fixed bug in averaging in case of AP and MOT metrics

leonid-pishchulin · Jun 30, 2018 · 0268b26 · 0268b26
1 parent 60cd97e
commit 0268b26
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Showing 3 changed files with 12 additions and 11 deletions.
diff --git a/README.md b/README.md
@@ -44,6 +44,7 @@ Evaluation requires ground truth (GT) annotations available at [PoseTrack](https
 			           "id": [0],
 				   "x": [394],
 				   "y": [173],
+				   "score": [0.7],
 			       },
 			       { ... }
 			   ]

diff --git a/py/evaluateAP.py b/py/evaluateAP.py
@@ -25,11 +25,11 @@ def computeMetrics(scoresAll, labelsAll, nGTall):
             apAll[j] = eval_helpers.VOCap(recall, precision) * 100
             preAll[j] = precision[len(precision) - 1] * 100
             recAll[j] = recall[len(recall) - 1] * 100
-    idxs = np.argwhere(~np.isnan(apAll[:,0]))
+    idxs = np.argwhere(~np.isnan(apAll[:nGTall.shape[0],0]))
     apAll[nGTall.shape[0]] = apAll[idxs, 0].mean()
-    idxs = np.argwhere(~np.isnan(recAll[:,0]))
+    idxs = np.argwhere(~np.isnan(recAll[:nGTall.shape[0],0]))
     recAll[nGTall.shape[0]] = recAll[idxs, 0].mean()
-    idxs = np.argwhere(~np.isnan(preAll[:,0]))
+    idxs = np.argwhere(~np.isnan(preAll[:nGTall.shape[0],0]))
     preAll[nGTall.shape[0]] = preAll[idxs, 0].mean()
 
     return apAll, preAll, recAll

diff --git a/py/evaluateTracking.py b/py/evaluateTracking.py
@@ -126,13 +126,13 @@ def computeMetrics(gtFramesAll, motAll, outputDir, bSaveSeq):
                                         numObj)
 
             # average metrics over all joints per sequence
-            idxs = np.argwhere(~np.isnan(metricsSeqAll[si]['mota'][0,:]))
+            idxs = np.argwhere(~np.isnan(metricsSeqAll[si]['mota'][0,:nJoints]))
             metricsSeqAll[si]['mota'][0,nJoints] = metricsSeqAll[si]['mota'][0,idxs].mean()
-            idxs = np.argwhere(~np.isnan(metricsSeqAll[si]['motp'][0,:]))
+            idxs = np.argwhere(~np.isnan(metricsSeqAll[si]['motp'][0,:nJoints]))
             metricsSeqAll[si]['motp'][0,nJoints] = metricsSeqAll[si]['motp'][0,idxs].mean()
-            idxs = np.argwhere(~np.isnan(metricsSeqAll[si]['pre'][0,:]))
+            idxs = np.argwhere(~np.isnan(metricsSeqAll[si]['pre'][0,:nJoints]))
             metricsSeqAll[si]['pre'][0,nJoints]  = metricsSeqAll[si]['pre'] [0,idxs].mean()
-            idxs = np.argwhere(~np.isnan(metricsSeqAll[si]['rec'][0,:]))
+            idxs = np.argwhere(~np.isnan(metricsSeqAll[si]['rec'][0,:nJoints]))
             metricsSeqAll[si]['rec'][0,nJoints]  = metricsSeqAll[si]['rec'] [0,idxs].mean()
 
             metricsSeq = metricsSeqAll[si].copy()
@@ -174,13 +174,13 @@ def computeMetrics(gtFramesAll, motAll, outputDir, bSaveSeq):
                                        numObj)
 
     # average metrics over all joints over all sequences
-    idxs = np.argwhere(~np.isnan(metricsFinAll['mota'][0,:]))
+    idxs = np.argwhere(~np.isnan(metricsFinAll['mota'][0,:nJoints]))
     metricsFinAll['mota'][0,nJoints] = metricsFinAll['mota'][0,idxs].mean()
-    idxs = np.argwhere(~np.isnan(metricsFinAll['motp'][0,:]))
+    idxs = np.argwhere(~np.isnan(metricsFinAll['motp'][0,:nJoints]))
     metricsFinAll['motp'][0,nJoints] = metricsFinAll['motp'][0,idxs].mean()
-    idxs = np.argwhere(~np.isnan(metricsFinAll['pre'][0,:]))
+    idxs = np.argwhere(~np.isnan(metricsFinAll['pre'][0,:nJoints]))
     metricsFinAll['pre'][0,nJoints]  = metricsFinAll['pre'] [0,idxs].mean()
-    idxs = np.argwhere(~np.isnan(metricsFinAll['rec'][0,:]))
+    idxs = np.argwhere(~np.isnan(metricsFinAll['rec'][0,:nJoints]))
     metricsFinAll['rec'][0,nJoints]  = metricsFinAll['rec'] [0,idxs].mean()
 
     metricsFin = metricsFinAll.copy()