adopt it for traffic light

Signed-off-by: MasatoSaeki <[email protected]>

driving_log_replayer_v2/driving_log_replayer_v2/traffic_light.py

@@ -12,18 +12,25 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from __future__ import annotations
+
 from dataclasses import dataclass
 import logging
 from pathlib import Path
 import sys
 from typing import Literal
+from typing import TYPE_CHECKING
 
 from autoware_perception_msgs.msg import TrafficSignalElement
 from perception_eval.evaluation import PerceptionFrameResult
 from pydantic import BaseModel
 from pydantic import field_validator
+from pydantic import model_validator
 import simplejson as json
 
+if TYPE_CHECKING:
+    from perception_eval.evaluation import PerceptionFrameResult
+
 from driving_log_replayer_v2.criteria import PerceptionCriteria
 from driving_log_replayer_v2.perception_eval_conversions import summarize_pass_fail_result
 from driving_log_replayer_v2.result import EvaluationItem
@@ -101,8 +108,38 @@ def get_most_probable_element(
     return elements[index]
 
 
+class Region(BaseModel):
+    x_position: tuple[float, float] | None = None
+    y_position: tuple[float, float] | None = None
+
+    @field_validator("x_position", "y_position", mode="before")
+    @classmethod
+    def validate_region_range(cls, v: str | None) -> tuple[number, number] | None:
+        if v is None:
+            return None
+
+        err_non_specify_msg = "both min and max values must be specified."
+        err_range_msg = (
+            f"{v} is not valid distance range, expected ordering min-max with min < max."
+        )
+
+        s_lower, s_upper = v.split(",")
+
+        if s_upper != "" or s_lower != "":
+            raise ValueError(err_non_specify_msg)
+
+        lower = float(s_lower)
+        upper = float(s_upper)
+
+        if lower >= upper:
+            raise ValueError(err_range_msg)
+
+        return (lower, upper)
+
+
 class Filter(BaseModel):
     Distance: tuple[float, float] | None = None
+    Region: Region | None
     # add filter condition here
 
     @field_validator("Distance", mode="before")
@@ -124,6 +161,29 @@ def validate_distance_range(cls, v: str | None) -> tuple[number, number] | None:
             raise ValueError(err_msg)
         return (lower, upper)
 
+    @field_validator("Region", mode="after")
+    @classmethod
+    def validate_region_value(cls, v: Region | None) -> Region | None:
+        if v is None:
+            return None
+        if v.x_position is None and v.y_position is None:
+            return None
+        return v
+
+    @model_validator(mode="before")
+    @classmethod
+    def set_region_default_value(cls, v: dict) -> dict:
+        if "Region" not in v:
+            v["Region"] = None
+        return v
+
+    @model_validator(mode="after")
+    def validate_duplicate_filter(self) -> Filter:
+        if self.Distance is not None and self.Region is not None:
+            error_msg = "Distance and Region filter cannot be used at the same time."
+            raise ValueError(error_msg)
+        return self
+
 
 class Criteria(BaseModel):
     PassRate: number
@@ -194,7 +254,7 @@ def __post_init__(self) -> None:
         self.criteria: PerceptionCriteria = PerceptionCriteria(
             methods=self.condition.CriteriaMethod,
             levels=self.condition.CriteriaLevel,
-            distance_range=self.condition.Filter.Distance,
+            filters=self.condition.Filter,
         )
 
     def set_frame(self, frame: PerceptionFrameResult) -> dict:

sample/traffic_light/scenario.yaml

@@ -16,11 +16,17 @@ Evaluation:
         CriteriaLevel: hard # Level of criteria (perfect/hard/normal/easy, or custom value 0.0-100.0)
         Filter:
           Distance: 0.0-50.0 # [m] null [Do not filter by distance] or lower_limit-(upper_limit) [Upper limit can be omitted. If omitted value is 1.7976931348623157e+308]
+          Region:
+            x_position: null # [m] null [Do not filter by x_position] or lower_limit,upper_limit [Lower and upper limit can be omitted. If omitted value is +-1.7976931348623157e+308]
+            y_position: null # [m] null [Do not filter by y_position] or lower_limit,upper_limit [Lower and upper limit can be omitted. If omitted value is +-1.7976931348623157e+308]
       - PassRate: 95.0 # How much (%) of the evaluation attempts are considered successful.
         CriteriaMethod: num_gt_tp # refer https://github.com/tier4/driving_log_replayer_v2/blob/develop/driving_log_replayer_v2/driving_log_replayer_v2/criteria/perception.py#L136-L152
         CriteriaLevel: easy # Level of criteria (perfect/hard/normal/easy, or custom value 0.0-100.0)
         Filter:
           Distance: 50.0- # [m] null [Do not filter by distance] or lower_limit-(upper_limit) [Upper limit can be omitted. If omitted value is 1.7976931348623157e+308]
+          Region:
+            x_position: null # [m] null [Do not filter by x_position] or lower_limit,upper_limit [Lower and upper limit can be omitted. If omitted value is +-1.7976931348623157e+308]
+            y_position: null # [m] null [Do not filter by y_position] or lower_limit,upper_limit [Lower and upper limit can be omitted. If omitted value is +-1.7976931348623157e+308]
   PerceptionEvaluationConfig:
     camera_type: cam_traffic_light_near # Specifies the type of camera for traffic_light.
     evaluation_config_dict:
@@ -30,6 +36,7 @@ Evaluation:
       min_distance: 0.0 # Maximum distance of traffic lights to be evaluated
       allow_matching_unknown: true # Whether or not to match objects whose labels are unknown
       merge_similar_labels: false # Whether or not to merge similar labels https://github.com/tier4/autoware_perception_evaluation/blob/develop/docs/en/perception/label.md#merge-similar-labels-option
+      uuid_matching_first: false # Whether or not to match by UUID first
   CriticalObjectFilterConfig:
     target_labels: [green, red, yellow, unknown]
   PerceptionPassFailConfig: