Change filter to minSize and brought up-to-date with master

root · Jordan Cheney
1 parent 7f645e54
Showing 5 changed files with 23 additions and 7 deletions
app/br/br.cpp
openbr/core/eval.cpp
openbr/core/eval.h
openbr/openbr.cpp
openbr/openbr.h
@@ -144,8 +144,8 @@ public:
                 check((parc >= 2) && (parc <= 3), "Incorrect parameter count for 'evalClustering'.");
                 br_eval_clustering(parv[0], parv[1], parc == 3 ? parv[2] : "");
             } else if (!strcmp(fun, "evalDetection")) {
-                check((parc >= 2) && (parc <= 4), "Incorrect parameter count for 'evalDetection'.");
-                br_eval_detection(parv[0], parv[1], parc >= 3 ? parv[2] : "", parc == 4 ? atoi(parv[3]) : 0);
+                check((parc >= 2) && (parc <= 5), "Incorrect parameter count for 'evalDetection'.");
+                br_eval_detection(parv[0], parv[1], parc >= 3 ? parv[2] : "", parc >= 4 ? atoi(parv[3]) : 0, parc == 5 ? atoi(parv[4]) : 0);
             } else if (!strcmp(fun, "evalLandmarking")) {
                 check((parc >= 2) && (parc <= 5), "Incorrect parameter count for 'evalLandmarking'.");
                 br_eval_landmarking(parv[0], parv[1], parc >= 3 ? parv[2] : "", parc >= 4 ? atoi(parv[3]) : 0, parc >= 5 ? atoi(parv[4]) : 1);
@@ -815,11 +815,27 @@ static int associateGroundTruthDetections(QList&lt;ResolvedDetection&gt; &amp;resolved, QL
     return totalTrueDetections;
 }
-float EvalDetection(const QString &predictedGallery, const QString &truthGallery, const QString &csv, bool normalize)
+float EvalDetection(const QString &predictedGallery, const QString &truthGallery, const QString &csv, bool normalize, int minSize)
 {
     qDebug("Evaluating detection of %s against %s", qPrintable(predictedGallery), qPrintable(truthGallery));
     // Organized by file, QMap used to preserve order
     QMap<QString, Detections> allDetections = getDetections(predictedGallery, truthGallery);
+    
+    // Remove any bounding boxes with a side smaller than minSize
+    if (minSize > 0) {
+        foreach(QString key, allDetections.keys()) {
+            for (int i = 0; i < allDetections[key].predicted.length(); i++) {
+                QRectF box = allDetections[key].predicted[i].boundingBox;
+                if (min(box.width(), box.height()) < minSize)
+                    allDetections[key].predicted.removeAt(i);
+            }
+            for (int i = 0; i < allDetections[key].truth.length(); i++) {
+                QRectF box = allDetections[key].truth[i].boundingBox;
+                if (min(box.width(), box.height()) < minSize)
+                    allDetections[key].truth.removeAt(i);
+            }
+        }         
+    }
     QList<ResolvedDetection> resolvedDetections, falseNegativeDetections;
     QRectF normalizations(0, 0, 0, 0);
@@ -29,7 +29,7 @@ namespace br
     float InplaceEval(const QString & simmat, const QString & target, const QString & query, const QString & csv = "");
     void EvalClassification(const QString &predictedGallery, const QString &truthGallery, QString predictedProperty = "", QString truthProperty = "");
-    float EvalDetection(const QString &predictedGallery, const QString &truthGallery, const QString &csv = "", bool normalize = false); // Return average overlap
+    float EvalDetection(const QString &predictedGallery, const QString &truthGallery, const QString &csv = "", bool normalize = false, int minSize = 0); // Return average overlap
     float EvalLandmarking(const QString &predictedGallery, const QString &truthGallery, const QString &csv = "", int normalizationIndexA = 0, int normalizationIndexB = 1); // Return average error
     void EvalRegression(const QString &predictedGallery, const QString &truthGallery, QString predictedProperty = "", QString truthProperty = "");
 }
@@ -124,9 +124,9 @@ void br_eval_clustering(const char *csv, const char *gallery, const char *truth_
     EvalClustering(csv, gallery, truth_property);
 }
-float br_eval_detection(const char *predicted_gallery, const char *truth_gallery, const char *csv, bool normalize)
+float br_eval_detection(const char *predicted_gallery, const char *truth_gallery, const char *csv, bool normalize, int minSize)
 {
-    return EvalDetection(predicted_gallery, truth_gallery, csv, normalize);
+    return EvalDetection(predicted_gallery, truth_gallery, csv, normalize, minSize);
 }
 float br_eval_landmarking(const char *predicted_gallery, const char *truth_gallery, const char *csv, int normalization_index_a, int normalization_index_b)
@@ -196,7 +196,7 @@ BR_EXPORT void br_eval_clustering(const char *csv, const char *gallery, const ch
  * \param normalize Optional \c bool flag to normalize predicted bounding boxes for improved detection. 
  * \return Average detection bounding box overlap.
  */
-BR_EXPORT float br_eval_detection(const char *predicted_gallery, const char *truth_gallery, const char *csv = "", bool normalize = false);
+BR_EXPORT float br_eval_detection(const char *predicted_gallery, const char *truth_gallery, const char *csv = "", bool normalize = false, int minSize);
 /*!
  * \brief Evaluates and prints landmarking accuracy to terminal.