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mppnet_4frames.yaml
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mppnet_4frames.yaml
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CLASS_NAMES: ['Vehicle', 'Pedestrian', 'Cyclist']
DATA_CONFIG:
_BASE_CONFIG_: cfgs/dataset_configs/waymo_dataset.yaml
PROCESSED_DATA_TAG: 'waymo_processed_data_v0_5_0'
SAMPLED_INTERVAL: {
'train': 1,
'test': 1
}
FILTER_EMPTY_BOXES_FOR_TRAIN: True
DISABLE_NLZ_FLAG_ON_POINTS: True
SEQUENCE_CONFIG:
ENABLED: True
SAMPLE_OFFSET: [-3,0]
USE_PREDBOX: True
ROI_BOXES_PATH: {
'train': '../output/xxxxx/train/result.pkl', # example: predicted boxes of RPN in training set
'test': '../output/xxxxx/val/result.pkl', # example: predicted boxes of RPN in evalulation set
}
DATA_AUGMENTOR:
DISABLE_AUG_LIST: [ 'placeholder' ]
AUG_CONFIG_LIST:
- NAME: random_world_flip
ALONG_AXIS_LIST: [ 'x', 'y' ]
- NAME: random_world_rotation
WORLD_ROT_ANGLE: [ -0.78539816, 0.78539816 ]
- NAME: random_world_scaling
WORLD_SCALE_RANGE: [ 0.95, 1.05 ]
DATA_PROCESSOR:
- NAME: mask_points_and_boxes_outside_range
REMOVE_OUTSIDE_BOXES: True
- NAME: shuffle_points
SHUFFLE_ENABLED: {
'train': True,
'test': True
}
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: MPPNet
ROI_HEAD:
NAME: MPPNetHead
TRANS_INPUT: 256
CLASS_AGNOSTIC: True
USE_BOX_ENCODING:
ENABLED: True
AVG_STAGE1_SCORE: True
USE_TRAJ_EMPTY_MASK: True
USE_AUX_LOSS: True
IOU_WEIGHT: [0.5,0.4]
ROI_GRID_POOL:
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 # GRID_SIZE*GRID_SIZE*GRID_SIZE
pos_hidden_dim: 64
enc_layers: 3
dim_feedforward: 512
hidden_dim: 256 #equal to ROI_HEAD.TRANS_INPUT
dropout: 0.1
nheads: 4
pre_norm: False
num_frames: 4
num_groups: 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