Update target variable names for age/gender prediction

Charles Otto
1 parent 74b9008f
Showing 6 changed files with 11 additions and 22 deletions
app/examples/age_estimation.cpp
app/examples/gender_estimation.cpp
openbr/frvt2012.cpp
openbr/gui/classifier.cpp
openbr/openbr.cpp
openbr/plugins/algorithms.cpp
@@ -29,8 +29,7 @@
 static void printTemplate(const br::Template &t)
 {
-    // may use age directly -cao
-    printf("%s age: %d\n", qPrintable(t.file.fileName()), int(t.file.get<float>("Regressand")));
+    printf("%s age: %d\n", qPrintable(t.file.fileName()), int(t.file.get<float>("Age")));
 }
 int main(int argc, char *argv[])
@@ -29,8 +29,7 @@
 static void printTemplate(const br::Template &t)
 {
-    // may use gender directly -cao
-    printf("%s gender: %s\n", qPrintable(t.file.fileName()), qPrintable(t.file.get<QString>("Label")));
+    printf("%s gender: %s\n", qPrintable(t.file.fileName()), qPrintable(t.file.get<QString>("Gender")));
 }
 int main(int argc, char *argv[])
@@ -132,8 +132,7 @@ int32_t SdkEstimator::estimate_age(const ONEFACE &amp;input_face, int32_t &amp;age)
     TemplateList templates;
     templates.append(templateFromONEFACE(input_face));
     templates >> *frvt2012_age_transform.data();
-    // should maybe use "Age" directly -cao
-    age = templates.first().file.get<float>("Regressand");
+    age = templates.first().file.get<float>("Age");
     return templates.first().file.failed() ? 4 : 0;
 }
@@ -142,7 +141,6 @@ int32_t SdkEstimator::estimate_gender(const ONEFACE &amp;input_face, int8_t &amp;gender,
     TemplateList templates;
     templates.append(templateFromONEFACE(input_face));
     templates >> *frvt2012_gender_transform.data();
-    // Should maybe use "Gender" directly -cao
-    mf = gender = templates.first().file.get<QString>("Label") == "Male" ? 0 : 1;
+    mf = gender = templates.first().file.get<QString>("Gender") == "Male" ? 0 : 1;
     return templates.first().file.failed() ? 4 : 0;
 }
@@ -43,13 +43,11 @@ void Classifier::_classify(File file)
             continue;
         if (algorithm == "GenderClassification") {
-            // Should maybe use gender directly -cao
             key = "Gender";
-            value = f.get<QString>("Label");
+            value = f.get<QString>(key);
         } else if (algorithm == "AgeRegression") {
             key = "Age";
-            // similarly, age -cao
-            value = QString::number(int(f.get<float>("Regressand")+0.5)) + " Years";
+            value = QString::number(int(f.get<float>(key)+0.5)) + " Years";
         } else {
             key = algorithm;
             value = f.get<QString>("Label");
@@ -79,12 +79,7 @@ float br_eval(const char *simmat, const char *mask, const char *csv)
 void br_eval_classification(const char *predicted_input, const char *truth_input, const char *predicted_property, const char * truth_property)
 {
-    if (predicted_property && truth_property)
-        EvalClassification(predicted_input, truth_input, predicted_property, truth_property);
-    else if (predicted_property)
-        EvalClassification(predicted_input, truth_input, predicted_property);
-    else
-        EvalClassification(predicted_input, truth_input);
+    EvalClassification(predicted_input, truth_input, predicted_property, truth_property);
 }
 void br_eval_clustering(const char *csv, const char *input)
@@ -92,9 +87,9 @@ void br_eval_clustering(const char *csv, const char *input)
     EvalClustering(csv, input);
 }
-void br_eval_regression(const char *predicted_input, const char *truth_input)
+void br_eval_regression(const char *predicted_input, const char *truth_input, const char * predicted_property, const char * truth_property)
 {
-    EvalRegression(predicted_input, truth_input);
+    EvalRegression(predicted_input, truth_input, predicted_property, truth_property);
 }
 void br_finalize()
@@ -75,8 +75,8 @@ class AlgorithmsInitializer : public Initializer
         Globals->abbreviations.insert("FaceRecognitionQuantization", "(Normalize(L1)+Quantize)");
         Globals->abbreviations.insert("FaceClassificationRegistration", "(ASEFEyes+Affine(56,72,0.33,0.45)+FTE(DFFS))");
         Globals->abbreviations.insert("FaceClassificationExtraction", "((Grid(7,7)+SIFTDescriptor(8)+ByRow)/DenseLBP+PCA(0.95,instances=-1)+Cat)");
-        Globals->abbreviations.insert("AgeRegressor", "Center(Range,instances=-1)+SVM(RBF,EPS_SVR,instances=100)");
-        Globals->abbreviations.insert("GenderClassifier", "Center(Range,instances=-1)+SVM(RBF,C_SVC,instances=4000)");
+        Globals->abbreviations.insert("AgeRegressor", "Center(Range,instances=-1)+SVM(RBF,EPS_SVR,inputVariable=Age,instances=100)");
+        Globals->abbreviations.insert("GenderClassifier", "Center(Range,instances=-1)+SVM(RBF,C_SVC,inputVariable=Gender,instances=4000)");
         Globals->abbreviations.insert("UCharL1", "Unit(ByteL1)");
     }
 };