tier4 · KSeangTan · Jan 14, 2026 · Jan 14, 2026 · Jan 20, 2026 · Jan 20, 2026
@@ -18,7 +18,6 @@
 
 # dataset scene setting
 dataset_test_groups = {
-    "jpntaxi_gen2": ("t4dataset_jpntaxi_gen2_infos_test.pkl", False),
     "jpntaxi_base": ("t4dataset_jpntaxi_base_infos_test.pkl", True),
 }
 

@@ -6,7 +6,7 @@
 from .sparse_encoder import BEVFusionSparseEncoder
 from .transformer import TransformerDecoderLayer
 from .transforms_3d import BEVFusionGlobalRotScaleTrans, BEVFusionRandomFlip3D, GridMask, ImageAug3D
-from .utils import BBoxBEVL1Cost, HeuristicAssigner3D, HungarianAssigner3D, IoU3DCost
+from .utils import BBoxBEVL1Cost, HeuristicAssigner3D, HungarianAssigner3D, IoU3DCost, TransFusionBBoxCoder
 
 __all__ = [
     "BEVFusion",
@@ -26,4 +26,5 @@
     "TransformerDecoderLayer",
     "BEVFusionRandomFlip3D",
     "BEVFusionGlobalRotScaleTrans",
+    "TransFusionBBoxCoder",
 ]
@@ -554,7 +554,7 @@ def get_targets_single(self, gt_instances_3d, preds_dict, batch_idx):
             vel = None
 
         boxes_dict = self.bbox_coder.decode(
-            score, rot, dim, center, height, vel
+            score, rot, dim, center, height, vel, filter=False
         )  # decode the prediction to real world metric bbox
         bboxes_tensor = boxes_dict[0]["bboxes"]
         gt_bboxes_tensor = gt_bboxes_3d.tensor.to(score.device)

@@ -3,7 +3,7 @@
     "../../../../../autoware_ml/configs/detection3d/dataset/t4dataset/j6gen2_base.py",
     "../default/pipelines/default_camera_lidar_intensity_120m.py",
     "../default/models/default_camera_swin_fpn_120m.py",
-    "../default/schedulers/default_30e_4xb8_adamw_linear_cosine.py",
+    "../default/schedulers/default_30e_8xb8_adamw_linear_cosine.py",
     "../default/default_misc.py",
 ]
 
@@ -16,7 +16,7 @@
 info_directory_path = "info/user_name/"
 
 experiment_group_name = "bevfusion_camera/j6gen2_base/" + _base_.dataset_type
-experiment_name = "bevfusion_camera_swin_fpn_30e_4xb8_j6gen2_base_120m"
+experiment_name = "bevfusion_camera_swin_fpn_30e_8xb8_j6gen2_base_120m"
 work_dir = "work_dirs/" + experiment_group_name + "/" + experiment_name
 
 # model parameter

@@ -3,7 +3,7 @@
     "../../../../../autoware_ml/configs/detection3d/dataset/t4dataset/j6gen2_base.py",
     "../default/pipelines/default_camera_lidar_intensity_120m.py",
     "../default/models/default_camera_swin_fpn_lidar_second_secfpn_120m.py",
-    "../default/schedulers/default_20e_4xb8_adamw_linear_cosine.py",
+    "../default/schedulers/default_20e_8xb8_adamw_linear_cosine.py",
     "../default/default_misc.py",
 ]
 
@@ -16,7 +16,7 @@
 info_directory_path = "info/user_name/"
 
 experiment_group_name = "bevfusion_camera_lidar_intensity/j6gen2_base/" + _base_.dataset_type
-experiment_name = "bevfusion_camera_lidar_voxel_second_secfpn_20e_4xb8_j6gen2_base_120m"
+experiment_name = "bevfusion_camera_lidar_voxel_second_secfpn_20e_8xb8_j6gen2_base_120m"
 work_dir = "work_dirs/" + experiment_group_name + "/" + experiment_name
 
