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“agent-sgs” committed Sep 19, 2022
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1 change: 0 additions & 1 deletion .gitignore
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Expand Up @@ -7,7 +7,6 @@ data/
venv/
*.idea/
*.so
*.yaml
*.sh
*.pth
*.pkl
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123 changes: 123 additions & 0 deletions tools/cfgs/kitti_models/pillarnet.yaml
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CLASS_NAMES: ['Car', 'Pedestrian', 'Cyclist']

DATA_CONFIG:
_BASE_CONFIG_: cfgs/dataset_configs/kitti_dataset.yaml


MODEL:
NAME: PillarNet

VFE:
NAME: DynamicPillarPFE
WITH_DISTANCE: False
USE_ABSLOTE_XYZ: True
USE_CLUSTER_XYZ: False
USE_NORM: True
NUM_FILTERS: [32]

BACKBONE_3D:
NAME: PillarBackBone8x


BACKBONE_2D:
NAME: BaseBEVBackboneV1

LAYER_NUMS: [5, 5]
LAYER_STRIDES: [1, 2]
NUM_FILTERS: [256, 256]
UPSAMPLE_STRIDES: [1, 2]
NUM_UPSAMPLE_FILTERS: [128, 128]

DENSE_HEAD:
NAME: AnchorHeadSingle
CLASS_AGNOSTIC: False

USE_DIRECTION_CLASSIFIER: True
DIR_OFFSET: 0.78539
DIR_LIMIT_OFFSET: 0.0
NUM_DIR_BINS: 2

ANCHOR_GENERATOR_CONFIG: [
{
'class_name': 'Car',
'anchor_sizes': [[3.9, 1.6, 1.56]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-1.78],
'align_center': False,
'feature_map_stride': 8,
'matched_threshold': 0.6,
'unmatched_threshold': 0.45
},
{
'class_name': 'Pedestrian',
'anchor_sizes': [[0.8, 0.6, 1.73]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-0.6],
'align_center': False,
'feature_map_stride': 8,
'matched_threshold': 0.5,
'unmatched_threshold': 0.35
},
{
'class_name': 'Cyclist',
'anchor_sizes': [[1.76, 0.6, 1.73]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-0.6],
'align_center': False,
'feature_map_stride': 8,
'matched_threshold': 0.5,
'unmatched_threshold': 0.35
}
]

TARGET_ASSIGNER_CONFIG:
NAME: AxisAlignedTargetAssigner
POS_FRACTION: -1.0
SAMPLE_SIZE: 512
NORM_BY_NUM_EXAMPLES: False
MATCH_HEIGHT: False
BOX_CODER: ResidualCoder

LOSS_CONFIG:
LOSS_WEIGHTS: {
'cls_weight': 1.0,
'loc_weight': 2.0,
'dir_weight': 0.2,
'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: 0.01
NMS_PRE_MAXSIZE: 4096
NMS_POST_MAXSIZE: 500


OPTIMIZATION:
BATCH_SIZE_PER_GPU: 4
NUM_EPOCHS: 80

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
161 changes: 161 additions & 0 deletions tools/cfgs/nuscenes_models/cbgs_pillar0075_res2d_centerpoint.yaml
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CLASS_NAMES: ['car','truck', 'construction_vehicle', 'bus', 'trailer',
'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone']

DATA_CONFIG:
_BASE_CONFIG_: cfgs/dataset_configs/nuscenes_dataset.yaml
POINT_CLOUD_RANGE: [-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]

DATA_AUGMENTOR:
DISABLE_AUG_LIST: ['placeholder']
AUG_CONFIG_LIST:
- NAME: gt_sampling
DB_INFO_PATH:
- nuscenes_dbinfos_10sweeps_withvelo.pkl
PREPARE: {
filter_by_min_points: [
'car:5','truck:5', 'construction_vehicle:5', 'bus:5', 'trailer:5',
'barrier:5', 'motorcycle:5', 'bicycle:5', 'pedestrian:5', 'traffic_cone:5'
],
}

SAMPLE_GROUPS: [
'car:2','truck:3', 'construction_vehicle:7', 'bus:4', 'trailer:6',
'barrier:2', 'motorcycle:6', 'bicycle:6', 'pedestrian:2', 'traffic_cone:2'
]

NUM_POINT_FEATURES: 5
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: [0.9, 1.1]

- 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
VOXEL_SIZE: [0.075, 0.075, 0.2]
MAX_POINTS_PER_VOXEL: 10
MAX_NUMBER_OF_VOXELS: {
'train': 120000,
'test': 160000
}


MODEL:
NAME: PillarNet

VFE:
NAME: DynamicPillarPFE
WITH_DISTANCE: False
USE_ABSLOTE_XYZ: True
USE_CLUSTER_XYZ: False
USE_NORM: True
NUM_FILTERS: [ 32 ]

BACKBONE_3D:
NAME: PillarRes18BackBone8x

BACKBONE_2D:
NAME: BaseBEVBackboneV1

LAYER_NUMS: [ 5, 5 ]
LAYER_STRIDES: [ 1, 2 ]
NUM_FILTERS: [ 256, 256 ]
UPSAMPLE_STRIDES: [ 1, 2 ]
NUM_UPSAMPLE_FILTERS: [ 128, 128 ]

DENSE_HEAD:
NAME: CenterHead
CLASS_AGNOSTIC: False

CLASS_NAMES_EACH_HEAD: [
['car'],
['truck', 'construction_vehicle'],
['bus', 'trailer'],
['barrier'],
['motorcycle', 'bicycle'],
['pedestrian', 'traffic_cone'],
]

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': 0.25,
'code_weights': [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2, 1.0, 1.0]
}

POST_PROCESSING:
SCORE_THRESH: 0.1
POST_CENTER_LIMIT_RANGE: [-61.2, -61.2, -10.0, 61.2, 61.2, 10.0]
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: 4
NUM_EPOCHS: 20

OPTIMIZER: adam_onecycle
LR: 0.001
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
97 changes: 97 additions & 0 deletions tools/cfgs/waymo_models/pillarnet.yaml
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CLASS_NAMES: ['Vehicle', 'Pedestrian', 'Cyclist']

DATA_CONFIG:
_BASE_CONFIG_: cfgs/dataset_configs/waymo_dataset.yaml

MODEL:
NAME: PillarNet

VFE:
NAME: DynamicPillarPFE
WITH_DISTANCE: False
USE_ABSLOTE_XYZ: True
USE_CLUSTER_XYZ: False
USE_NORM: True
NUM_FILTERS: [32]

BACKBONE_3D:
NAME: PillarRes18BackBone8x

BACKBONE_2D:
NAME: BaseBEVBackboneV1

LAYER_NUMS: [5, 5]
LAYER_STRIDES: [1, 2]
NUM_FILTERS: [256, 256]
UPSAMPLE_STRIDES: [1, 2]
NUM_UPSAMPLE_FILTERS: [128, 128]

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']
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': 2.0,
'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

POST_PROCESSING:
RECALL_THRESH_LIST: [0.3, 0.5, 0.7]

EVAL_METRIC: waymo


OPTIMIZATION:
BATCH_SIZE_PER_GPU: 4
NUM_EPOCHS: 30

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

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