From 9e9e1a9b627e2b045d06a98586887cbdd24f930d Mon Sep 17 00:00:00 2001
From: Scott Klum <scott.klum@gmail.com>
Date: Fri, 30 Jan 2015 12:51:23 -0500
Subject: [PATCH] More liblinear cleanup

---
 openbr/plugins/liblinear.cpp | 49 ++++++++++++++++++++++++++++++++-----------------
 1 file changed, 32 insertions(+), 17 deletions(-)

diff --git a/openbr/plugins/liblinear.cpp b/openbr/plugins/liblinear.cpp
index 7094b9a..7de2485 100644
--- a/openbr/plugins/liblinear.cpp
+++ b/openbr/plugins/liblinear.cpp
@@ -13,7 +13,7 @@ using namespace cv;
 namespace br
 {
 
-class LinearSVM : public Transform
+class Linear : public Transform
 {
     Q_OBJECT
     Q_ENUMS(Solver)
@@ -22,9 +22,7 @@ class LinearSVM : 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)
+    Q_PROPERTY(bool overwriteMat READ get_overwriteMat WRITE set_overwriteMat RESET reset_overwriteMat STORED false)
 
 public:
     enum Solver { L2R_LR,
@@ -45,9 +43,7 @@ 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)
+    BR_PROPERTY(bool, overwriteMat, true)
 
     model *m;
 
@@ -56,9 +52,6 @@ private:
         Mat samples = OpenCVUtils::toMat(data.data());
         Mat labels = OpenCVUtils::toMat(File::get<float>(data, inputVariable));
 
-        // Number of features = n
-        // Number of instances = l
-
         problem prob;
         prob.n = samples.cols;
         prob.l = samples.rows;
@@ -84,6 +77,7 @@ private:
         }
 
         parameter param;
+
         // TODO: Support grid search
         param.C = C;
         param.eps = FLT_EPSILON;
@@ -109,19 +103,40 @@ private:
         Mat sample = src.m().reshape(1,1);
         feature_node *x_space = new feature_node[sample.cols+1];
 
-        // Assign the address of the ith instance to be the address of the jth feature
         for (int j=0; j<sample.cols; j++) {
             x_space[j].index = j+1;
             x_space[j].value = sample.at<float>(0,j);
         }
         x_space[sample.cols].index = -1;
 
-        // TODO: Call appropriate function based on solver
-        double prob_estimates[1];
-        float prediction = predict_values(m,x_space,prob_estimates);
+        float prediction;
+        double prob_estimates[m->nr_class];
+
+        if (solver == L2R_L2LOSS_SVR        ||
+            solver == L2R_L1LOSS_SVR_DUAL   ||
+            solver == L2R_L2LOSS_SVR_DUAL   ||
+            solver == L2R_L2LOSS_SVC_DUAL   ||
+            solver == L2R_L2LOSS_SVC        ||
+            solver == L2R_L1LOSS_SVC_DUAL   ||
+            solver == MCSVM_CS              ||
+            solver == L1R_L2LOSS_SVC)
+        {
+            prediction = predict_values(m,x_space,prob_estimates);
+            if (returnDFVal) prediction = prob_estimates[0];
+        } else if (solver == L2R_LR         ||
+                   solver == L2R_LR_DUAL    ||
+                   solver == L1R_LR)
+        {
+            prediction = predict_probability(m,x_space,prob_estimates);
+            if (returnDFVal) prediction = prob_estimates[0];
+        }
 
-        dst.m() = Mat(1, 1, CV_32F);
-        dst.m().at<float>(0, 0) = prob_estimates[0];
+        if (overwriteMat) {
+            dst.m() = Mat(1, 1, CV_32F);
+            dst.m().at<float>(0, 0) = prediction;
+        } else {
+            dst.file.set(outputVariable,prediction);
+        }
 
         delete[] x_space;
     }
@@ -141,7 +156,7 @@ private:
     }
 };
 
-BR_REGISTER(Transform, LinearSVM)
+BR_REGISTER(Transform, Linear)
 
 } // namespace br
 
--
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