Joe Verbout
opencv on mbed
ConjGradSolver Class Reference
[Optimization Algorithms]
This class is used to perform the non-linear non-constrained minimization of a function with known gradient,. More...
#include <optim.hpp>
Inherits cv::MinProblemSolver.
Public Member Functions | |
| virtual Ptr< Function > | getFunction () const =0 |
| Getter for the optimized function. | |
| virtual void | setFunction (const Ptr< Function > &f)=0 |
| Setter for the optimized function. | |
| virtual TermCriteria | getTermCriteria () const =0 |
| Getter for the previously set terminal criteria for this algorithm. | |
| virtual void | setTermCriteria (const TermCriteria &termcrit)=0 |
| Set terminal criteria for solver. | |
| virtual double | minimize (InputOutputArray x)=0 |
| actually runs the algorithm and performs the minimization. | |
| virtual CV_WRAP void | clear () |
| Clears the algorithm state. | |
| virtual void | write (FileStorage &fs) const |
| Stores algorithm parameters in a file storage. | |
| virtual void | read (const FileNode &fn) |
| Reads algorithm parameters from a file storage. | |
| virtual bool | empty () const |
| Returns true if the Algorithm is empty (e.g. | |
| virtual CV_WRAP void | save (const String &filename) const |
| Saves the algorithm to a file. | |
| virtual CV_WRAP String | getDefaultName () const |
| Returns the algorithm string identifier. | |
Static Public Member Functions | |
| static Ptr< ConjGradSolver > | create (const Ptr< MinProblemSolver::Function > &f=Ptr< ConjGradSolver::Function >(), TermCriteria termcrit=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5000, 0.000001)) |
| This function returns the reference to the ready-to-use ConjGradSolver object. | |
| template<typename _Tp > | |
| static Ptr< _Tp > | read (const FileNode &fn) |
| Reads algorithm from the file node. | |
| template<typename _Tp > | |
| static Ptr< _Tp > | load (const String &filename, const String &objname=String()) |
| Loads algorithm from the file. | |
| template<typename _Tp > | |
| static Ptr< _Tp > | loadFromString (const String &strModel, const String &objname=String()) |
| Loads algorithm from a String. | |
Detailed Description
This class is used to perform the non-linear non-constrained minimization of a function with known gradient,.
defined on an *n*-dimensional Euclidean space, using the **Nonlinear Conjugate Gradient method**. The implementation was done based on the beautifully clear explanatory article [An Introduction to the Conjugate Gradient Method Without the Agonizing Pain](http://www.cs.cmu.edu/~quake-papers/painless-conjugate-gradient.pdf) by Jonathan Richard Shewchuk. The method can be seen as an adaptation of a standard Conjugate Gradient method (see, for example <http://en.wikipedia.org/wiki/Conjugate_gradient_method>) for numerically solving the systems of linear equations.
It should be noted, that this method, although deterministic, is rather a heuristic method and therefore may converge to a local minima, not necessary a global one. What is even more disastrous, most of its behaviour is ruled by gradient, therefore it essentially cannot distinguish between local minima and maxima. Therefore, if it starts sufficiently near to the local maximum, it may converge to it. Another obvious restriction is that it should be possible to compute the gradient of a function at any point, thus it is preferable to have analytic expression for gradient and computational burden should be born by the user.
The latter responsibility is accompilished via the getGradient method of a MinProblemSolver::Function interface (which represents function being optimized). This method takes point a point in *n*-dimensional space (first argument represents the array of coordinates of that point) and comput its gradient (it should be stored in the second argument as an array).
- Note:
- class ConjGradSolver thus does not add any new methods to the basic MinProblemSolver interface.
-
term criteria should meet following condition:
termcrit.type == (TermCriteria::MAX_ITER + TermCriteria::EPS) && termcrit.epsilon > 0 && termcrit.maxCount > 0 // or termcrit.type == TermCriteria::MAX_ITER) && termcrit.maxCount > 0
Definition at line 236 of file optim.hpp.
Member Function Documentation
| virtual CV_WRAP void clear | ( | ) | [virtual, inherited] |
Clears the algorithm state.
Reimplemented in DescriptorMatcher, and FlannBasedMatcher.
| static Ptr<ConjGradSolver> create | ( | const Ptr< MinProblemSolver::Function > & | f = Ptr< ConjGradSolver::Function >(), |
| TermCriteria | termcrit = TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5000, 0.000001) |
||
| ) | [static] |
This function returns the reference to the ready-to-use ConjGradSolver object.
