Add ability to use EvalClustering with gal and cluster property inste…

…ad of a cluster csv

app/br/br.cpp

@@ -163,8 +163,8 @@ class FakeMain : public QRunnable
                 check(parc >= 2 && parc <= 4, "Incorrect parameter count for 'evalClassification'.");
                 br_eval_classification(parv[0], parv[1], parc >= 3 ? parv[2] : "", parc >= 4 ? parv[3] : "");
             } else if (!strcmp(fun, "evalClustering")) {
-                check((parc >= 2) && (parc <= 3), "Incorrect parameter count for 'evalClustering'.");
-                br_eval_clustering(parv[0], parv[1], parc == 3 ? parv[2] : "");
+                check((parc >= 2) && (parc <= 5), "Incorrect parameter count for 'evalClustering'.");
+                br_eval_clustering(parv[0], parv[1], parc > 2 ? parv[2] : "", parc > 3 ? atoi(parv[3]) : 1, parc > 4 ? parv[4] : "");
             } else if (!strcmp(fun, "evalDetection")) {
                 check((parc >= 2) && (parc <= 6), "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, parc == 6 ? atoi(parv[5]) : 0);

openbr/core/cluster.cpp

@@ -432,13 +432,16 @@ float jaccardIndex(const QVector<int> &indicesA, const QVector<int> &indicesB)
 
 // Evaluates clustering algorithms based on metrics described in
 // Santo Fortunato "Community detection in graphs", Physics Reports 486 (2010)
-void br::EvalClustering(const QString &csv, const QString &input, QString truth_property)
+void br::EvalClustering(const QString &clusters, const QString &truth_gallery, QString truth_property, bool cluster_csv, QString cluster_property)
 {
     if (truth_property.isEmpty())
         truth_property = "Label";
-    qDebug("Evaluating %s against %s", qPrintable(csv), qPrintable(input));
+    if (!cluster_csv && cluster_property.isEmpty()) {
+        cluster_property = "ClusterID";
+    }
+    qDebug("Evaluating %s against %s", qPrintable(clusters), qPrintable(truth_gallery));
 
-    TemplateList tList = TemplateList::fromGallery(input);
+    TemplateList tList = TemplateList::fromGallery(truth_gallery);
     QList<int> labels = tList.indexProperty(truth_property);
 
     QHash<int, int> labelToIndex;
@@ -459,7 +462,23 @@ void br::EvalClustering(const QString &csv, const QString &input, QString truth_
         truthClusters[labelToIndex[labels[i]]].append(i);
     }
 
-    Clusters testClusters = ReadClusters(csv);
+    Clusters testClusters;
+    if (cluster_csv) {
+        testClusters = ReadClusters(clusters);
+    } else {
+        // get Clusters from gallery
+        const TemplateList tl(TemplateList::fromGallery(clusters));
+        QHash<int,Cluster > clust_id_map;
+        for (int i=0; i<tl.size(); i++) {
+            const Template &t = tl.at(i);
+            int c = t.file.get<int>(cluster_property);
+            if (!clust_id_map.contains(c)) {
+                clust_id_map.insert(c, Cluster());
+            }
+            clust_id_map[c].append(i);
+        }
+        testClusters = Clusters::fromList(clust_id_map.values());
+    }
 
     QVector<int> testIndices(labels.size());
     for (int i=0; i<testClusters.size(); i++)

openbr/core/cluster.h

@@ -57,7 +57,7 @@ namespace br
 
     // evaluate clustering results in csv, reading ground truth data from gallery input, using truth_property
     // as the key for ground truth labels.
-    void EvalClustering(const QString &csv, const QString &input, QString truth_property);
+    void EvalClustering(const QString &clusters, const QString &truth_gallery, QString truth_property, bool cluster_csv, QString cluster_property);
 
     // Read/write clusters from a text format, 1 line = 1 cluster, each line contains comma separated list
     // of assigned indices.

openbr/openbr.cpp

@@ -124,9 +124,9 @@ void br_eval_classification(const char *predicted_gallery, const char *truth_gal
     EvalClassification(predicted_gallery, truth_gallery, predicted_property, truth_property);
 }
 
-void br_eval_clustering(const char *csv, const char *gallery, const char *truth_property)
+void br_eval_clustering(const char *clusters, const char *truth_gallery, const char *truth_property, bool cluster_csv, const char *cluster_property)
 {
-    EvalClustering(csv, gallery, truth_property);
+    EvalClustering(clusters, truth_gallery, truth_property, cluster_csv, cluster_property);
 }
 
 float br_eval_detection(const char *predicted_gallery, const char *truth_gallery, const char *csv, bool normalize, int minSize, int maxSize)

openbr/openbr.h

@@ -56,7 +56,7 @@ BR_EXPORT float br_inplace_eval(const char * simmat, const char *target, const c
 
 BR_EXPORT void br_eval_classification(const char *predicted_gallery, const char *truth_gallery, const char *predicted_property = "", const char *truth_property = "");
 
-BR_EXPORT void br_eval_clustering(const char *csv, const char *gallery, const char * truth_property);
+BR_EXPORT void br_eval_clustering(const char *clusters, const char *truth_gallery, const char *truth_property = "", bool cluster_csv = true, const char *cluster_property = "");
 
 BR_EXPORT float br_eval_detection(const char *predicted_gallery, const char *truth_gallery, const char *csv = "", bool normalize = false, int minSize = 0, int maxSize = 0);