Implementation of affinity propagation prototype based on opencv ml

The Spring Festival Implementation of apcluster will try to submit it to opencv ml together with RBM when it is available recently. This is a prototype code that lacks many error control procedures, but supports cvsparsemat.

Mlapcluster. h

# Ifndef guard_mlapcluster_h <br/> # define guard_mlapcluster_h <br/> # include <ml. h> <br/> # define cv_type_name_ml_apcluster "opencv-ml-affinity-propagation-cluster" <br/> struct cv_exports cvapcparams <br/>{< br/> int maxiteration; <br/> int stopcriterion; <br/> double Lambda; <br/> cvapcparams () <br/>: maxiteration (2000), <br/> stopcriterion (200 ), <br/> Lambda (0.9) <br/>{}< br/> cvapcparams (INT _ maxiterati On, int _ stopcriterion, double _ lambda) <br/>: maxiteration (_ maxiteration), <br/> stopcriterion (_ stopcriterion), <br/> Lambda (_ lambda) <br/>{}< br/>}; <br/> class cv_exports cvapcluster: Public cvstatmodel <br/>{< br/> PRIVATE: <br/> cvapcparams * Params; <br/> Public: <br/> cvapcluster (cvapcparams * _ Params) <br/>: Params (_ Params) <br/>{}< br/> virtual ~ Cvapcluster () <br/>{< br/> clear (); <br/>}< br/> virtual bool train (const cvmat * _ train_data, const cvmat * _ response); <br/> virtual bool train (const cvsparsemat * _ train_data, const cvmat * _ response); <br/> virtual void clear (); <br/> virtual void write (cvfilestorage * FS, const char * Name); <br/> virtual void read (cvfilestorage * FS, cvfilenode * root_node ); <br/>}; <br/> # endif

Mlapcluster. cpp

# Include "mlapcluster. H "<br/> # include <limits> <br/> bool cvapcluster: train (const cvmat * similarity, <br/> const cvmat * labels) <br/>{< br/> int stop = 0; <br/> cv_funcname ("cvapcluster: Train"); <br/>__ begin __; <br/> cvmat * RSP; <br/> cvmat * aVL; <br/> int * rspmaxidx; <br/> double * rspmaxval; <br/> double * rspmaxval2; <br/> double * diagrsp; <br/> double & Lam = Params-> Lambda; <br/> double _ Lam = 1. -Lam; <Br/> int num; <br/> If (! Cv_is_mat (similarity) | similarity-> rows! = Similarity-> Cols | cv_mat_type (similarity-> type )! = Cv_64fc1) <br/> cv_error (cv_stsbadarg, <br/> "similarity matrix is a double-point matrix with equal rows and Cols "); </P> <p> num = similarity-> rows; <br/> If (! Cv_is_mat (labels) | labels-> Cols! = Num | cv_mat_type (labels-> type )! = Cv_32sc1) <br/> cv_error (cv_stsbadarg, <br/> "labels array (when passed) must be a valid 1D integer vector of <sample_count> elements "); <br/> RSp = cvcreatemat (Num, num, cv_64fc1); <br/> AVL = cvcreatemat (Num, num, cv_64fc1); <br/> cvzero (RSP ); <br/> cvzero (AVL); </P> <p> rspmaxidx = (int *) cvalloc (Num * sizeof (rspmaxidx [0]); <br/> rspmaxval = (double *) cvalloc (Num * sizeof (rspmaxval [0]); <br/> Rspmaxval2 = (double *) cvalloc (Num * sizeof (rspmaxval2 [0]); <br/> diagrsp = (double *) cvalloc (Num * sizeof (diagrsp [0]); <br/> for (int K = 0; k <Params-> maxiteration; k ++) <br/>{< br/> double * rsp_vec = RSP-> data. DB; <br/> double * avl_vec = AVL-> data. DB; <br/> double * sim_vec = similarity-> data. DB; <br/> double * sim_vec2 = sim_vec; <br/> for (INT I = 0; I <num; I ++) <br/>{< br/> int yk =-1; <br/> do Uble y =-STD: numeric_limits <double >:: max (), y2 =-STD: numeric_limits <double >:: max (); <br/> for (Int J = 0; j <num; j ++) <br/>{< br/> double T = * sim_vec2 + * avl_vec; <br/> If (T> Y) <br/>{< br/> Y = T; <br/> yk = J; <br/>} else if (T> Y2) <br/> Y2 = T; <br/> sim_vec2 ++; <br/> avl_vec ++; <br/>}< br/> for (Int J = 0; j <num; j ++) <br/>{< br/> If (J! = Yk) <br/> * rsp_vec = * rsp_vec * Lam + (* sim_vec-y) * _ Lam; <br/> else <br/> * rsp_vec = * rsp_vec * Lam + (* sim_vec-y2) * _ Lam; <br/> rsp_vec ++; <br/> sim_vec ++; <br/>}< br/> int * rspmaxidx_vec = rspmaxidx; <br/> double * rspmaxval_vec = rspmaxval; <br/> double * rspmaxval2_vec = rspmaxval2; <br/> for (INT I = 0; I <num; I ++, rspmaxidx_vec ++, rspmaxval_vec ++, rspmaxval2_vec ++) <br/>{< br/> * rspmaxidx_vec =-1; <Br/> * rspmaxval_vec = 0; <br/> * rspmaxval2_vec = 0; <br/>}< br/> rsp_vec = RSP-> data. DB; <br/> double * diagrsp_vec = diagrsp; <br/> for (INT I = 0; I <num; I ++, diagrsp_vec ++) <br/>{< br/> rspmaxidx_vec = rspmaxidx; <br/> rspmaxval_vec = rspmaxval; <br/> rspmaxval2_vec = rspmaxval2; <br/> for (Int J = 0; j <num; j ++, rspmaxidx_vec ++, rspmaxval_vec ++, rspmaxval2_vec ++) <br/>{< br/> if (I! = J) <br/>{< br/> If (* rsp_vec> * rspmaxval_vec) <br/>{< br/> * rspmaxidx_vec = I; <br/> * rspmaxval_vec = * rsp_vec; <br/>} else if (* rsp_vec> * rspmaxval2_vec) <br/> * rspmaxval2_vec = * rsp_vec; <br/>} else <br/> * diagrsp_vec = * rsp_vec; <br/> rsp_vec ++; <br/>}< br/> avl_vec = AVL-> data. DB; <br/> diagrsp_vec = diagrsp; <br/> for (INT I = 0; I <num; I ++, diagrsp_vec ++) <br/>{< br/> rspmaxidx_vec = Rspmaxidx; <br/> rspmaxval_vec = rspmaxval; <br/> rspmaxval2_vec = rspmaxval2; <br/> for (Int J = 0; j <num; j ++, rspmaxidx_vec ++, rspmaxval_vec ++, rspmaxval2_vec ++) <br/>{< br/> double TMP; <br/> if (I! = J) <br/>{< br/> if (I! = * Rspmaxidx_vec) <br/> TMP = * diagrsp_vec + * rspmaxval_vec; <br/> else <br/> TMP = * diagrsp_vec + * rspmaxval2_vec; <br/> If (TMP> 0) <br/> TMP = 0; <br/>} else <br/> TMP = * rspmaxval_vec; <br/> * avl_vec = * avl_vec * Lam + TMP * _ Lam; <br/> avl_vec ++; <br/>}< br/> stop ++; <br/> int * cls_vec = labels-> data. i; <br/> rsp_vec = RSP-> data. DB; <br/> avl_vec = AVL-> data. DB; <br/> for (INT I = 0; I <num; I ++, Cl S_vec ++) <br/>{< br/> int maxidx = I; <br/> double maxval =-STD: numeric_limits <double >:: max (); <br/> for (Int J = 0; j <num; j ++) <br/>{< br/> double T = * rsp_vec + * avl_vec; <br/> If (T> maxval) <br/>{< br/> maxval = T; <br/> maxidx = J; <br/>}< br/> rsp_vec ++; <br/> avl_vec ++; <br/>}< br/> If (* cls_vec! = Maxidx) <br/> stop = 0; <br/> * cls_vec = maxidx; <br/>}< br/> If (stop> Params-> stopcriterion) <br/> break; <br/>}< br/> cvfree (& diagrsp); <br/> cvfree (& rspmaxval2 ); <br/> cvfree (& rspmaxval); <br/> cvfree (& rspmaxidx); <br/> cvreleasemat (& AVL); <br/> cvreleasemat (& RSP ); <br/>__ end __; <br/> return stop> Params-> stopcriterion; <br/>}< br/> struct cvsparsenode2d <br/>{< br/> int I; <br/> int K; <br /> Double val; <br/>}; <br/> bool <br/> cvapcluster: train (const cvsparsemat * similarity, <br/> const cvmat * labels) <br/>{< br/> int stop = 0; <br/> cv_funcname ("cvapcluster: Train"); <br/>__ begin __; <br/> int * psize; <br/> int * psize_vec; <br/> int num; <br/> double * RSP; <br/> double * aVL; <br/> double * rsp_vec; <br/> double * avl_vec; <br/> cvsparsenode2d * nodes; <br/> cvsparsenode2d ** node_entries; <br /> Int * rspmaxidx; <br/> double * rspmaxval; <br/> double * rspmaxval2; <br/> double * diagrsp; <br/> int Total = 0; <br/> double & Lam = Params-> Lambda; <br/> double _ Lam = 1. -lam; <br/> If (! Cv_is_sparse_mat (similarity) | similarity-> dims! = 2 | similarity-> size [0]! = Similarity-> size [1] | cv_mat_type (similarity-> type )! = Cv_64fc1) <br/> cv_error (cv_stsbadarg, <br/> "similarity matrix is a double-point sparse matrix with equal rows and Cols "); <br/> num = similarity-> size [0]; <br/> If (! Cv_is_mat (labels) | labels-> Cols! = Num | cv_mat_type (labels-> type )! = Cv_32sc1) <br/> cv_error (cv_stsbadarg, <br/> "labels array (when passed) must be a valid 1D integer vector of <sample_count> elements "); <br/> psize = (int *) cvalloc (Num * sizeof (psize [0]); <br/> psize_vec = psize; <br/> for (INT I = 0; I <num; I ++, psize_vec ++) <br/> * psize_vec = 0; <br/> cvsparsematiterator mat_iterator; <br/> cvsparsenode * node; <br/> node = cvinitsparsematiterator (similarity ,& Mat_iterator); <br/> for (; node! = 0; node = cvgetnextsparsenode (& mat_iterator) <br/>{< br/> const int * idx = cv_node_idx (similarity, node ); <br/> psize [idx [0] ++; <br/> total ++; <br/>}< br/> RSp = (double *) cvalloc (total * sizeof (RSP [0]); <br/> AVL = (double *) cvalloc (total * sizeof (AVL [0]); <br/> rsp_vec = RSP; <br/> avl_vec = aVL; <br/> nodes = (cvsparsenode2d *) cvalloc (total * sizeof (nodes [0]); <br/> node_entries = (cvsparsenode2 D **) cvalloc (Num * sizeof (node_entries [0]); <br/> psize_vec = psize; <br/> node_entries [0] = nodes; <br/> for (INT I = 1; I <num; I ++, psize_vec ++) <br/> node_entries [I] = node_entries [I-1] + * psize_vec; <br/> node = cvinitsparsematiterator (similarity, & mat_iterator); <br/> for (; node! = 0; node = cvgetnextsparsenode (& mat_iterator), rsp_vec ++, avl_vec ++) <br/>{< br/> * rsp_vec = * avl_vec = 0; <br/> const int * idx = cv_node_idx (similarity, node); <br/> cvsparsenode2d * & node_entry = node_entries [idx [0]; <br/> node_entry-> I = idx [0]; <br/> node_entry-> K = idx [1]; <br/> node_entry-> val = * (double *) cv_node_val (similarity, node); <br/> node_entry ++; <br/>}< br/> cvfree (& node_entries ); <Br/> rspmaxidx = (int *) cvalloc (Num * sizeof (rspmaxidx [0]); <br/> rspmaxval = (double *) cvalloc (Num * sizeof (rspmaxval [0]); <br/> rspmaxval2 = (double *) cvalloc (Num * sizeof (rspmaxval2 [0]); <br/> diagrsp = (double *) cvalloc (Num * sizeof (diagrsp [0]); <br/> for (int K = 0; k <Params-> maxiteration; k ++) <br/>{< br/> cvsparsenode2d * nodes_vec = nodes; <br/> psize_vec = psize; <br/> cvsparsenode2d * nodes _ Vec2 = nodes; <br/> avl_vec = aVL; <br/> rsp_vec = RSP; <br/> for (INT I = 0; I <num; I ++, psize_vec ++) <br/>{< br/> int yk =-1; <br/> double y =-STD: numeric_limits <double >:: max (), y2 =-STD: numeric_limits <double >:: max (); <br/> for (Int J = 0; j <* psize_vec; j ++) <br/>{< br/> double T = nodes_vec2-> Val + * avl_vec; <br/> If (T> Y) <br/>{< br/> Y = T; <br/> yk = nodes_vec2-> K; <br/>} else if (T> Y2) <br/> Y2 = T; <br/> nodes_vec2 ++; <br/> avl_vec ++; <br/>}< br/> for (Int J = 0; j <* psize_vec; j ++) <br/>{< br/> If (nodes_vec-> K! = Yk) <br/> * rsp_vec = * rsp_vec * Lam + (nodes_vec-> Val-y) * _ Lam; <br/> else <br/> * rsp_vec = * rsp_vec * Lam + (nodes_vec-> val-y2) * _ Lam; <br/> nodes_vec ++; <br/> rsp_vec ++; <br/>}< br/> int * rspmaxidx_vec = rspmaxidx; <br/> double * rspmaxval_vec = rspmaxval; <br/> double * rspmaxval2_vec = rspmaxval2; <br/> for (INT I = 0; I <num; I ++, rspmaxidx_vec ++, rspmaxval_vec ++, rspmaxval2_vec ++) <br/>{< br/> * rspmax Idx_vec =-1; <br/> * rspmaxval_vec = 0; <br/> * rspmaxval2_vec = 0; <br/>}< br/> rsp_vec = RSP; <br/> psize_vec = psize; <br/> nodes_vec = nodes; <br/> double * diagrsp_vec = diagrsp; <br/> for (INT I = 0; I <num; I ++, psize_vec ++, diagrsp_vec ++) <br/> for (Int J = 0; j <* psize_vec; j ++) <br/>{< br/> if (I! = Nodes_vec-> K) <br/> {<br/> If (* rsp_vec> rspmaxval [nodes_vec-> K]) <br/>{< br/> rspmaxidx [nodes_vec-> K] = I; <br/> rspmaxval [nodes_vec-> K] = * rsp_vec; <br/>} else if (* rsp_vec> rspmaxval2 [nodes_vec-> K]) <br/> rspmaxval2 [nodes_vec-> K] = * rsp_vec; <br/>} else <br/> * diagrsp_vec = * rsp_vec; <br/> nodes_vec ++; <br/> rsp_vec ++; <br/>}< br/> avl_vec = aVL; <br/> diagrsp_vec = diagrsp; <br/> psize_vec = PSI Ze; <br/> nodes_vec = nodes; <br/> for (INT I = 0; I <num; I ++, psize_vec ++, diagrsp_vec ++) <br/> for (Int J = 0; j <* psize_vec; j ++) <br/>{< br/> double