 # model parameter

@@ -1,9 +1,9 @@
 _base_ = [
     "../../../../../autoware_ml/configs/detection3d/default_runtime.py",
-    "../../../../../autoware_ml/configs/detection3d/dataset/t4dataset/jpntaxi_gen2_base.py",
+    "../../../../../autoware_ml/configs/detection3d/dataset/t4dataset/jpntaxi_base.py",
     "../default/pipelines/default_camera_lidar_intensity_120m.py",
     "../default/models/default_camera_swin_fpn_lidar_second_secfpn_120m.py",
-    "../default/schedulers/default_20e_4xb8_adamw_linear_cosine.py",
+    "../default/schedulers/default_20e_8xb8_adamw_linear_cosine.py",
     "../default/default_misc.py",
 ]
 
@@ -15,8 +15,8 @@
 data_root = "data/t4dataset/"
 info_directory_path = "info/user_name/"
 
-experiment_group_name = "bevfusion_camera_lidar_intensity/jpntaxi_gen2_base/" + _base_.dataset_type
-experiment_name = "bevfusion_camera_lidar_voxel_second_secfpn_20e_4xb8_jpntaxi_gen2_base_120m"
+experiment_group_name = "bevfusion_camera_lidar_intensity/jpntaxi_base/" + _base_.dataset_type
+experiment_name = "bevfusion_camera_lidar_voxel_second_secfpn_20e_8xb8_jpntaxi_base_120m"
 work_dir = "work_dirs/" + experiment_group_name + "/" + experiment_name
 
 # model parameter

@@ -3,7 +3,7 @@
     "../../../../../autoware_ml/configs/detection3d/dataset/t4dataset/j6gen2_base.py",
     "../default/pipelines/default_offline_lidar_intensity_120m.py",
     "../default/models/default_lidar_second_secfpn_120m.py",
-    "../default/schedulers/default_30e_4xb8_adamw_cosine.py",
+    "../default/schedulers/default_30e_8xb8_adamw_cosine.py",
     "../default/default_misc.py",
 ]
 
@@ -16,7 +16,7 @@
 info_directory_path = "info/user_name/"
 
 experiment_group_name = "bevfusion_lidar_intensity_offline/j6gen2_base/" + _base_.dataset_type
-experiment_name = "lidar_voxel_second_secfpn_30e_4xb8_j6gen2_base_120m"
+experiment_name = "lidar_voxel_second_secfpn_30e_8xb8_j6gen2_base_120m"
 work_dir = "work_dirs/" + experiment_group_name + "/" + experiment_name
 
 # model parameter

@@ -3,7 +3,7 @@
     "../../../../../autoware_ml/configs/detection3d/dataset/t4dataset/jpntaxi_gen2_base.py",
     "../default/pipelines/default_offline_lidar_intensity_120m.py",
     "../default/models/default_lidar_second_secfpn_120m.py",
-    "../default/schedulers/default_30e_4xb8_adamw_cosine.py",
+    "../default/schedulers/default_30e_8xb8_adamw_cosine.py",
     "../default/default_misc.py",
 ]
 
@@ -16,7 +16,7 @@
 info_directory_path = "info/user_name/"
 
 experiment_group_name = "bevfusion_lidar_intensity_offline/jpntaxi_gen2_base/" + _base_.dataset_type
-experiment_name = "lidar_voxel_second_secfpn_30e_4xb8_jpntaxi_gen2_base_120m"
+experiment_name = "lidar_voxel_second_secfpn_30e_8xb8_jpntaxi_gen2_base_120m"
 work_dir = "work_dirs/" + experiment_group_name + "/" + experiment_name
 
 # model parameter

@@ -4,7 +4,7 @@
     "../default/pipelines/default_offline_lidar_120m.py",
     "../models/default_lidar_second_secfpn_120m.py",
     "../default/models/default_lidar_second_secfpn_120m.py",
-    "../default/schedulers/default_50e_4xb8_adamw_cosine.py",
+    "../default/schedulers/default_50e_8xb8_adamw_cosine.py",
     "../default/default_misc.py",
 ]
 
@@ -17,7 +17,7 @@
 info_directory_path = "info/user_name/"
 
 experiment_group_name = "bevfusion_lidar_offline/base/" + _base_.dataset_type
-experiment_name = "lidar_voxel_second_secfpn_50e_4xb8_base_120m"
+experiment_name = "lidar_voxel_second_secfpn_50e_8xb8_base_120m"
 work_dir = "work_dirs/" + experiment_group_name + "/" + experiment_name
 
