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Add support for CenterPoint on Nuscenes (#786)
* add cbgs_dyn_pp_centerpoint.yaml * add cbgs_voxel01_res3d_centerpoint.yaml * add support of centerpoint on Nuscenes in README
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tools/cfgs/nuscenes_models/cbgs_dyn_pp_centerpoint.yaml
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CLASS_NAMES: ['car','truck', 'construction_vehicle', 'bus', 'trailer', | ||
'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone'] | ||
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DATA_CONFIG: | ||
_BASE_CONFIG_: cfgs/dataset_configs/nuscenes_dataset.yaml | ||
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POINT_CLOUD_RANGE: [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0] | ||
DATA_PROCESSOR: | ||
- NAME: mask_points_and_boxes_outside_range | ||
REMOVE_OUTSIDE_BOXES: True | ||
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- NAME: shuffle_points | ||
SHUFFLE_ENABLED: { | ||
'train': True, | ||
'test': True | ||
} | ||
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- NAME: transform_points_to_voxels_placeholder | ||
VOXEL_SIZE: [0.2, 0.2, 8.0] | ||
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MODEL: | ||
NAME: CenterPoint | ||
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VFE: | ||
NAME: DynPillarVFE | ||
WITH_DISTANCE: False | ||
USE_ABSLOTE_XYZ: True | ||
USE_NORM: True | ||
NUM_FILTERS: [ 64, 64 ] | ||
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MAP_TO_BEV: | ||
NAME: PointPillarScatter | ||
NUM_BEV_FEATURES: 64 | ||
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BACKBONE_2D: | ||
NAME: BaseBEVBackbone | ||
LAYER_NUMS: [3, 5, 5] | ||
LAYER_STRIDES: [2, 2, 2] | ||
NUM_FILTERS: [64, 128, 256] | ||
UPSAMPLE_STRIDES: [0.5, 1, 2] | ||
NUM_UPSAMPLE_FILTERS: [128, 128, 128] | ||
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DENSE_HEAD: | ||
NAME: CenterHead | ||
CLASS_AGNOSTIC: False | ||
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CLASS_NAMES_EACH_HEAD: [ | ||
['car'], | ||
['truck', 'construction_vehicle'], | ||
['bus', 'trailer'], | ||
['barrier'], | ||
['motorcycle', 'bicycle'], | ||
['pedestrian', 'traffic_cone'], | ||
] | ||
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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}, | ||
} | ||
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TARGET_ASSIGNER_CONFIG: | ||
FEATURE_MAP_STRIDE: 4 | ||
NUM_MAX_OBJS: 500 | ||
GAUSSIAN_OVERLAP: 0.1 | ||
MIN_RADIUS: 2 | ||
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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] | ||
} | ||
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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 | ||
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POST_PROCESSING: | ||
RECALL_THRESH_LIST: [0.3, 0.5, 0.7] | ||
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EVAL_METRIC: kitti | ||
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OPTIMIZATION: | ||
BATCH_SIZE_PER_GPU: 4 | ||
NUM_EPOCHS: 20 | ||
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OPTIMIZER: adam_onecycle | ||
LR: 0.001 | ||
WEIGHT_DECAY: 0.01 | ||
MOMENTUM: 0.9 | ||
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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 | ||
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LR_WARMUP: False | ||
WARMUP_EPOCH: 1 | ||
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GRAD_NORM_CLIP: 10 |
104 changes: 104 additions & 0 deletions
104
tools/cfgs/nuscenes_models/cbgs_voxel01_res3d_centerpoint.yaml
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CLASS_NAMES: ['car','truck', 'construction_vehicle', 'bus', 'trailer', | ||
'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone'] | ||
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DATA_CONFIG: | ||
_BASE_CONFIG_: cfgs/dataset_configs/nuscenes_dataset.yaml | ||
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MODEL: | ||
NAME: CenterPoint | ||
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VFE: | ||
NAME: MeanVFE | ||
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BACKBONE_3D: | ||
NAME: VoxelResBackBone8x | ||
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MAP_TO_BEV: | ||
NAME: HeightCompression | ||
NUM_BEV_FEATURES: 256 | ||
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BACKBONE_2D: | ||
NAME: BaseBEVBackbone | ||
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LAYER_NUMS: [5, 5] | ||
LAYER_STRIDES: [1, 2] | ||
NUM_FILTERS: [128, 256] | ||
UPSAMPLE_STRIDES: [1, 2] | ||
NUM_UPSAMPLE_FILTERS: [256, 256] | ||
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DENSE_HEAD: | ||
NAME: CenterHead | ||
CLASS_AGNOSTIC: False | ||
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CLASS_NAMES_EACH_HEAD: [ | ||
['car'], | ||
['truck', 'construction_vehicle'], | ||
['bus', 'trailer'], | ||
['barrier'], | ||
['motorcycle', 'bicycle'], | ||
['pedestrian', 'traffic_cone'], | ||
] | ||
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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}, | ||
} | ||
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TARGET_ASSIGNER_CONFIG: | ||
FEATURE_MAP_STRIDE: 8 | ||
NUM_MAX_OBJS: 500 | ||
GAUSSIAN_OVERLAP: 0.1 | ||
MIN_RADIUS: 2 | ||
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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] | ||
} | ||
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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 | ||
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POST_PROCESSING: | ||
RECALL_THRESH_LIST: [0.3, 0.5, 0.7] | ||
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EVAL_METRIC: kitti | ||
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OPTIMIZATION: | ||
BATCH_SIZE_PER_GPU: 4 | ||
NUM_EPOCHS: 30 | ||
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OPTIMIZER: adam_onecycle | ||
LR: 0.003 | ||
WEIGHT_DECAY: 0.01 | ||
MOMENTUM: 0.9 | ||
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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 | ||
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LR_WARMUP: False | ||
WARMUP_EPOCH: 1 | ||
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GRAD_NORM_CLIP: 10 |