Update waymo dataset, evaluation metrics and related configs for 2.0 (#1663)

* update waymo dataset

* [Fix] Fix all unittests and refactor tests directory and add circle ci in `test-1.x` (#1654)

* add circle ci

* delete github ci

* fix ci

* fix ut

* fix markdown version

* rm

* fix part of uts

* fix comments

* change foler

* refactor test directory

* fix kitti metric ut

* fix all ut
Co-authored-by: VVsssssk <shenkun@pjlab.org.cn>

* add waymo dataset and evaluation metrics

* convert second configs for v2.0

* [Refactor] Unify ceph config (#1677)

* refactor ceph in config

* support metric load ann file from ceph

* add doc string and remove useless code

* [Fix]Fix create data (#1659)

* add circle ci

* delete github ci

* fix ci

* fix ut

* fix markdown version

* rm

* fix part of uts

* fix comments

* change foler

* refactor test directory

* fix kitti metric ut

* fix all ut

* fix creat data
Co-authored-by: ChaimZhu <zhuchenming@pjlab.org.cn>

* [Fix] Fix seg mapping (#1681)

* [Doc]: fix markdown version (#1653)

* [CI] Add circle ci (#1647)

* add circle ci

* delete github ci

* fix ci

* fix ut

* fix markdown version

* rm

* fix seg mapping for scannet

* fix requiremetn

* fix all seg dataet

* resolve commnets
Co-authored-by: VVsssssk <88368822+VVsssssk@users.noreply.github.com>

* [Fix] Fix SSN configs (#1686)

* modify doc string and evaluation file location

* add doc string

* remove path mapping in flieclient args
Co-authored-by: ChaimZhu <zhuchenming@pjlab.org.cn>
Co-authored-by: VVsssssk <shenkun@pjlab.org.cn>
Co-authored-by: VVsssssk <88368822+VVsssssk@users.noreply.github.com>
Co-authored-by: Shilong Zhang <61961338+jshilong@users.noreply.github.com>

configs/benchmark/hv_pointpillars_secfpn_4x8_80e_pcdet_kitti-3d-3class.py

@@ -121,7 +121,9 @@ db_sampler = dict(
         Car=15,
         Pedestrian=15,
         Cyclist=15,
-    ))
+    ),
+    points_loader=dict(
+        type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4))
 
 train_pipeline = [
     dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4),

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

@@ -111,23 +111,16 @@ db_sampler = dict(
         Car=20,
         Pedestrian=15,
         Cyclist=15,
-    ))
+    ),
+    points_loader=dict(
+        type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4))
 file_client_args = dict(backend='disk')
 # file_client_args = dict(
 #     backend='petrel', path_mapping=dict(data='s3://kitti_data/'))
 
 train_pipeline = [
-    dict(
-        type='LoadPointsFromFile',
-        coord_type='LIDAR',
-        load_dim=4,
-        use_dim=4,
-        file_client_args=file_client_args),
-    dict(
-        type='LoadAnnotations3D',
-        with_bbox_3d=True,
-        with_label_3d=True,
-        file_client_args=file_client_args),
+    dict(type='LoadPointsFromFile', coord_type='LIDAR', 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='RandomFlip3D', flip_ratio_bev_horizontal=0.5),
     dict(
@@ -141,12 +134,7 @@ train_pipeline = [
     dict(type='Collect3D', keys=['points', 'gt_bboxes_3d', 'gt_labels_3d'])
 ]
 test_pipeline = [
-    dict(
-        type='LoadPointsFromFile',
-        coord_type='LIDAR',
-        load_dim=4,
-        use_dim=4,
-        file_client_args=file_client_args),
+    dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4),
     dict(
         type='MultiScaleFlipAug3D',
         img_scale=(1333, 800),
@@ -171,12 +159,7 @@ test_pipeline = [
 # construct a pipeline for data and gt loading in show function
 # please keep its loading function consistent with test_pipeline (e.g. client)
 eval_pipeline = [
-    dict(
-        type='LoadPointsFromFile',
-        coord_type='LIDAR',
-        load_dim=4,
-        use_dim=4,
-        file_client_args=file_client_args),
+    dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4),
     dict(
         type='DefaultFormatBundle3D',
         class_names=class_names,

