Peter M. Groen / openbr

Commit 60f9377867e8765b358bbd1288ed8bca2d6ad679

Authored by Scott Klum
1 parent 31ac65fc

Revert "Added additional options to SVM" 

This reverts commit 31ac65fc2826a05a49d85d4043b717b694af2db4.
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Showing 3 changed files with 7 additions and 22 deletions
.gitignore
  View file @60f9377
@@ -6,7 +6,6 @@ data/*/img @@ -6,7 +6,6 @@ data/*/img
6 data/*/vid 6 data/*/vid
7 data/PCSO/* 7 data/PCSO/*
8 data/lfpw 8 data/lfpw
9 -data/lfw  
10 build* 9 build*
11 scripts/results 10 scripts/results
12 11
openbr/plugins/stasm4.cpp
  View file @60f9377
@@ -186,7 +186,7 @@ private: @@ -186,7 +186,7 @@ private:
186 for (int j = 0; j < 3; j++, cnt++) 186 for (int j = 0; j < 3; j++, cnt++)
187 affine(i, j) = paramList[cnt]; 187 affine(i, j) = paramList[cnt];
188 affine(2, 2) = 1; 188 affine(2, 2) = 1;
189 - //affine = affine.inverse(); 189 + affine = affine.inverse();
190 Eigen::MatrixXf affineInv = affine.block(0, 0, 2, 3); 190 Eigen::MatrixXf affineInv = affine.block(0, 0, 2, 3);
191 Eigen::MatrixXf pointsT = points.transpose(); 191 Eigen::MatrixXf pointsT = points.transpose();
192 points = affineInv * pointsT; 192 points = affineInv * pointsT;
openbr/plugins/svm.cpp
  View file @60f9377
@@ -40,7 +40,6 @@ static void storeSVM(const SVM &amp;svm, QDataStream &amp;stream) @@ -40,7 +40,6 @@ static void storeSVM(const SVM &amp;svm, QDataStream &amp;stream)
40 tempFile.open(); 40 tempFile.open();
41 QByteArray data = tempFile.readAll(); 41 QByteArray data = tempFile.readAll();
42 tempFile.close(); 42 tempFile.close();
43 - qDebug() << "Storing" << data.size() << "bytes for SVM";  
44 stream << data; 43 stream << data;
45 } 44 }
46 45
@@ -60,7 +59,7 @@ static void loadSVM(SVM &amp;svm, QDataStream &amp;stream) @@ -60,7 +59,7 @@ static void loadSVM(SVM &amp;svm, QDataStream &amp;stream)
60 svm.load(qPrintable(tempFile.fileName())); 59 svm.load(qPrintable(tempFile.fileName()));
61 } 60 }
62 61
63 -static void trainSVM(SVM &svm, Mat data, Mat lab, int kernel, int type, float C, float gamma, int folds, bool balanceFolds, int termCriteria) 62 +static void trainSVM(SVM &svm, Mat data, Mat lab, int kernel, int type, float C, float gamma)
64 { 63 {
65 if (data.type() != CV_32FC1) 64 if (data.type() != CV_32FC1)
66 qFatal("Expected single channel floating point training data."); 65 qFatal("Expected single channel floating point training data.");
@@ -68,18 +67,11 @@ static void trainSVM(SVM &amp;svm, Mat data, Mat lab, int kernel, int type, float C, @@ -68,18 +67,11 @@ static void trainSVM(SVM &amp;svm, Mat data, Mat lab, int kernel, int type, float C,
68 CvSVMParams params; 67 CvSVMParams params;
69 params.kernel_type = kernel; 68 params.kernel_type = kernel;
70 params.svm_type = type; 69 params.svm_type = type;
71 - params.term_crit = cvTermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, termCriteria, FLT_EPSILON);  
72 - 70 + params.p = 0.1;
  71 + params.nu = 0.5;
73 if ((C == -1) || ((gamma == -1) && (kernel == CvSVM::RBF))) { 72 if ((C == -1) || ((gamma == -1) && (kernel == CvSVM::RBF))) {
74 try { 73 try {
