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Preserve CLEAR tracker identity precision #5235

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247599a
Preserve CLEAR tracker identity precision
FlorianPfaff Aug 6, 2026
9c2aa67
Test large CLEAR tracker identities
FlorianPfaff Aug 6, 2026
636ab66
Format CLEAR precision fix
FlorianPfaff Aug 6, 2026
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11 changes: 7 additions & 4 deletions src/pyrecest/evaluation/tracking_metrics/_clear_identity.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,7 @@
from ._data import TrackingSequence, unit_interval_scalar

_EPS = np.finfo(float).eps
_UNMATCHED_ID = -1


@dataclass(frozen=True)
Expand Down Expand Up @@ -39,8 +40,8 @@ def evaluate_clear(data: TrackingSequence, *, threshold: float) -> ClearCounts:
return ClearCounts(0, data.num_tracker_detections, 0, 0, 0.0)
tp = fp = fn = switches = 0
motp_sum = 0.0
previous_id = np.full(data.num_gt_ids, np.nan)
previous_timestep_id = np.full(data.num_gt_ids, np.nan)
previous_id = np.full(data.num_gt_ids, _UNMATCHED_ID, dtype=int)
previous_timestep_id = np.full(data.num_gt_ids, _UNMATCHED_ID, dtype=int)
for gt_ids, tracker_ids, similarity in zip(
data.gt_ids, data.tracker_ids, data.similarity_scores, strict=True
):
Expand All @@ -60,9 +61,11 @@ def evaluate_clear(data: TrackingSequence, *, threshold: float) -> ClearCounts:
matched_gt = gt_ids[match_rows]
matched_tracker = tracker_ids[match_cols]
previous = previous_id[matched_gt]
switches += int(np.sum((~np.isnan(previous)) & (matched_tracker != previous)))
switches += int(
np.sum((previous != _UNMATCHED_ID) & (matched_tracker != previous))
)
previous_id[matched_gt] = matched_tracker
previous_timestep_id[:] = np.nan
previous_timestep_id[:] = _UNMATCHED_ID
previous_timestep_id[matched_gt] = matched_tracker
matches = len(match_rows)
tp += matches
Expand Down
15 changes: 15 additions & 0 deletions tests/evaluation/test_tracking_metrics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -82,6 +82,21 @@ def test_identity_switch_reduces_association_metrics() -> None:
assert finalize_identity(identity_counts)["idf1"] == pytest.approx(0.5)


def test_clear_preserves_large_tracker_identity_precision() -> None:
large_tracker_id = 2**53 + 1
data = _sequence(
[[0], [0]],
[[large_tracker_id], [large_tracker_id - 1]],
[[[1.0]], [[1.0]]],
num_gt_ids=1,
num_tracker_ids=large_tracker_id + 1,
)

counts = evaluate_clear(data, threshold=0.5)

assert (counts.tp, counts.fp, counts.fn, counts.id_switches) == (2, 0, 0, 1)


def test_hota_uses_multiple_localization_thresholds() -> None:
data = _sequence(
[[0]],
Expand Down
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