All the parameters are optional, so this procedure can be called even without parameters at all. In this case, the default values will be used. As default value for terminal criteria are the only sensible ones, MinProblemSolver::setFunction() should be called upon the obtained object, if the function was not given to create(). Otherwise, the two ways (submit it to create() or miss it out and call the MinProblemSolver::setFunction()) are absolutely equivalent (and will drop the same errors in the same way, should invalid input be detected).
- Parameters:
-
f Pointer to the function that will be minimized, similarly to the one you submit via MinProblemSolver::setFunction. termcrit Terminal criteria to the algorithm, similarly to the one you submit via MinProblemSolver::setTermCriteria.
| virtual bool empty | ( | ) | const [virtual, inherited] |
| virtual CV_WRAP String getDefaultName | ( | ) | const [virtual, inherited] |
Returns the algorithm string identifier.
This string is used as top level xml/yml node tag when the object is saved to a file or string.
Getter for the optimized function.
The optimized function is represented by Function interface, which requires derivatives to implement the sole method calc(double*) to evaluate the function.
- Returns:
- Smart-pointer to an object that implements Function interface - it represents the function that is being optimized. It can be empty, if no function was given so far.
| virtual TermCriteria getTermCriteria | ( | ) | const [pure virtual, inherited] |
Getter for the previously set terminal criteria for this algorithm.
- Returns:
- Deep copy of the terminal criteria used at the moment.
| static Ptr<_Tp> load | ( | const String & | filename, |
| const String & | objname = String() |
||
| ) | [static, inherited] |
Loads algorithm from the file.
- Parameters:
-
filename Name of the file to read. objname The optional name of the node to read (if empty, the first top-level node will be used)
This is static template method of Algorithm. It's usage is following (in the case of SVM):
Ptr<SVM> svm = Algorithm::load<SVM>("my_svm_model.xml");
In order to make this method work, the derived class must overwrite Algorithm::read(const FileNode& fn).
| static Ptr<_Tp> loadFromString | ( | const String & | strModel, |
| const String & | objname = String() |
||
| ) | [static, inherited] |
Loads algorithm from a String.
- Parameters:
-
strModel The string variable containing the model you want to load. objname The optional name of the node to read (if empty, the first top-level node will be used)
This is static template method of Algorithm. It's usage is following (in the case of SVM):
Ptr<SVM> svm = Algorithm::loadFromString<SVM>(myStringModel);
| virtual double minimize | ( | InputOutputArray | x ) | [pure virtual, inherited] |
actually runs the algorithm and performs the minimization.
The sole input parameter determines the centroid of the starting simplex (roughly, it tells where to start), all the others (terminal criteria, initial step, function to be minimized) are supposed to be set via the setters before the call to this method or the default values (not always sensible) will be used.
- Parameters:
-
x The initial point, that will become a centroid of an initial simplex. After the algorithm will terminate, it will be setted to the point where the algorithm stops, the point of possible minimum.
- Returns:
- The value of a function at the point found.
| virtual void read | ( | const FileNode & | fn ) | [virtual, inherited] |
Reads algorithm parameters from a file storage.
Reimplemented in DescriptorMatcher, and FlannBasedMatcher.
Reads algorithm from the file node.
This is static template method of Algorithm. It's usage is following (in the case of SVM):
Ptr<SVM> svm = Algorithm::read<SVM>(fn);
In order to make this method work, the derived class must overwrite Algorithm::read(const FileNode& fn) and also have static create() method without parameters (or with all the optional parameters)
Reimplemented in DescriptorMatcher, and FlannBasedMatcher.
| virtual CV_WRAP void save | ( | const String & | filename ) | const [virtual, inherited] |
Saves the algorithm to a file.
In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).
Setter for the optimized function.
It should be called at least once before the call to* minimize(), as default value is not usable.
- Parameters:
-
f The new function to optimize.
| virtual void setTermCriteria | ( | const TermCriteria & | termcrit ) | [pure virtual, inherited] |
Set terminal criteria for solver.
This method *is not necessary* to be called before the first call to minimize(), as the default value is sensible.
Algorithm stops when the number of function evaluations done exceeds termcrit.maxCount, when the function values at the vertices of simplex are within termcrit.epsilon range or simplex becomes so small that it can enclosed in a box with termcrit.epsilon sides, whatever comes first.
- Parameters:
-
termcrit Terminal criteria to be used, represented as cv::TermCriteria structure.
| virtual void write | ( | FileStorage & | fs ) | const [virtual, inherited] |
Stores algorithm parameters in a file storage.
Reimplemented in DescriptorMatcher, and FlannBasedMatcher.
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