Openlidar benchmark config

configs/benchmark/hv_PartA2_secfpn_2x8_cyclic_80e_pcdet_kitti-3d-3class.py → configs/benchmark/hv_PartA2_secfpn_4x8_cyclic_80e_pcdet_kitti-3d-3class.py

@@ -203,23 +203,16 @@ db_sampler = dict(
     data_root=data_root,
     info_path=data_root + 'kitti_dbinfos_train.pkl',
     rate=1.0,
-    object_rot_range=[0.0, 0.0],
     prepare=dict(
         filter_by_difficulty=[-1],
         filter_by_min_points=dict(Car=5, Pedestrian=5, Cyclist=5)),
     classes=class_names,
-    sample_groups=dict(Car=15, Pedestrian=10, Cyclist=10))
+    sample_groups=dict(Car=20, Pedestrian=15, Cyclist=15))
 train_pipeline = [
     dict(type='LoadPointsFromFile', load_dim=4, use_dim=4),
     dict(type='LoadAnnotations3D', with_bbox_3d=True, with_label_3d=True),
     dict(type='ObjectSample', db_sampler=db_sampler),
-    dict(
-        type='ObjectNoise',
-        num_try=100,
-        translation_std=[1.0, 1.0, 0.5],
-        global_rot_range=[0.0, 0.0],
-        rot_range=[-0.78539816, 0.78539816]),
-    dict(type='RandomFlip3D', flip_ratio=0.5),
+    dict(type='RandomFlip3D', flip_ratio_bev_horizontal=0.5),
     dict(
         type='GlobalRotScaleTrans',
         rot_range=[-0.78539816, 0.78539816],

configs/benchmark/hv_pointpillars_secfpn_6x8_160e_pcdet_kitti-3d-3class.py → configs/benchmark/hv_pointpillars_secfpn_4x8_160e_pcdet_kitti-3d-3class.py

@@ -119,21 +119,15 @@ db_sampler = dict(
         )),
     classes=class_names,
     sample_groups=dict(
-        Car=15,
-        Pedestrian=10,
-        Cyclist=10,
+        Car=20,
+        Pedestrian=15,
+        Cyclist=15,
     ))
 
 train_pipeline = [
     dict(type='LoadPointsFromFile', load_dim=4, use_dim=4),
     dict(type='LoadAnnotations3D', with_bbox_3d=True, with_label_3d=True),
     dict(type='ObjectSample', db_sampler=db_sampler),
-    dict(
-        type='ObjectNoise',
-        num_try=100,
-        translation_std=[1.0, 1.0, 0.1],
-        global_rot_range=[0.0, 0.0],
-        rot_range=[-0.78539816, 0.78539816]),
     dict(type='RandomFlip3D', flip_ratio_bev_horizontal=0.5),
     dict(
         type='GlobalRotScaleTrans',
@@ -170,7 +164,7 @@ test_pipeline = [
 ]
 
 data = dict(
-    samples_per_gpu=6,
+    samples_per_gpu=4,
     workers_per_gpu=4,
     train=dict(
         type=dataset_type,

configs/benchmark/hv_second_secfpn_6x8_80e_pcdet_kitti-3d-3class.py → configs/benchmark/hv_second_secfpn_4x8_80e_pcdet_kitti-3d-3class.py

@@ -103,14 +103,14 @@ db_sampler = dict(
         filter_by_difficulty=[-1],
         filter_by_min_points=dict(
             Car=5,
-            Pedestrian=10,
-            Cyclist=10,
+            Pedestrian=5,
+            Cyclist=5,
         )),
     classes=class_names,
     sample_groups=dict(
-        Car=12,
-        Pedestrian=6,
-        Cyclist=6,
+        Car=20,
+        Pedestrian=15,
+        Cyclist=15,
     ))
 file_client_args = dict(backend='disk')
 # file_client_args = dict(
@@ -128,12 +128,6 @@ train_pipeline = [
         with_label_3d=True,
         file_client_args=file_client_args),
     dict(type='ObjectSample', db_sampler=db_sampler),
-    dict(
-        type='ObjectNoise',
-        num_try=100,
-        translation_std=[1.0, 1.0, 0.1],
-        global_rot_range=[0.0, 0.0],
-        rot_range=[-0.78539816, 0.78539816]),
     dict(type='RandomFlip3D', flip_ratio_bev_horizontal=0.5),
     dict(
         type='GlobalRotScaleTrans',
@@ -174,7 +168,7 @@ test_pipeline = [
 ]
 
 data = dict(
-    samples_per_gpu=6,
+    samples_per_gpu=4,
     workers_per_gpu=4,
     train=dict(
         type=dataset_type,