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fixed GPU docs

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This commit is contained in:
Vladislav Vinogradov
2011-01-31 07:38:58 +00:00
parent 13019516f7
commit 13c08e384a
5 changed files with 81938 additions and 81505 deletions
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70
doc/gpu_features2d.tex
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@@ -1,62 +1,6 @@
\section{Feature Detection and Description}
\cvclass{gpu::SURFParams\_GPU}
Various SURF algorithm parameters.
\begin{lstlisting}
struct SURFParams_GPU
{
SURFParams_GPU() :
threshold(0.1f),
nOctaves(4),
nIntervals(4),
initialScale(2.f),
l1(3.f/1.5f),
l2(5.f/1.5f),
l3(3.f/1.5f),
l4(1.f/1.5f),
edgeScale(0.81f),
initialStep(1),
extended(true),
featuresRatio(0.01f)
{
}
//! The interest operator threshold
float threshold;
//! The number of octaves to process
int nOctaves;
//! The number of intervals in each octave
int nIntervals;
//! The scale associated with the first interval of the first octave
float initialScale;
//! mask parameter l_1
float l1;
//! mask parameter l_2
float l2;
//! mask parameter l_3
float l3;
//! mask parameter l_4
float l4;
//! The amount to scale the edge rejection mask
float edgeScale;
//! The initial sampling step in pixels.
int initialStep;
//! True, if generate 128-len descriptors, false - 64-len descriptors
bool extended;
//! max features = featuresRatio * img.size().srea()
float featuresRatio;
};
\end{lstlisting}
\cvclass{gpu::SURF\_GPU}
Class for extracting Speeded Up Robust Features from an image.
@@ -236,8 +180,8 @@ void matchSingle(const GpuMat\& queryDescs, \par const GpuMat\& trainDescs, \par
\begin{description}
\cvarg{queryDescs} {Query set of descriptors.}
\cvarg{trainDescs} {Train set of descriptors. This will not be added to train descriptors collection stored in class object.}
\cvarg{trainIdx} {One row \texttt{CV\_32SC1} matrix. Will contain the best train index for each query. If some query descriptors masked out in \texttt{mask} it will contain -1.}
\cvarg{distance} {One row \texttt{CV\_32FC1} matrix. Will contain the best distance for each query. If some query descriptors masked out in \texttt{mask} it will contain \texttt{FLT\_MAX}.}
\cvarg{trainIdx} {One row \texttt{CV\_32SC1} matrix. Will contain the best train index for each query. If some query descriptors are masked out in \texttt{mask} it will contain -1.}
\cvarg{distance} {One row \texttt{CV\_32FC1} matrix. Will contain the best distance for each query. If some query descriptors are masked out in \texttt{mask} it will contain \texttt{FLT\_MAX}.}
\cvarg{mask}{Mask specifying permissible matches between input query and train matrices of descriptors.}
\end{description}
@@ -252,9 +196,9 @@ void matchCollection(const GpuMat\& queryDescs, \par const GpuMat\& trainCollect
\begin{description}
\cvarg{queryDescs} {Query set of descriptors.}
\cvarg{trainCollection} {\texttt{GpuMat} containing train collection. It can be obtained from train descriptors collection that was set using \texttt{add} method by \hyperref[cppfunc.gpu.BruteForceMatcher.makeGpuCollection]{makeGpuCollection}. Or it can contain user defined collection. It must be one row matrix, each element is a \texttt{DevMem2D} that points to one train descriptors matrix.}
\cvarg{trainIdx} {One row \texttt{CV\_32SC1} matrix. Will contain the best train index for each query. If some query descriptors masked out in \texttt{maskCollection} it will contain -1.}
\cvarg{imgIdx} {One row \texttt{CV\_32SC1} matrix. Will contain image train index for each query. If some query descriptors masked out in \texttt{maskCollection} it will contain -1.}
\cvarg{distance} {One row \texttt{CV\_32FC1} matrix. Will contain the best distance for each query. If some query descriptors masked out in \texttt{maskCollection} it will contain \texttt{FLT\_MAX}.}
\cvarg{trainIdx} {One row \texttt{CV\_32SC1} matrix. Will contain the best train index for each query. If some query descriptors are masked out in \texttt{maskCollection} it will contain -1.}
\cvarg{imgIdx} {One row \texttt{CV\_32SC1} matrix. Will contain image train index for each query. If some query descriptors are masked out in \texttt{maskCollection} it will contain -1.}
\cvarg{distance} {One row \texttt{CV\_32FC1} matrix. Will contain the best distance for each query. If some query descriptors are masked out in \texttt{maskCollection} it will contain \texttt{FLT\_MAX}.}
\cvarg{maskCollection}{\texttt{GpuMat} containing set of masks. It can be obtained from \texttt{std::vector<GpuMat>} by \hyperref[cppfunc.gpu.BruteForceMatcher.makeGpuCollection]{makeGpuCollection}. Or it can contain user defined mask set. It must be empty matrix or one row matrix, each element is a \texttt{PtrStep} that points to one mask.}
\end{description}
@@ -299,8 +243,8 @@ void knnMatch(const GpuMat\& queryDescs, \par const GpuMat\& trainDescs, \par Gp
\begin{description}
\cvarg{queryDescs} {Query set of descriptors.}
\cvarg{trainDescs} {Train set of descriptors. This will not be added to train descriptors collection stored in class object.}
\cvarg{trainIdx} {Matrix with $\texttt{nQueries} \times \texttt{k}$ size and \texttt{CV\_32SC1} type. \texttt{trainIdx.at<int>(queryIdx, i)} will contain index of the i'th best trains. If some query descriptors masked out in \texttt{mask} it will contain -1.}
\cvarg{distance} {Matrix with $\texttt{nQuery} \times \texttt{k}$ and \texttt{CV\_32FC1} type. Will contain distance for each query and the i'th best trains. If some query descriptors masked out in \texttt{mask} it will contain \texttt{FLT\_MAX}.}
\cvarg{trainIdx} {Matrix with $\texttt{nQueries} \times \texttt{k}$ size and \texttt{CV\_32SC1} type. \texttt{trainIdx.at<int>(queryIdx, i)} will contain index of the i'th best trains. If some query descriptors are masked out in \texttt{mask} it will contain -1.}
\cvarg{distance} {Matrix with $\texttt{nQuery} \times \texttt{k}$ and \texttt{CV\_32FC1} type. Will contain distance for each query and the i'th best trains. If some query descriptors are masked out in \texttt{mask} it will contain \texttt{FLT\_MAX}.}
\cvarg{allDist} {Buffer to store all distances between query descriptors and train descriptors. It will have $\texttt{nQuery} \times \texttt{nTrain}$ size and \texttt{CV\_32FC1} type. \texttt{allDist.at<float>(queryIdx, trainIdx)} will contain \texttt{FLT\_MAX}, if \texttt{trainIdx} is one from k best, otherwise it will contain distance between \texttt{queryIdx} and \texttt{trainIdx} descriptors.}
\cvarg{k}{Number of the best matches will be found per each query descriptor (or less if it's not possible).}
\cvarg{mask}{Mask specifying permissible matches between input query and train matrices of descriptors.}