From 1aed6ade0f84f6d7b819289edffa8236295586bd Mon Sep 17 00:00:00 2001
From: Scott Klum <scott.klum@gmail.com>
Date: Fri, 26 Dec 2014 10:58:39 -0500
Subject: [PATCH] Added additional SVM parameters

---
 openbr/plugins/svm.cpp | 32 ++++++++++++++++++++++++++------
 1 file changed, 26 insertions(+), 6 deletions(-)

diff --git a/openbr/plugins/svm.cpp b/openbr/plugins/svm.cpp
index ad4594f..b80901e 100644
--- a/openbr/plugins/svm.cpp
+++ b/openbr/plugins/svm.cpp
@@ -59,7 +59,7 @@ static void loadSVM(SVM &svm, QDataStream &stream)
     svm.load(qPrintable(tempFile.fileName()));
 }
 
-static void trainSVM(SVM &svm, Mat data, Mat lab, int kernel, int type, float C, float gamma)
+static void trainSVM(SVM &svm, Mat data, Mat lab, int kernel, int type, float C, float gamma, int folds, bool balanceFolds, int termCriteria)
 {
     if (data.type() != CV_32FC1)
         qFatal("Expected single channel floating point training data.");
@@ -69,9 +69,18 @@ static void trainSVM(SVM &svm, Mat data, Mat lab, int kernel, int type, float C,
     params.svm_type = type;
     params.p = 0.1;
     params.nu = 0.5;
+    params.term_crit = cvTermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, termCriteria, FLT_EPSILON);
+
     if ((C == -1) || ((gamma == -1) && (kernel == CvSVM::RBF))) {
         try {
-            svm.train_auto(data, lab, Mat(), Mat(), params, 5);
+            svm.train_auto(data, lab, Mat(), Mat(), params, folds,
+                           CvSVM::get_default_grid(CvSVM::C),
+                           CvSVM::get_default_grid(CvSVM::GAMMA),
+                           CvSVM::get_default_grid(CvSVM::P),
+                           CvSVM::get_default_grid(CvSVM::NU),
+                           CvSVM::get_default_grid(CvSVM::COEF),
+                           CvSVM::get_default_grid(CvSVM::DEGREE),
+                           balanceFolds);
         } catch (...) {
             qWarning("Some classes do not contain sufficient examples or are not discriminative enough for accurate SVM classification.");
             svm.train(data, lab, Mat(), Mat(), params);
@@ -104,6 +113,9 @@ class SVMTransform : public Transform
     Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
     Q_PROPERTY(QString outputVariable READ get_outputVariable WRITE set_outputVariable RESET reset_outputVariable STORED false)
     Q_PROPERTY(bool returnDFVal READ get_returnDFVal WRITE set_returnDFVal RESET reset_returnDFVal STORED false)
+    Q_PROPERTY(int termCriteria READ get_termCriteria WRITE set_termCriteria RESET reset_termCriteria STORED false)
+    Q_PROPERTY(int folds READ get_folds WRITE set_folds RESET reset_folds STORED false)
+    Q_PROPERTY(bool balanceFolds READ get_balanceFolds WRITE set_balanceFolds RESET reset_balanceFolds STORED false)
 
 public:
     enum Kernel { Linear = CvSVM::LINEAR,
@@ -125,7 +137,9 @@ private:
     BR_PROPERTY(QString, inputVariable, "Label")
     BR_PROPERTY(QString, outputVariable, "")
     BR_PROPERTY(bool, returnDFVal, false)
-
+    BR_PROPERTY(int, termCriteria, 1000)
+    BR_PROPERTY(int, folds, 5)
+    BR_PROPERTY(bool, balanceFolds, false)
 
     SVM svm;
     QHash<QString, int> labelMap;
@@ -146,7 +160,8 @@ private:
             QList<int> dataLabels = _data.indexProperty(inputVariable, labelMap, reverseLookup);
             lab = OpenCVUtils::toMat(dataLabels);
         }
-        trainSVM(svm, data, lab, kernel, type, C, gamma);
+
+        trainSVM(svm, data, lab, kernel, type, C, gamma, folds, balanceFolds, termCriteria);
     }
 
     void project(const Template &src, Template &dst) const
@@ -207,7 +222,9 @@ class SVMDistance : public Distance
     Q_PROPERTY(Kernel kernel READ get_kernel WRITE set_kernel RESET reset_kernel STORED false)
     Q_PROPERTY(Type type READ get_type WRITE set_type RESET reset_type STORED false)
     Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
-
+    Q_PROPERTY(int termCriteria READ get_termCriteria WRITE set_termCriteria RESET reset_termCriteria STORED false)
+    Q_PROPERTY(int folds READ get_folds WRITE set_folds RESET reset_folds STORED false)
+    Q_PROPERTY(bool balanceFolds READ get_balanceFolds WRITE set_balanceFolds RESET reset_balanceFolds STORED false)
 
 public:
     enum Kernel { Linear = CvSVM::LINEAR,
@@ -225,6 +242,9 @@ private:
     BR_PROPERTY(Kernel, kernel, Linear)
     BR_PROPERTY(Type, type, EPS_SVR)
     BR_PROPERTY(QString, inputVariable, "Label")
+    BR_PROPERTY(int, termCriteria, 1000)
+    BR_PROPERTY(int, folds, 5)
+    BR_PROPERTY(bool, balanceFolds, false)
 
     SVM svm;
 
@@ -249,7 +269,7 @@ private:
         deltaData = deltaData.rowRange(0, index);
         deltaLab = deltaLab.rowRange(0, index);
 
-        trainSVM(svm, deltaData, deltaLab, kernel, type, -1, -1);
+        trainSVM(svm, deltaData, deltaLab, kernel, type, -1, -1, folds, balanceFolds, termCriteria);
     }
 
     float compare(const Mat &a, const Mat &b) const
--
libgit2 0.21.4