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# model settings
_base_ = './pointpillars_hv_secfpn_8xb6-160e_kitti-3d-3class.py'
# dataset settings
dataset_type = 'KittiDataset'
data_root = 'data/kitti/'
class_names = ['Car']
metainfo = dict(classes=class_names)
backend_args = None
point_cloud_range = [0, -39.68, -3, 69.12, 39.68, 1]
model = dict(
bbox_head=dict(
type='Anchor3DHead',
num_classes=1,
anchor_generator=dict(
_delete_=True,
type='AlignedAnchor3DRangeGenerator',
ranges=[[0, -39.68, -1.78, 69.12, 39.68, -1.78]],
sizes=[[3.9, 1.6, 1.56]],
rotations=[0, 1.57],
reshape_out=True)),
# model training and testing settings
train_cfg=dict(
_delete_=True,
assigner=dict(
type='Max3DIoUAssigner',
iou_calculator=dict(type='BboxOverlapsNearest3D'),
pos_iou_thr=0.6,
neg_iou_thr=0.45,
min_pos_iou=0.45,
ignore_iof_thr=-1),
allowed_border=0,
pos_weight=-1,
debug=False))
db_sampler = dict(
data_root=data_root,
info_path=data_root + 'kitti_dbinfos_train.pkl',
rate=1.0,
prepare=dict(filter_by_difficulty=[-1], filter_by_min_points=dict(Car=5)),
classes=class_names,
sample_groups=dict(Car=15),
points_loader=dict(
type='LoadPointsFromFile',
coord_type='LIDAR',
load_dim=4,
use_dim=4,
backend_args=backend_args),
backend_args=backend_args)
train_pipeline = [
dict(
type='LoadPointsFromFile',
coord_type='LIDAR',
load_dim=4,
use_dim=4,
backend_args=backend_args),
dict(type='LoadAnnotations3D', with_bbox_3d=True, with_label_3d=True),
dict(type='ObjectSample', db_sampler=db_sampler, use_ground_plane=True),
dict(type='RandomFlip3D', flip_ratio_bev_horizontal=0.5),
dict(
type='GlobalRotScaleTrans',
rot_range=[-0.78539816, 0.78539816],
scale_ratio_range=[0.95, 1.05]),
dict(type='PointsRangeFilter', point_cloud_range=point_cloud_range),
dict(type='ObjectRangeFilter', point_cloud_range=point_cloud_range),
dict(type='PointShuffle'),
dict(
type='Pack3DDetInputs',
keys=['points', 'gt_labels_3d', 'gt_bboxes_3d'])
]
test_pipeline = [
dict(
type='LoadPointsFromFile',
coord_type='LIDAR',
load_dim=4,
use_dim=4,
backend_args=backend_args),
dict(
type='MultiScaleFlipAug3D',
img_scale=(1333, 800),
pts_scale_ratio=1,
flip=False,
transforms=[
dict(
type='GlobalRotScaleTrans',
rot_range=[0, 0],
scale_ratio_range=[1., 1.],
translation_std=[0, 0, 0]),
dict(type='RandomFlip3D'),
dict(
type='PointsRangeFilter', point_cloud_range=point_cloud_range)
]),
dict(type='Pack3DDetInputs', keys=['points'])
]
train_dataloader = dict(
dataset=dict(dataset=dict(pipeline=train_pipeline, metainfo=metainfo)))
test_dataloader = dict(dataset=dict(pipeline=test_pipeline, metainfo=metainfo))
val_dataloader = dict(dataset=dict(pipeline=test_pipeline, metainfo=metainfo))
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