configs/centerpoint/centerpoint_0075voxel_second_secfpn_4x8_cyclic_20e_nus.py

@@ -62,21 +62,14 @@ db_sampler = dict(
         type='LoadPointsFromFile',
         coord_type='LIDAR',
         load_dim=5,
-        use_dim=[0, 1, 2, 3, 4],
-        file_client_args=file_client_args))
+        use_dim=[0, 1, 2, 3, 4]))
 
 train_pipeline = [
-    dict(
-        type='LoadPointsFromFile',
-        coord_type='LIDAR',
-        load_dim=5,
-        use_dim=5,
-        file_client_args=file_client_args),
+    dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5),
     dict(
         type='LoadPointsFromMultiSweeps',
         sweeps_num=9,
         use_dim=[0, 1, 2, 3, 4],
-        file_client_args=file_client_args,
         pad_empty_sweeps=True,
         remove_close=True),
     dict(type='LoadAnnotations3D', with_bbox_3d=True, with_label_3d=True),
@@ -101,17 +94,11 @@ train_pipeline = [
         keys=['points', 'gt_bboxes_3d', 'gt_labels_3d'])
 ]
 test_pipeline = [
-    dict(
-        type='LoadPointsFromFile',
-        coord_type='LIDAR',
-        load_dim=5,
-        use_dim=5,
-        file_client_args=file_client_args),
+    dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5),
     dict(
         type='LoadPointsFromMultiSweeps',
         sweeps_num=9,
         use_dim=[0, 1, 2, 3, 4],
-        file_client_args=file_client_args,
         pad_empty_sweeps=True,
         remove_close=True),
     dict(

configs/centerpoint/centerpoint_0075voxel_second_secfpn_dcn_4x8_cyclic_flip-tta_20e_nus.py

@@ -8,17 +8,11 @@ class_names = [
 ]
 
 test_pipeline = [
-    dict(
-        type='LoadPointsFromFile',
-        coord_type='LIDAR',
-        load_dim=5,
-        use_dim=5,
-        file_client_args=file_client_args),
+    dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5),
     dict(
         type='LoadPointsFromMultiSweeps',
         sweeps_num=9,
         use_dim=[0, 1, 2, 3, 4],
-        file_client_args=file_client_args,
         pad_empty_sweeps=True,
         remove_close=True),
     dict(

configs/centerpoint/centerpoint_0075voxel_second_secfpn_dcn_4x8_cyclic_tta_20e_nus.py

@@ -10,17 +10,11 @@ class_names = [
 ]
 
 test_pipeline = [
-    dict(
-        type='LoadPointsFromFile',
-        coord_type='LIDAR',
-        load_dim=5,
-        use_dim=5,
-        file_client_args=file_client_args),
+    dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5),
     dict(
         type='LoadPointsFromMultiSweeps',
         sweeps_num=9,
         use_dim=[0, 1, 2, 3, 4],
-        file_client_args=file_client_args,
         pad_empty_sweeps=True,
         remove_close=True),
     dict(

configs/centerpoint/centerpoint_0075voxel_second_secfpn_dcn_circlenms_4x8_cyclic_flip-tta_20e_nus.py

@@ -9,17 +9,11 @@ class_names = [
 ]
 
 test_pipeline = [
-    dict(
-        type='LoadPointsFromFile',
-        coord_type='LIDAR',
-        load_dim=5,
-        use_dim=5,
-        file_client_args=file_client_args),
+    dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5),
     dict(
         type='LoadPointsFromMultiSweeps',
         sweeps_num=9,
         use_dim=[0, 1, 2, 3, 4],
-        file_client_args=file_client_args,
         pad_empty_sweeps=True,
         remove_close=True),
     dict(

configs/centerpoint/centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py

@@ -57,21 +57,14 @@ db_sampler = dict(
         type='LoadPointsFromFile',
         coord_type='LIDAR',
         load_dim=5,
-        use_dim=[0, 1, 2, 3, 4],
-        file_client_args=file_client_args))
+        use_dim=[0, 1, 2, 3, 4]))
 
