Added brier score for p-metrics in forecasting

argoverse · Apr 22, 2021 · 08e1454 · 08e1454
1 parent 538f3e6
commit 08e1454
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Showing 2 changed files with 223 additions and 211 deletions.
diff --git a/argoverse/evaluation/eval_forecasting.py b/argoverse/evaluation/eval_forecasting.py
@@ -115,20 +115,9 @@ def get_displacement_errors_and_miss_rate(
 
         if forecasted_probabilities is not None:
             prob_n_misses.append(1.0 if curr_min_fde > miss_threshold else (1.0 - pruned_probabilities[min_idx]))
-            prob_min_ade.append(
-                min(
-                    -np.log(pruned_probabilities[min_idx]),
-                    -np.log(LOW_PROB_THRESHOLD_FOR_METRICS),
-                )
-                + curr_min_ade
-            )
-            prob_min_fde.append(
-                min(
-                    -np.log(pruned_probabilities[min_idx]),
-                    -np.log(LOW_PROB_THRESHOLD_FOR_METRICS),
-                )
-                + curr_min_fde
-            )
+            prob_min_ade.append((1 - pruned_probabilities[min_idx]) ** 2 + curr_min_ade)
+            prob_min_fde.append((1 - pruned_probabilities[min_idx]) ** 2 + curr_min_fde)
+
     metric_results["minADE"] = sum(min_ade) / len(min_ade)
     metric_results["minFDE"] = sum(min_fde) / len(min_fde)
     metric_results["MR"] = sum(n_misses) / len(n_misses)