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safdnet_1f_2x_argo.yaml
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CLASS_NAMES: ['Regular_vehicle', 'Pedestrian', 'Bicyclist', 'Motorcyclist', 'Wheeled_rider',
'Bollard', 'Construction_cone', 'Sign', 'Construction_barrel', 'Stop_sign', 'Mobile_pedestrian_crossing_sign',
'Large_vehicle', 'Bus', 'Box_truck', 'Truck', 'Vehicular_trailer', 'Truck_cab', 'School_bus', 'Articulated_bus',
'Message_board_trailer', 'Bicycle', 'Motorcycle', 'Wheeled_device', 'Wheelchair', 'Stroller', 'Dog']
DATA_CONFIG:
_BASE_CONFIG_: cfgs/dataset_configs/argo2_dataset.yaml
POINT_CLOUD_RANGE: [-200, -200, -4, 200, 200, 4]
DATA_AUGMENTOR:
DISABLE_AUG_LIST: ['placeholder']
AUG_CONFIG_LIST:
- NAME: gt_sampling
DB_INFO_PATH:
- argo2_dbinfos.pkl
USE_SHARED_MEMORY: False # set it to True to speed up (it costs about 15GB shared memory)
PREPARE: {
filter_by_min_points: [
'Regular_vehicle:5', 'Pedestrian:5', 'Bicyclist:5', 'Motorcyclist:5', 'Wheeled_rider:5',
'Bollard:5', 'Construction_cone:5', 'Sign:5', 'Construction_barrel:5', 'Stop_sign:5',
'Mobile_pedestrian_crossing_sign:5', 'Large_vehicle:5', 'Bus:5', 'Box_truck:5', 'Truck:5',
'Vehicular_trailer:5', 'Truck_cab:5', 'School_bus:5', 'Articulated_bus:5', 'Message_board_trailer:5',
'Bicycle:5', 'Motorcycle:5', 'Wheeled_device:5', 'Wheelchair:5', 'Stroller:5',
'Dog:5'
],
}
SAMPLE_GROUPS: [
'Regular_vehicle:1', 'Pedestrian:2', 'Bicyclist:2', 'Motorcyclist:2', 'Wheeled_rider:2',
'Bollard:2', 'Construction_cone:2', 'Sign:2', 'Construction_barrel:2', 'Stop_sign:2',
'Mobile_pedestrian_crossing_sign:1', 'Large_vehicle:1', 'Bus:1', 'Box_truck:1', 'Truck:1',
'Vehicular_trailer:1', 'Truck_cab:1', 'School_bus:1', 'Articulated_bus:1', 'Message_board_trailer:2',
'Bicycle:2', 'Motorcycle:2', 'Wheeled_device:2', 'Wheelchair:2', 'Stroller:2',
'Dog:2'
]
NUM_POINT_FEATURES: 4
DATABASE_WITH_FAKELIDAR: False
REMOVE_EXTRA_WIDTH: [0.0, 0.0, 0.0]
LIMIT_WHOLE_SCENE: True
- 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]
- NAME: random_world_translation
NOISE_TRANSLATE_STD: [0.5, 0.5, 0.5]
DATA_PROCESSOR:
- NAME: mask_points_and_boxes_outside_range
REMOVE_OUTSIDE_BOXES: True
- NAME: shuffle_points
SHUFFLE_ENABLED: {
'train': True,
'test': True
}
- NAME: transform_points_to_voxels_placeholder
VOXEL_SIZE: [0.1, 0.1, 0.2]
MODEL:
NAME: CenterPoint
VFE:
NAME: DynamicVoxelVFE
WITH_DISTANCE: False
USE_ABSLOTE_XYZ: True
USE_NORM: True
NUM_FILTERS: [64, 64]
BACKBONE_3D:
NAME: SparseHEDNet
SED_FEATURE_DIM: 64
SED_NUM_LAYERS: 1
SED_NUM_SBB: [4, 2, 2]
SED_DOWN_STRIDE: [1, 2, 2]
SED_DOWN_KERNEL_SIZE: [3, 3, 3]
AFD_FEATURE_DIM: 64
AFD_NUM_LAYERS: 2
AFD_NUM_SBB: [4, 2, 2] # slightly better than using one [8, 4, 4]
AFD_DOWN_STRIDE: [1, 2, 2]
AFD_DOWN_KERNEL_SIZE: [3, 3, 3]
AFD: True
FG_THRESHOLD: 0.4
FEATMAP_STRIDE: 8
DETACH_FEATURE: True
GREOUP_POOLING_KERNEL_SIZE: [7, 13, 3, 3]
GROUP_CLASS_NAMES: [
['Regular_vehicle',],
['Large_vehicle', 'Bus', 'Box_truck', 'Truck', 'Vehicular_trailer', 'Truck_cab', 'School_bus', 'Articulated_bus', 'Message_board_trailer'],
['Pedestrian', 'Bicyclist', 'Motorcyclist', 'Wheeled_rider', \
'Bollard', 'Construction_cone', 'Sign', 'Construction_barrel', 'Stop_sign', 'Mobile_pedestrian_crossing_sign', \
'Bicycle', 'Motorcycle', 'Wheeled_device', 'Wheelchair', 'Stroller', 'Dog'],
]
DENSE_HEAD:
NAME: SparseCenterHead
CLASS_AGNOSTIC: False
CLASS_NAMES_EACH_HEAD: [
['Regular_vehicle',],
['Pedestrian', 'Bicyclist', 'Motorcyclist', 'Wheeled_rider'],
['Bollard', 'Construction_cone', 'Sign', 'Construction_barrel', 'Stop_sign', 'Mobile_pedestrian_crossing_sign'],
['Large_vehicle', 'Bus', 'Box_truck', 'Truck', 'Vehicular_trailer', 'Truck_cab', 'School_bus', 'Articulated_bus', 'Message_board_trailer'],
['Bicycle', 'Motorcycle', 'Wheeled_device', 'Wheelchair', 'Stroller'],
['Dog'],
]
INPUT_FEATURES: 64
HEAD_CONV_TYPE: spconv
USE_BIAS_BEFORE_NORM: False
NUM_HM_CONV: 2
BN_EPS: 0.001
BN_MOM: 0.01
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, 0.2, 0.2]
}
POST_PROCESSING:
SCORE_THRESH: 0.1
POST_CENTER_LIMIT_RANGE: [-200, -200, -20, 200, 200, 20]
MAX_OBJ_PER_SAMPLE: 500
NMS_CONFIG:
NMS_TYPE: nms_gpu
NMS_THRESH: 0.2
NMS_PRE_MAXSIZE: 1000
NMS_POST_MAXSIZE: 83
POST_PROCESSING:
RECALL_THRESH_LIST: [0.3, 0.5, 0.7]
EVAL_METRIC: kitti
OPTIMIZATION:
BATCH_SIZE_PER_GPU: 2
NUM_EPOCHS: 24
OPTIMIZER: adam_onecycle
LR: 0.003
WEIGHT_DECAY: 0.05
MOMENTUM: 0.9
MOMS: [0.95, 0.85]
PCT_START: 0.1
DIV_FACTOR: 100
DECAY_STEP_LIST: [35, 45]
LR_DECAY: 0.1
LR_CLIP: 0.0000001
LR_WARMUP: False
WARMUP_EPOCH: 1
GRAD_NORM_CLIP: 10
LOSS_SCALE_FP16: 32.0
HOOK:
DisableAugmentationHook:
DISABLE_AUG_LIST: ['gt_sampling', 'random_world_flip','random_world_rotation','random_world_scaling', 'random_world_translation']
NUM_LAST_EPOCHS: 1