Add v1.0 of ospa metric

Author: spencer@primus

avapi/evaluation/ospa.py

@@ -0,0 +1,28 @@
+# Optimal subpattern assignment metric for object tracking
+
+import numpy as np
+from avstack.modules.assignment import gnn_single_frame_assign
+
+
+class OspaMetric:
+    @staticmethod
+    def _cost(list_shorter: list, list_longer: list, p: float = 1.0, c: float = 1.0):
+        n = len(list_longer)
+        m = len(list_shorter)
+        A = np.array(
+            [[np.linalg.norm(l1 - l2) for l1 in list_shorter] for l2 in list_longer]
+        )
+        assign = gnn_single_frame_assign(A, cost_threshold=c)
+        rows, cols = assign.rows_and_cols()
+        c_una = c * len(assign.unassigned_rows)
+        distance = (
+            1 / n * (np.sum(A[rows, cols]) + c_una) ** p + (n - m) * c**p
+        ) ** 1 / p
+        return distance
+
+    @staticmethod
+    def cost(tracks: list, truths: list):
+        if len(tracks) <= len(truths):
+            return OspaMetric._cost(tracks, truths)
+        else:
+            return OspaMetric._cost(truths, tracks)

tests/evaluation/test_ospa.py

@@ -0,0 +1,18 @@
+import numpy as np
+
+from avapi.evaluation.ospa import OspaMetric
+
+
+def test_ospa_metric_one_to_one():
+    tracks = [np.random.randn(3)]
+    truths = [np.random.randn(3)]
+    cost = OspaMetric.cost(tracks, truths)
+    assert cost > 0
+
+
+def test_ospa_metric_two_to_one():
+    tracks = [np.random.randn(3) * i**3 for i in range(2)]
+    truths = [np.random.randn(3) for _ in range(1)]
+    cost1 = OspaMetric.cost(tracks[:1], truths)
+    cost2 = OspaMetric.cost(tracks, truths)
+    assert 0 < cost1 < cost2