TMP; <br/> if (I! = Nodes_vec-> K) <br/>{< br/> if (I! = Rspmaxidx [nodes_vec-> K]) <br/> TMP = * diagrsp_vec + rspmaxval [nodes_vec-> K]; <br/> else <br/> TMP = * diagrsp_vec + rspmaxval2 [nodes_vec-> K]; <br/> If (TMP> 0) <br/> TMP = 0; <br/>} else <br/> TMP = rspmaxval [nodes_vec-> K]; <br/> * avl_vec = * avl_vec * Lam + TMP * _ Lam; <br/> nodes_vec ++; <br/> avl_vec ++; <br/>}< br/> stop ++; <br/> int * cls_vec = labels-> data. i; <br/> rsp_vec = RSP; <br/> avl_vec = aVL; <br/> psiz E_vec = psize; <br/> nodes_vec = nodes; <br/> for (INT I = 0; I <num; I ++, psize_vec ++, cls_vec ++) <br/>{< br/> int maxidx = I; <br/> double maxval =-STD: numeric_limits <double >:: max (); <br/> for (Int J = 0; j <* psize_vec; j ++) <br/> {<br/> double T = * rsp_vec + * avl_vec; <br/> If (T> maxval) <br/>{< br/> maxval = T; <br/> maxidx = nodes_vec-> K; <br/>}< br/> nodes_vec ++; <br/> rsp_vec ++; <br/> avl_v EC ++; <br/>}< br/> If (* cls_vec! = Maxidx) <br/> stop = 0; <br/> * cls_vec = maxidx; <br/>}< br/> If (stop> Params-> stopcriterion) <br/> break; <br/>}< br/> cvfree (& diagrsp); <br/> cvfree (& rspmaxval2 ); <br/> cvfree (& rspmaxval); <br/> cvfree (& rspmaxidx); </P> <p> cvfree (& RSP ); <br/> cvfree (& AVL); <br/> cvfree (& psize); <br/> cvfree (& nodes); <br/>__ end __; <br/> return stop> Params-> stopcriterion; <br/>}< br/> void <br/> cvapcluster: clear () <br/>{< br/>}< br/> void <br/> cvapcluster: Write (cvfilestorage * FS, <br/> const char * name) <br/>{< br/>}< br/> void <br/> cvapcluster: Read (cvfilestorage * FS, <br/> cvfilenode * root_node) <br/>{< br/>}

Test example

# Include "mlapcluster. H "<br/> # include <iostream> <br/> int main () <br/> {<br/> cvapcparams * Params = new cvapcparams (2000,200, 0.5 ); <br/> cvapcluster * apcluster = new cvapcluster (Params); <br/> // cvmat * Dist = cvcreatemat (25, 25, cv_64fc1 ); <br/> int sizes [] = {25, 25}; <br/> cvsparsemat * Dist = cvcreatesparsemat (2, sizes, cv_64fc1 ); <br/> cvzero (DIST); <br/> freopen ("toyproblemsimilarities.txt", "r", stdin); <br/> double Total = 0; <br/> for (int K = 0; k <25*24; k ++) <br/> {<br/> int I, J; <br/> double D; <br/> STD: CIN> I> j> D; <br/> cvsetreal2d (Dist, I-1, J-1, d ); <br/> total + = D; <br/>}< br/> total =-15.561256; <br/> // Total = total/(25*24 ); <br/> printf ("Preference: % F/N", total); <br/> for (int K = 0; k <25; k ++) <br/> cvsetreal2d (Dist, K, K, total); <br/> cvmat * response = cvcreatemat (1, 25, cv_32sc1); <br/> long T; <br/> T = cvgettickcount (); <br/> apcluster-> train (Dist, response); <br/> T = cvgettickcount ()-T; <br/> printf ("apcluster trained in % LLD Ms. /n ", T/1000000); <br/> for (INT I = 0; I <25; I ++) <br/> printf (" % d ", response-> data. I [I]); <br/> printf ("/N"); <br/> return 0; <br/>}