 train_pipeline = [
-    dict(
-        type='LoadPointsFromFile',
-        coord_type='LIDAR',
-        load_dim=5,
-        use_dim=5,
-        file_client_args=file_client_args),
+    dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5),
     dict(
         type='LoadPointsFromMultiSweeps',
         sweeps_num=9,
         use_dim=[0, 1, 2, 3, 4],
-        file_client_args=file_client_args,
         pad_empty_sweeps=True,
         remove_close=True),
     dict(type='LoadAnnotations3D', with_bbox_3d=True, with_label_3d=True),
@@ -95,17 +88,11 @@ train_pipeline = [
         keys=['points', 'gt_bboxes_3d', 'gt_labels_3d'])
 ]
 test_pipeline = [
-    dict(
-        type='LoadPointsFromFile',
-        coord_type='LIDAR',
-        load_dim=5,
-        use_dim=5,
-        file_client_args=file_client_args),
+    dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5),
     dict(
         type='LoadPointsFromMultiSweeps',
         sweeps_num=9,
         use_dim=[0, 1, 2, 3, 4],
-        file_client_args=file_client_args,
         pad_empty_sweeps=True,
         remove_close=True),
     dict(
@@ -133,12 +120,11 @@ eval_pipeline = [
         coord_type='LIDAR',
         load_dim=5,
         use_dim=5,
-        file_client_args=file_client_args),
+    ),
     dict(
         type='LoadPointsFromMultiSweeps',
         sweeps_num=9,
         use_dim=[0, 1, 2, 3, 4],
-        file_client_args=file_client_args,
         pad_empty_sweeps=True,
         remove_close=True),
     dict(type='Pack3DDetInputs', keys=['points'])

configs/centerpoint/centerpoint_02pillar_second_secfpn_4x8_cyclic_20e_nus.py

@@ -58,21 +58,14 @@ db_sampler = dict(
         type='LoadPointsFromFile',
         coord_type='LIDAR',
         load_dim=5,
-        use_dim=[0, 1, 2, 3, 4],
-        file_client_args=file_client_args))
+        use_dim=[0, 1, 2, 3, 4]))
 
 train_pipeline = [
-    dict(
-        type='LoadPointsFromFile',
-        coord_type='LIDAR',
-        load_dim=5,
-        use_dim=5,
-        file_client_args=file_client_args),
+    dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5),
     dict(
         type='LoadPointsFromMultiSweeps',
         sweeps_num=9,
         use_dim=[0, 1, 2, 3, 4],
-        file_client_args=file_client_args,
         pad_empty_sweeps=True,
         remove_close=True),
     dict(type='LoadAnnotations3D', with_bbox_3d=True, with_label_3d=True),
@@ -96,17 +89,11 @@ train_pipeline = [
         keys=['points', 'gt_bboxes_3d', 'gt_labels_3d'])
 ]
 test_pipeline = [
-    dict(
-        type='LoadPointsFromFile',
-        coord_type='LIDAR',
-        load_dim=5,
-        use_dim=5,
-        file_client_args=file_client_args),
+    dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5),
     dict(
         type='LoadPointsFromMultiSweeps',
         sweeps_num=9,
         use_dim=[0, 1, 2, 3, 4],
-        file_client_args=file_client_args,
         pad_empty_sweeps=True,
         remove_close=True),
     dict(
@@ -127,17 +114,11 @@ test_pipeline = [
 # construct a pipeline for data and gt loading in show function
 # please keep its loading function consistent with test_pipeline (e.g. client)
 eval_pipeline = [
-    dict(
-        type='LoadPointsFromFile',
-        coord_type='LIDAR',
-        load_dim=5,
-        use_dim=5,
-        file_client_args=file_client_args),
+    dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5),
     dict(
         type='LoadPointsFromMultiSweeps',
         sweeps_num=9,
         use_dim=[0, 1, 2, 3, 4],
-        file_client_args=file_client_args,
         pad_empty_sweeps=True,
         remove_close=True),
     dict(type='Pack3DDetInputs', keys=['points'])

configs/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d.py

@@ -14,21 +14,21 @@ model = dict(
         dcn=dict(type='DCNv2', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, False, True, True)))
 
