
virtual void clear();
// Reads object from file node
// Reads object from file node
virtual void read (const FileNode& fn);
// Writes object to file storage
virtual void write (FileStorage& fs) const;
......
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