refactor: update detection/tracking metrics (#136)

Signed-off-by: ktro2828 <kotaro.uetake@tier4.jp>

Author: ktro2828

t4_devkit/evaluation/matching/parameter.py

@@ -87,7 +87,6 @@ class MatchingScorer(str, Enum):
     PLANE_DISTANCE = "PLANE_DISTANCE"
     IOU2D = "IOU2D"
     IOU3D = "IOU3D"
-    HEADING_YAW = "HEADING_YAW"
 
 
 class MatchingPolicy(str, Enum):

t4_devkit/evaluation/matching/scorer.py

@@ -19,7 +19,6 @@
     "PlaneDistance",
     "Iou2D",
     "Iou3D",
-    "HeadingYaw",
 ]
 
 
@@ -246,61 +245,3 @@ def _calculate_score(
         intersection = compute_volume_intersection(box1, box2)
         union = box1.volume + box2.volume - intersection
         return intersection / union
-
-
-class HeadingYaw(MatchingScorerImpl):
-    def _validate(self, box1, box2):
-        super()._validate(box1, box2)
-
-        if not isinstance(box1, Box3D):
-            raise TypeError("For Iou3D, input boxes must be 3D.")
-
-    @classmethod
-    def is_smaller_score_better(cls) -> bool:
-        return True
-
-    def _calculate_score(
-        self,
-        box1: Box3D,
-        box2: Box3D,
-        ego2map: HomogeneousMatrix | None = None,
-    ) -> float:
-        box1 = self._transform2ego(box1, ego2map)
-        box2 = self._transform2ego(box2, ego2map)
-
-        return abs(box2.diff_yaw(box1))
-
-    def _transform2ego(self, box: Box3D, ego2map: HomogeneousMatrix | None = None) -> Box3D:
-        """Transform the box to base link frame if it is not.
-
-        Todo:
-            This method should be function.
-        """
-        if box.frame_id == "base_link":
-            return box
-
-        if ego2map is None:
-            raise ValueError(f"For {box.frame_id}, `ego2map` must be specified.")
-
-        matrix = HomogeneousMatrix(
-            position=box.position,
-            rotation=box.rotation,
-            src=box.frame_id,
-            dst="base_link",
-        )
-
-        tf = ego2map.inv().transform(matrix=matrix)
-
-        return Box3D(
-            unix_time=box.unix_time,
-            frame_id="base_link",
-            semantic_label=box.semantic_label,
-            position=tf.position,
-            rotation=tf.rotation,
-            shape=box.shape,
-            velocity=box.velocity,
-            num_points=box.num_points,
-            future=box.future,
-            confidence=box.confidence,
-            uuid=box.uuid,
-        )

t4_devkit/evaluation/metric/ap.py

@@ -5,10 +5,8 @@
 import numpy as np
 from attrs import define, field
 
-from ..matching import CenterDistance, HeadingYaw
-
 if TYPE_CHECKING:
-    from t4_devkit.evaluation import FrameBoxMatch, MatchingScorerLike
+    from t4_devkit.evaluation import BoxMatch, FrameBoxMatch, MatchingScorerLike
 
 __all__ = ["Ap", "ApH"]
 
@@ -61,18 +59,18 @@ def compute_ap(self) -> float:
 
             return float(np.mean(filtered_precision)) / (1.0 - Ap.min_precision)
 
-    def __init__(self, threshold: float) -> None:
-        self.scorer = self._configure_scorer()
+    def __init__(self, scorer: MatchingScorerLike, threshold: float) -> None:
+        self.scorer = scorer
         self.threshold = threshold
 
-    def _configure_scorer(self) -> MatchingScorerLike:
-        return CenterDistance()
-
     def __call__(self, frames: list[FrameBoxMatch]) -> float:
-        component = self._compute_tp_fp(frames)
-        return component.compute_ap()
+        buffer = self._update_buffer(frames)
+        return buffer.compute_ap()
 
-    def _compute_tp_fp(self, frames: list[FrameBoxMatch]) -> ApBuffer:
+    def _compute_tp(self, _box_match: BoxMatch) -> float:
+        return 1.0
+
+    def _update_buffer(self, frames: list[FrameBoxMatch]) -> ApBuffer:
         buffer = self.ApBuffer()
         for frame in frames:
             buffer.num_gt += frame.num_gt
@@ -86,7 +84,7 @@ def _compute_tp_fp(self, frames: list[FrameBoxMatch]) -> ApBuffer:
                     threshold=self.threshold,
                     ego2map=frame.ego2map,
                 ):
-                    buffer.tp_list.append(1.0)
+                    buffer.tp_list.append(self._compute_tp(box_match))
                     buffer.fp_list.append(0.0)
                 else:
                     buffer.tp_list.append(0.0)
@@ -98,5 +96,11 @@ class ApH(Ap):
     def __init__(self, threshold: float) -> None:
         super().__init__(threshold=threshold)
 
-    def _configure_scorer(self) -> HeadingYaw:
-        return HeadingYaw()
+    def _compute_tp(self, box_match: BoxMatch) -> float:
+        if not box_match.is_matched():
+            return 0.0
+
+        diff_yaw = box_match.estimation.diff_yaw(box_match.ground_truth)
+        if diff_yaw > np.pi:
+            diff_yaw = 2.0 * np.pi - diff_yaw
+        return min(1.0, max(0.0, 1.0 - diff_yaw / np.pi))

t4_devkit/evaluation/metric/clear.py

@@ -4,8 +4,6 @@
 
 from attrs import define, field
 
-from ..matching import CenterDistance
-
 if TYPE_CHECKING:
     from t4_devkit.evaluation import BoxMatch, FrameBoxMatch, MatchingScorerLike
 
@@ -31,18 +29,15 @@ def compute_mota(self) -> float:
         def compute_motp(self) -> float:
             return max(self.score / self.num_tp, 0.0) if self.num_tp > 0 else 0.0
 
-    def __init__(self, threshold: float) -> None:
-        self.scorer = self._configure_scorer()
+    def __init__(self, scorer: MatchingScorerLike, threshold: float) -> None:
+        self.scorer = scorer
         self.threshold = threshold
 
-    def _configure_scorer(self) -> MatchingScorerLike:
-        return CenterDistance()
-
     def __call__(self, frames: list[FrameBoxMatch]) -> float:
-        buffer = self._compute_clear(frames)
+        buffer = self._update_buffer(frames)
         return buffer.compute_mota()
 
-    def _compute_clear(self, frames: list[FrameBoxMatch]) -> ClearBuffer:
+    def _update_buffer(self, frames: list[FrameBoxMatch]) -> ClearBuffer:
         buffer = self.ClearBuffer()
         num_frame = len(frames)
         for i in range(1, num_frame):
@@ -75,7 +70,7 @@ def _compute_clear(self, frames: list[FrameBoxMatch]) -> ClearBuffer:
                         buffer.score += self.scorer(
                             previous_match.estimation,
                             previous_match.ground_truth,
-                            previous_frame.ego2map,
+                            ego2map=previous_frame.ego2map,
                         )
                         break
 
@@ -129,5 +124,5 @@ def _check_match(
 
 class Motp(Mota):
     def __call__(self, frames: list[FrameBoxMatch]) -> float:
-        buffer = self._compute_clear(frames)
+        buffer = self._update_buffer(frames)
         return buffer.compute_motp()