-# file_client_args = dict(backend='disk')
+file_client_args = dict(backend='disk')
 # Uncomment the following if use ceph or other file clients.
 # See https://mmcv.readthedocs.io/en/latest/api.html#mmcv.fileio.FileClient
 # for more details.
-file_client_args = dict(
-    backend='petrel',
-    path_mapping=dict({
-        './data/nuscenes/':
-        's3://openmmlab/datasets/detection3d/nuscenes/',
-        'data/nuscenes/':
-        's3://openmmlab/datasets/detection3d/nuscenes/'
-    }))
+# file_client_args = dict(
+#     backend='petrel',
+#     path_mapping=dict({
+#         './data/nuscenes/':
+#         's3://openmmlab/datasets/detection3d/nuscenes/',
+#         'data/nuscenes/':
+#         's3://openmmlab/datasets/detection3d/nuscenes/'
+#     }))
 
 train_pipeline = [
-    dict(type='LoadImageFromFileMono3D', file_client_args=file_client_args),
+    dict(type='LoadImageFromFileMono3D'),
     dict(
         type='LoadAnnotations3D',
         with_bbox=True,
@@ -47,7 +47,7 @@ train_pipeline = [
         ]),
 ]
 test_pipeline = [
-    dict(type='LoadImageFromFileMono3D', file_client_args=file_client_args),
+    dict(type='LoadImageFromFileMono3D'),
     dict(type='mmdet.Resize', scale_factor=1.0),
     dict(type='Pack3DDetInputs', keys=['img'])
 ]

configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py

@@ -36,16 +36,8 @@ file_client_args = dict(backend='disk')
 #         'data/nuscenes/': 's3://nuscenes/nuscenes/'
 #     }))
 train_pipeline = [
-    dict(
-        type='LoadPointsFromFile',
-        coord_type='LIDAR',
-        load_dim=5,
-        use_dim=5,
-        file_client_args=file_client_args),
-    dict(
-        type='LoadPointsFromMultiSweeps',
-        sweeps_num=10,
-        file_client_args=file_client_args),
+    dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5),
+    dict(type='LoadPointsFromMultiSweeps', sweeps_num=10),
     dict(type='LoadAnnotations3D', with_bbox_3d=True, with_label_3d=True),
     dict(
         type='GlobalRotScaleTrans',

configs/groupfree3d/groupfree3d_8x4_scannet-3d-18class-L12-O256.py

@@ -94,10 +94,7 @@ train_pipeline = [
         with_mask_3d=True,
         with_seg_3d=True),
     dict(type='GlobalAlignment', rotation_axis=2),
-    dict(
-        type='PointSegClassMapping',
-        valid_cat_ids=(3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16, 24, 28, 33, 34,
-                       36, 39)),
+    dict(type='PointSegClassMapping'),
     dict(type='PointSample', num_points=50000),
     dict(
         type='RandomFlip3D',

configs/groupfree3d/groupfree3d_8x4_scannet-3d-18class-L6-O256.py

@@ -93,10 +93,7 @@ train_pipeline = [
         with_mask_3d=True,
         with_seg_3d=True),
     dict(type='GlobalAlignment', rotation_axis=2),
-    dict(
-        type='PointSegClassMapping',
-        valid_cat_ids=(3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16, 24, 28, 33, 34,
-                       36, 39)),
+    dict(type='PointSegClassMapping'),
     dict(type='PointSample', num_points=50000),
     dict(
         type='RandomFlip3D',

configs/groupfree3d/groupfree3d_8x4_scannet-3d-18class-w2x-L12-O256.py

@@ -109,10 +109,7 @@ train_pipeline = [
         with_mask_3d=True,
         with_seg_3d=True),
     dict(type='GlobalAlignment', rotation_axis=2),
-    dict(
-        type='PointSegClassMapping',
-        valid_cat_ids=(3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16, 24, 28, 33, 34,
-                       36, 39)),
+    dict(type='PointSegClassMapping'),
     dict(type='PointSample', num_points=50000),
     dict(
         type='RandomFlip3D',