 # model parameter

@@ -3,7 +3,7 @@
     "../../../../../autoware_ml/configs/detection3d/dataset/t4dataset/j6gen2_base.py",
     "../default/pipelines/default_lidar_intensity_120m.py",
     "../default/models/default_lidar_second_secfpn_120m.py",
-    "../default/schedulers/default_30e_4xb8_adamw_cosine.py",
+    "../default/schedulers/default_30e_8xb8_adamw_cosine.py",
     "../default/default_misc.py",
 ]
 
@@ -13,10 +13,10 @@
 
 # user setting
 data_root = "data/t4dataset/"
-info_directory_path = "info/user_name/"
+info_directory_path = "info/kokseang_2_6_2/"
 
-experiment_group_name = "bevfusion_lidar_intensity/j6gen2_base/" + _base_.dataset_type
-experiment_name = "lidar_voxel_second_secfpn_30e_4xb8_j6gen2_base_120m"
+experiment_group_name = "bevfusion_lidar_intensity_2.6.1/j6gen2_base/" + _base_.dataset_type
+experiment_name = "lidar_voxel_second_secfpn_30e_8xb8_j6gen2_base_120m"
 work_dir = "work_dirs/" + experiment_group_name + "/" + experiment_name
 
 # model parameter
@@ -143,3 +143,5 @@
     checkpoint=dict(type="CheckpointHook", interval=1, max_keep_ckpts=3, save_best="NuScenes metric/T4Metric/mAP"),
 )
 log_processor = dict(window_size=50)
+
+load_from = "work_dirs/bevfusion_lidar_2.6.0/base/T4Dataset/lidar_voxel_second_secfpn_50e_8xb8_base_120m/epoch_50.pth"
@@ -0,0 +1,78 @@
+_base_ = [
+    "./bevfusion_lidar_voxel_second_secfpn_30e_8xb8_j6gen2_base_120m.py",
+]
+
+# user setting
+data_root = "data/t4dataset/"
+info_directory_path = "info/kokseang_2_6_1/"
+
+experiment_group_name = "bevfusion_lidar_intensity_2.6.1/j6gen2_base/" + _base_.dataset_type
+experiment_name = "lidar_voxel_second_secfpn_30e_8xb8_j6gen2_base_120m_t4metric_v2"
+work_dir = "work_dirs/" + experiment_group_name + "/" + experiment_name
+
+# Add evaluator configs
+perception_evaluator_configs = dict(
+    dataset_paths=_base_.data_root,
+    frame_id="base_link",
+    evaluation_config_dict=_base_.evaluator_metric_configs,
+    load_raw_data=False,
+)
+
+frame_pass_fail_config = dict(
+    target_labels=_base_.class_names,
+    # Matching thresholds per class (must align with `plane_distance_thresholds` used in evaluation)
+    matching_threshold_list=[2.0, 2.0, 2.0, 2.0, 2.0],
+    confidence_threshold_list=None,
+)
+
+training_statistics_parquet_path = (
+    _base_.data_root + _base_.info_directory_path + _base_.info_train_statistics_file_name
+)
+testing_statistics_parquet_path = _base_.data_root + _base_.info_directory_path + _base_.info_test_statistics_file_name
+validation_statistics_parquet_path = (
+    _base_.data_root + _base_.info_directory_path + _base_.info_val_statistics_file_name
+)
+
+val_evaluator = dict(
+    _delete_=True,
+    type="T4MetricV2",
+    data_root=_base_.data_root,
+    ann_file=_base_.data_root + _base_.info_directory_path + _base_.info_val_file_name,
+    training_statistics_parquet_path=training_statistics_parquet_path,
+    testing_statistics_parquet_path=testing_statistics_parquet_path,
+    validation_statistics_parquet_path=validation_statistics_parquet_path,
+    output_dir="validation",
+    dataset_name="base",
+    perception_evaluator_configs=perception_evaluator_configs,
+    critical_object_filter_config=None,
+    frame_pass_fail_config=frame_pass_fail_config,
+    num_workers=64,
+    scene_batch_size=-1,
+    write_metric_summary=False,
+    class_names={{_base_.class_names}},
+    name_mapping={{_base_.name_mapping}},
+    experiment_name=experiment_name,
+    experiment_group_name=_base_.experiment_group_name,
+)
+
+test_evaluator = dict(
+    _delete_=True,
+    type="T4MetricV2",
+    data_root=_base_.data_root,
+    ann_file=_base_.data_root + _base_.info_directory_path + _base_.info_test_file_name,
+    training_statistics_parquet_path=training_statistics_parquet_path,
+    testing_statistics_parquet_path=testing_statistics_parquet_path,
+    validation_statistics_parquet_path=validation_statistics_parquet_path,
+    output_dir="testing",
+    dataset_name="base",
+    perception_evaluator_configs=perception_evaluator_configs,
+    critical_object_filter_config=None,
+    frame_pass_fail_config=frame_pass_fail_config,
+    num_workers=64,
+    scene_batch_size=-1,
+    write_metric_summary=True,
+    class_names={{_base_.class_names}},
+    name_mapping={{_base_.name_mapping}},
+    experiment_name=experiment_name,
+    experiment_group_name=_base_.experiment_group_name,
+)
@@ -1,9 +1,9 @@
 _base_ = [
     "../../../../../autoware_ml/configs/detection3d/default_runtime.py",
-    "../../../../../autoware_ml/configs/detection3d/dataset/t4dataset/jpntaxi_gen2_base.py",
+    "../../../../../autoware_ml/configs/detection3d/dataset/t4dataset/jpntaxi_base.py",
     "../default/pipelines/default_lidar_intensity_120m.py",
     "../default/models/default_lidar_second_secfpn_120m.py",
-    "../default/schedulers/default_30e_4xb8_adamw_cosine.py",
+    "../default/schedulers/default_30e_8xb8_adamw_cosine.py",
     "../default/default_misc.py",
 ]
 
