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OpenPCDet/tools/cfgs/waymo_models/mppnet_e2e_memorybank_inference.yaml
2025-09-21 20:19:38 +08:00

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YAML

CLASS_NAMES: ['Vehicle', 'Pedestrian', 'Cyclist']
DATA_CONFIG:
_BASE_CONFIG_: cfgs/dataset_configs/waymo_dataset_multiframe.yaml
PROCESSED_DATA_TAG: 'waymo_processed_data_v0_5_0'
SEQUENCE_CONFIG:
ENABLED: True
SAMPLE_OFFSET: [-3, 0] #16frame using [-15,0]
POINT_FEATURE_ENCODING: {
encoding_type: absolute_coordinates_encoding,
used_feature_list: ['x', 'y', 'z', 'intensity', 'elongation','time'],
src_feature_list: ['x', 'y', 'z', 'intensity', 'elongation','time'],
}
MODEL:
NAME: MPPNetE2E
VFE:
NAME: DynMeanVFE
BACKBONE_3D:
NAME: VoxelResBackBone8x
MAP_TO_BEV:
NAME: HeightCompression
NUM_BEV_FEATURES: 256
BACKBONE_2D:
NAME: BaseBEVBackbone
NUM_FRAME: 2
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: [
['Vehicle', 'Pedestrian', 'Cyclist']
]
SHARED_CONV_CHANNEL: 64
USE_BIAS_BEFORE_NORM: True
NUM_HM_CONV: 2
SEPARATE_HEAD_CFG:
HEAD_ORDER: ['center', 'center_z', 'dim', 'rot','vel']
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},
'vel': {'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': 2.0,
'code_weights': [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2]
}
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: MPPNetHeadE2E
TRANS_INPUT: 256
CLASS_AGNOSTIC: True
USE_BOX_ENCODING:
ENABLED: True
NORM_T0: True
ALL_YAW_T0: True
AVG_STAGE1_SCORE: True
USE_TRAJ_EMPTY_MASK: True
USE_AUX_LOSS: True
IOU_WEIGHT: [0.5,0.4]
ROI_GRID_POOL: #if using 16frame, change to the corresponding setting
GRID_SIZE: 4
MLPS: [[128,128], [128,128]]
POOL_RADIUS: [0.8, 1.6]
NSAMPLE: [16, 16]
POOL_METHOD: max_pool
Transformer:
num_lidar_points: 128
num_proxy_points: 64
pos_hidden_dim: 64
enc_layers: 3
dim_feedforward: 512
hidden_dim: 256
dropout: 0.1
nheads: 4
pre_norm: False
num_frames: 4 #16frame using 16
num_groups: 4
sequence_stride: 1 #16frame using 4
use_grid_pos:
enabled: True
init_type: index
use_mlp_mixer:
enabled: True
hidden_dim: 16
TARGET_CONFIG:
BOX_CODER: ResidualCoder
ROI_PER_IMAGE: 96
FG_RATIO: 0.5
REG_AUG_METHOD: single
ROI_FG_AUG_TIMES: 10
RATIO: 0.2
USE_ROI_AUG: True
USE_TRAJ_AUG:
ENABLED: True
THRESHOD: 0.8
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': 2.0,
'traj_reg_weight': [2.0, 2.0, 2.0],
'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
SAVE_BBOX: False
EVAL_METRIC: waymo
NOT_APPLY_NMS_FOR_VEL: True
NMS_CONFIG:
MULTI_CLASSES_NMS: False
NMS_TYPE: nms_gpu
NMS_THRESH: 0.7
NMS_PRE_MAXSIZE: 4096
NMS_POST_MAXSIZE: 500
OPTIMIZATION:
BATCH_SIZE_PER_GPU: 2
NUM_EPOCHS: 6
OPTIMIZER: adam_onecycle
LR: 0.003
WEIGHT_DECAY: 0.01
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