configs/groupfree3d/groupfree3d_8x4_scannet-3d-18class-w2x-L12-O512.py

@@ -110,10 +110,7 @@ train_pipeline = [
         with_mask_3d=True,
         with_seg_3d=True),
     dict(type='GlobalAlignment', rotation_axis=2),
-    dict(
-        type='PointSegClassMapping',
-        valid_cat_ids=(3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16, 24, 28, 33, 34,
-                       36, 39)),
+    dict(type='PointSegClassMapping'),
     dict(type='PointSample', num_points=50000),
     dict(
         type='RandomFlip3D',

configs/imvoxelnet/imvoxelnet_4x8_kitti-3d-car.py

@@ -94,7 +94,7 @@ file_client_args = dict(
 
 train_pipeline = [
     dict(type='LoadAnnotations3D'),
-    dict(type='LoadImageFromFileMono3D', file_client_args=file_client_args),
+    dict(type='LoadImageFromFileMono3D'),
     dict(type='RandomFlip3D', flip_ratio_bev_horizontal=0.5),
     dict(
         type='RandomResize', scale=[(1173, 352), (1387, 416)],
@@ -103,7 +103,7 @@ train_pipeline = [
     dict(type='Pack3DDetInputs', keys=['img', 'gt_bboxes_3d', 'gt_labels_3d'])
 ]
 test_pipeline = [
-    dict(type='LoadImageFromFileMono3D', file_client_args=file_client_args),
+    dict(type='LoadImageFromFileMono3D'),
     dict(type='Resize', scale=(1280, 384), keep_ratio=True),
     dict(type='Pack3DDetInputs', keys=['img'])
 ]

configs/nuimages/mask_rcnn_r50_fpn_coco-2x_1x_nus-2d.py

@@ -17,7 +17,7 @@ img_norm_cfg = dict(
     mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
 
 test_pipeline = [
-    dict(type='LoadImageFromFile', file_client_args=file_client_args),
+    dict(type='LoadImageFromFile'),
     dict(
         type='MultiScaleFlipAug',
         img_scale=(1600, 900),

configs/paconv/paconv_cuda_ssg_8x8_cosine_200e_s3dis_seg-3d-13class.py

@@ -22,10 +22,7 @@ train_pipeline = [
         with_label_3d=False,
         with_mask_3d=False,
         with_seg_3d=True),
-    dict(
-        type='PointSegClassMapping',
-        valid_cat_ids=tuple(range(len(class_names))),
-        max_cat_id=13),
+    dict(type='PointSegClassMapping'),
     dict(
         type='IndoorPatchPointSample',
         num_points=num_points,

configs/paconv/paconv_ssg_8x8_cosine_150e_s3dis_seg-3d-13class.py

@@ -26,15 +26,13 @@ train_pipeline = [
         shift_height=False,
         use_color=True,
         load_dim=6,
-        use_dim=[0, 1, 2, 3, 4, 5],
-        file_client_args=file_client_args),
+        use_dim=[0, 1, 2, 3, 4, 5]),
     dict(
         type='LoadAnnotations3D',
         with_bbox_3d=False,
         with_label_3d=False,
         with_mask_3d=False,
-        with_seg_3d=True,
-        file_client_args=file_client_args),
+        with_seg_3d=True),
     dict(type='PointSegClassMapping'),
     dict(
         type='IndoorPatchPointSample',

configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class.py

@@ -18,7 +18,9 @@ db_sampler = dict(
         filter_by_difficulty=[-1],
         filter_by_min_points=dict(Car=5, Pedestrian=10, Cyclist=10)),
     classes=class_names,
-    sample_groups=dict(Car=12, Pedestrian=6, Cyclist=6))
+    sample_groups=dict(Car=12, Pedestrian=6, Cyclist=6),
+    points_loader=dict(
+        type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4))
 train_pipeline = [
     dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4),
     dict(type='LoadAnnotations3D', with_bbox_3d=True, with_label_3d=True),

configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-car.py

@@ -82,7 +82,9 @@ db_sampler = dict(
     rate=1.0,
     prepare=dict(filter_by_difficulty=[-1], filter_by_min_points=dict(Car=5)),
     classes=class_names,
-    sample_groups=dict(Car=15))
+    sample_groups=dict(Car=15),
+    points_loader=dict(
+        type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4))
 train_pipeline = [
     dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4),
     dict(type='LoadAnnotations3D', with_bbox_3d=True, with_label_3d=True),