@@ -13,10 +13,10 @@
 
 # user setting
 data_root = "data/t4dataset/"
-info_directory_path = "info/user_name/"
+info_directory_path = "info/kokseang_2_6_1/"
 
-experiment_group_name = "bevfusion_lidar_intensity/jpntaxi_gen2_base/" + _base_.dataset_type
-experiment_name = "lidar_voxel_second_secfpn_30e_4xb8_jpntaxi_gen2_base_120m"
+experiment_group_name = "bevfusion_lidar_intensity_2.6.1/jpntaxi_base/" + _base_.dataset_type
+experiment_name = "lidar_voxel_second_secfpn_30e_8xb8_jpntaxi_base_120m"
 work_dir = "work_dirs/" + experiment_group_name + "/" + experiment_name
 
 # model parameter
@@ -143,3 +143,5 @@
     checkpoint=dict(type="CheckpointHook", interval=1, max_keep_ckpts=3, save_best="NuScenes metric/T4Metric/mAP"),
 )
 log_processor = dict(window_size=50)
+
+load_from = "work_dirs/bevfusion_lidar_2.6.0/base/T4Dataset/lidar_voxel_second_secfpn_50e_8xb8_base_120m/epoch_40.pth"
@@ -0,0 +1,78 @@
+_base_ = [
+    "./bevfusion_lidar_voxel_second_secfpn_30e_8xb8_jpntaxi_base_120m.py",
+]
+
+# user setting
+data_root = "data/t4dataset/"
+info_directory_path = "info/kokseang_2_6_1/"
+
+experiment_group_name = "bevfusion_lidar_intensity_2.6.1/jpntaxi_base/" + _base_.dataset_type
+experiment_name = "lidar_voxel_second_secfpn_30e_8xb8_jpntaxi_base_120m_t4metric_v2"
+work_dir = "work_dirs/" + experiment_group_name + "/" + experiment_name
+
+# Add evaluator configs
+perception_evaluator_configs = dict(
+    dataset_paths=_base_.data_root,
+    frame_id="base_link",
+    evaluation_config_dict=_base_.evaluator_metric_configs,
+    load_raw_data=False,
+)
+
+frame_pass_fail_config = dict(
+    target_labels=_base_.class_names,
+    # Matching thresholds per class (must align with `plane_distance_thresholds` used in evaluation)
+    matching_threshold_list=[2.0, 2.0, 2.0, 2.0, 2.0],
+    confidence_threshold_list=None,
+)
+
+training_statistics_parquet_path = (
+    _base_.data_root + _base_.info_directory_path + _base_.info_train_statistics_file_name
+)
+testing_statistics_parquet_path = _base_.data_root + _base_.info_directory_path + _base_.info_test_statistics_file_name
+validation_statistics_parquet_path = (
+    _base_.data_root + _base_.info_directory_path + _base_.info_val_statistics_file_name
+)
+
+val_evaluator = dict(
+    _delete_=True,
+    type="T4MetricV2",
+    data_root=_base_.data_root,
+    ann_file=_base_.data_root + _base_.info_directory_path + _base_.info_val_file_name,
+    training_statistics_parquet_path=training_statistics_parquet_path,
+    testing_statistics_parquet_path=testing_statistics_parquet_path,
