CLASS_NAMES: ['car','truck','bus','motorcycle','bicycle','pedestrian']

DATA_CONFIG:

_BASE_CONFIG_: cfgs/dataset_configs/nuscenes_dataset_da.yaml

MAX_SWEEPS: 1

POINT_FEATURE_ENCODING: {

encoding_type: absolute_coordinates_encoding,

used_feature_list: ['x', 'y', 'z'],

src_feature_list: ['x', 'y', 'z','intensity','timestamp'],

}

DATA_PROCESSOR:

- NAME: mask_points_and_boxes_outside_range

REMOVE_OUTSIDE_BOXES: True

STRICT_MASK: True

- NAME: shuffle_points

SHUFFLE_ENABLED: {

'train': True,

'test': False

}

- NAME: transform_points_to_voxels_placeholder

VOXEL_SIZE: [0.1, 0.1, 0.15]

MODEL:

NAME: VoxelRCNN

VFE:

NAME: DynMeanVFE

BACKBONE_3D:

NAME: VoxelBackBone8x

MAP_TO_BEV:

NAME: HeightCompression

NUM_BEV_FEATURES: 256

BACKBONE_2D:

NAME: BaseBEVBackbone

LAYER_NUMS: [5, 5]

LAYER_STRIDES: [1, 2]

NUM_FILTERS: [128, 256]

UPSAMPLE_STRIDES: [1, 2]

NUM_UPSAMPLE_FILTERS: [256, 256]

DENSE_HEAD:

NAME: CenterHead

CLASS_AGNOSTIC: False

CLASS_NAMES_EACH_HEAD: [

['car','truck','bus','motorcycle','bicycle','pedestrian']

]

SHARED_CONV_CHANNEL: 64

USE_BIAS_BEFORE_NORM: True

NUM_HM_CONV: 2

SEPARATE_HEAD_CFG:

HEAD_ORDER: [ 'center', 'center_z', 'dim', 'rot' ]

HEAD_DICT: {

'center': { 'out_channels': 2, 'num_conv': 2 },

'center_z': { 'out_channels': 1, 'num_conv': 2 },

'dim': { 'out_channels': 3, 'num_conv': 2 },

'rot': { 'out_channels': 2, 'num_conv': 2 },

}

TARGET_ASSIGNER_CONFIG:

FEATURE_MAP_STRIDE: 8

NUM_MAX_OBJS: 500

GAUSSIAN_OVERLAP: 0.1

MIN_RADIUS: 2

LOSS_CONFIG:

LOSS_WEIGHTS: {

'cls_weight': 1.0,

'loc_weight': 0.25,

'code_weights': [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ]

}

POST_PROCESSING:

SCORE_THRESH: 0.1

POST_CENTER_LIMIT_RANGE: [ -75.2, -75.2, -2, 75.2, 75.2, 4 ]

MAX_OBJ_PER_SAMPLE: 500

NMS_CONFIG:

NMS_TYPE: nms_gpu

NMS_THRESH: 0.7

NMS_PRE_MAXSIZE: 4096

NMS_POST_MAXSIZE: 500

ROI_HEAD:

NAME: VoxelRCNNHead

CLASS_AGNOSTIC: True

SHARED_FC: [256, 256]

CLS_FC: [256, 256]

REG_FC: [256, 256]

DP_RATIO: 0.3

NMS_CONFIG:

TRAIN:

NMS_TYPE: nms_gpu

MULTI_CLASSES_NMS: False

NMS_PRE_MAXSIZE: 9500

NMS_POST_MAXSIZE: 512

NMS_THRESH: 0.8

TEST:

NMS_TYPE: nms_gpu

MULTI_CLASSES_NMS: False

NMS_PRE_MAXSIZE: 1024

NMS_POST_MAXSIZE: 100

NMS_THRESH: 0.7

# NMS_PRE_MAXSIZE: 4096

# NMS_POST_MAXSIZE: 300

# NMS_THRESH: 0.85

ROI_GRID_POOL:

FEATURES_SOURCE: ['x_conv2', 'x_conv3', 'x_conv4']

PRE_MLP: True

GRID_SIZE: 6

POOL_LAYERS:

x_conv2:

MLPS: [ [ 64, 64 ] ]

QUERY_RANGES: [ [ 3, 3, 2 ] ]

POOL_RADIUS: [ 0.4 ]

NSAMPLE: [ 16 ]

POOL_METHOD: max_pool

x_conv3:

MLPS: [ [ 64, 64 ] ]

QUERY_RANGES: [ [ 3, 3, 2 ] ]

POOL_RADIUS: [ 0.8 ]

NSAMPLE: [ 16 ]

POOL_METHOD: max_pool

x_conv4:

MLPS: [ [ 64, 64 ] ]

QUERY_RANGES: [ [ 3, 3, 2 ] ]

POOL_RADIUS: [ 1.6 ]

NSAMPLE: [ 16 ]

POOL_METHOD: max_pool

TARGET_CONFIG:

BOX_CODER: ResidualCoder

ROI_PER_IMAGE: 128

FG_RATIO: 0.5

SAMPLE_ROI_BY_EACH_CLASS: True

CLS_SCORE_TYPE: roi_iou

CLS_FG_THRESH: 0.75

CLS_BG_THRESH: 0.25

CLS_BG_THRESH_LO: 0.1

HARD_BG_RATIO: 0.8

REG_FG_THRESH: 0.55

LOSS_CONFIG:

CLS_LOSS: BinaryCrossEntropy

REG_LOSS: smooth-l1

CORNER_LOSS_REGULARIZATION: True

LOSS_WEIGHTS: {

'rcnn_cls_weight': 1.0,

'rcnn_reg_weight': 1.0,

'rcnn_corner_weight': 1.0,

'code_weights': [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]

}

POST_PROCESSING:

RECALL_THRESH_LIST: [0.3, 0.5, 0.7]

SCORE_THRESH: 0.1

OUTPUT_RAW_SCORE: False

EVAL_METRIC: kitti

NMS_CONFIG:

MULTI_CLASSES_NMS: False

NMS_TYPE: nms_gpu

NMS_THRESH: 0.7 # apparently this is useless cause centerhead already does NMS; so edit NMS_THRESH there

NMS_PRE_MAXSIZE: 4096

NMS_POST_MAXSIZE: 500

OPTIMIZATION:

BATCH_SIZE_PER_GPU: 2

NUM_EPOCHS: 20

OPTIMIZER: adam_onecycle

LR: 0.01

WEIGHT_DECAY: 0.001

MOMENTUM: 0.9

MOMS: [0.95, 0.85]

PCT_START: 0.4

DIV_FACTOR: 10

DECAY_STEP_LIST: [35, 45]

LR_DECAY: 0.1

LR_CLIP: 0.0000001

LR_WARMUP: False

WARMUP_EPOCH: 1

GRAD_NORM_CLIP: 10