75 - svm.train_auto(data, lab, Mat(), Mat(), params, folds,  
76 - CvSVM::get_default_grid(CvSVM::C),  
77 - CvSVM::get_default_grid(CvSVM::GAMMA),  
78 - CvSVM::get_default_grid(CvSVM::P),  
79 - CvSVM::get_default_grid(CvSVM::NU),  
80 - CvSVM::get_default_grid(CvSVM::COEF),  
81 - CvSVM::get_default_grid(CvSVM::DEGREE),  
82 - balanceFolds); 74 + svm.train_auto(data, lab, Mat(), Mat(), params, 5);
83 } catch (...) { 75 } catch (...) {
84 qWarning("Some classes do not contain sufficient examples or are not discriminative enough for accurate SVM classification."); 76 qWarning("Some classes do not contain sufficient examples or are not discriminative enough for accurate SVM classification.");
85 svm.train(data, lab, Mat(), Mat(), params); 77 svm.train(data, lab, Mat(), Mat(), params);
@@ -112,9 +104,6 @@ class SVMTransform : public Transform @@ -112,9 +104,6 @@ class SVMTransform : public Transform
112 Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false) 104 Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
113 Q_PROPERTY(QString outputVariable READ get_outputVariable WRITE set_outputVariable RESET reset_outputVariable STORED false) 105 Q_PROPERTY(QString outputVariable READ get_outputVariable WRITE set_outputVariable RESET reset_outputVariable STORED false)
114 Q_PROPERTY(bool returnDFVal READ get_returnDFVal WRITE set_returnDFVal RESET reset_returnDFVal STORED false) 106 Q_PROPERTY(bool returnDFVal READ get_returnDFVal WRITE set_returnDFVal RESET reset_returnDFVal STORED false)
115 - Q_PROPERTY(int termCriteria READ get_termCriteria WRITE set_termCriteria RESET reset_termCriteria STORED false)  
116 - Q_PROPERTY(int folds READ get_folds WRITE set_folds RESET reset_folds STORED false)  
117 - Q_PROPERTY(bool balanceFolds READ get_balanceFolds WRITE set_balanceFolds RESET reset_balanceFolds STORED false)  
118 107
119 public: 108 public:
120 enum Kernel { Linear = CvSVM::LINEAR, 109 enum Kernel { Linear = CvSVM::LINEAR,
@@ -136,9 +125,7 @@ private: @@ -136,9 +125,7 @@ private:
136 BR_PROPERTY(QString, inputVariable, "Label") 125 BR_PROPERTY(QString, inputVariable, "Label")
137 BR_PROPERTY(QString, outputVariable, "") 126 BR_PROPERTY(QString, outputVariable, "")
138 BR_PROPERTY(bool, returnDFVal, false) 127 BR_PROPERTY(bool, returnDFVal, false)
139 - BR_PROPERTY(int, termCriteria, 1000)  
140 - BR_PROPERTY(int, folds, 5)  
141 - BR_PROPERTY(bool, balanceFolds, false) 128 +
142 129
143 SVM svm; 130 SVM svm;
144 QHash<QString, int> labelMap; 131 QHash<QString, int> labelMap;
@@ -159,8 +146,7 @@ private: @@ -159,8 +146,7 @@ private:
159 QList<int> dataLabels = _data.indexProperty(inputVariable, labelMap, reverseLookup); 146 QList<int> dataLabels = _data.indexProperty(inputVariable, labelMap, reverseLookup);
160 lab = OpenCVUtils::toMat(dataLabels); 147 lab = OpenCVUtils::toMat(dataLabels);
161 } 148 }
162 -  
163 - trainSVM(svm, data, lab, kernel, type, C, gamma, folds, balanceFolds, termCriteria); 149 + trainSVM(svm, data, lab, kernel, type, C, gamma);
164 } 150 }
165 151
166 void project(const Template &src, Template &dst) const 152 void project(const Template &src, Template &dst) const