+    validation_statistics_parquet_path=validation_statistics_parquet_path,
+    output_dir="validation",
+    dataset_name="base",
+    perception_evaluator_configs=perception_evaluator_configs,
+    critical_object_filter_config=None,
+    frame_pass_fail_config=frame_pass_fail_config,
+    num_workers=64,
+    scene_batch_size=-1,
+    write_metric_summary=False,
+    class_names={{_base_.class_names}},
+    name_mapping={{_base_.name_mapping}},
+    experiment_name=experiment_name,
+    experiment_group_name=_base_.experiment_group_name,
+)
+
+test_evaluator = dict(
+    _delete_=True,
+    type="T4MetricV2",
+    data_root=_base_.data_root,
+    ann_file=_base_.data_root + _base_.info_directory_path + _base_.info_test_file_name,
+    training_statistics_parquet_path=training_statistics_parquet_path,
+    testing_statistics_parquet_path=testing_statistics_parquet_path,
+    validation_statistics_parquet_path=validation_statistics_parquet_path,
+    output_dir="testing",
+    dataset_name="base",
+    perception_evaluator_configs=perception_evaluator_configs,
+    critical_object_filter_config=None,
+    frame_pass_fail_config=frame_pass_fail_config,
+    num_workers=64,
+    scene_batch_size=-1,
+    write_metric_summary=True,
+    class_names={{_base_.class_names}},
+    name_mapping={{_base_.name_mapping}},
+    experiment_name=experiment_name,
+    experiment_group_name=_base_.experiment_group_name,
+)
@@ -3,7 +3,7 @@
     "../../../../../autoware_ml/configs/detection3d/dataset/t4dataset/base.py",
     "../default/pipelines/default_lidar_120m.py",
     "../default/models/default_lidar_second_secfpn_120m.py",
-    "../default/schedulers/default_50e_4xb8_adamw_cosine.py",
+    "../default/schedulers/default_50e_8xb8_adamw_cosine.py",
     "../default/default_misc.py",
 ]
 
@@ -13,10 +13,10 @@
 
 # user setting
 data_root = "data/t4dataset/"
-info_directory_path = "info/user_name/"
+info_directory_path = "info/kokseang_2_6_2/"
 
-experiment_group_name = "bevfusion_lidar/base/" + _base_.dataset_type
-experiment_name = "lidar_voxel_second_secfpn_50e_4xb8_base_120m"
+experiment_group_name = "bevfusion_lidar_2.6.0/base/" + _base_.dataset_type
+experiment_name = "lidar_voxel_second_secfpn_50e_8xb8_base_120m"
 work_dir = "work_dirs/" + experiment_group_name + "/" + experiment_name
 
 # model parameter
@@ -143,3 +143,5 @@
     checkpoint=dict(type="CheckpointHook", interval=1, max_keep_ckpts=3, save_best="NuScenes metric/T4Metric/mAP"),
 )
 log_processor = dict(window_size=50)
+
+resume = True