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CAGroup3D.yaml
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CAGroup3D.yaml
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CLASS_NAMES: ['bed', 'table', 'sofa', 'chair', 'toilet', 'desk', 'dresser',
'night_stand', 'bookshelf', 'bathtub']
DATA_CONFIG:
_BASE_CONFIG_: cfgs/dataset_configs/sunrgbd_dataset.yaml
VOXEL_SIZE: &VOXEL_SIZE 0.02
N_CLASSES: &N_CLASSES 10
SEMANTIC_THR: &SEMANTIC_THR 0.15
MODEL:
NAME: CAGroup3D
VOXEL_SIZE: *VOXEL_SIZE
SEMANTIC_MIN_THR: 0.05
SEMANTIC_ITER_VALUE: 0.02
SEMANTIC_THR: *SEMANTIC_THR
BACKBONE_3D:
NAME: BiResNet
IN_CHANNELS: 3
OUT_CHANNELS: 64
DENSE_HEAD:
NAME: CAGroup3DHead
IN_CHANNELS: [64, 128, 256, 512]
OUT_CHANNELS: 64
SEMANTIC_THR: *SEMANTIC_THR
VOXEL_SIZE: *VOXEL_SIZE
N_CLASSES: *N_CLASSES
N_REG_OUTS: 8
CLS_KERNEL: 9
WITH_YAW: True
USE_SEM_SCORE: False
EXPAND_RATIO: 3
ASSIGNER:
NAME: CAGroup3DAssigner
LIMIT: 27
TOPK: 18
N_SCALES: 4
LOSS_OFFSET:
NAME: SmoothL1Loss
BETA: 0.04
REDUCTION: sum
LOSS_WEIGHT: 0.2
LOSS_BBOX:
NAME: IoU3DLoss
WITH_YAW: True
LOSS_WEIGHT: 1.0
NMS_CONFIG:
SCORE_THR: 0.01
NMS_PRE: 1000
IOU_THR: 0.5
ROI_HEAD:
NAME: CAGroup3DRoIHead
NUM_CLASSES: *N_CLASSES
MIDDLE_FEATURE_SOURCE: [3]
GRID_SIZE: 7
VOXEL_SIZE: *VOXEL_SIZE
COORD_KEY: 2
MLPS: [[64,128,128]]
CODE_SIZE: 7
ENCODE_SINCOS: True
ROI_PER_IMAGE: 128
ROI_FG_RATIO: 0.9
REG_FG_THRESH: 0.3
ROI_CONV_KERNEL: 5
ENLARGE_RATIO: False
USE_IOU_LOSS: True
USE_GRID_OFFSET: False
USE_SIMPLE_POOLING: True
USE_CENTER_POOLING: True
LOSS_WEIGHTS:
RCNN_CLS_WEIGHT: 1.0 # no use
RCNN_REG_WEIGHT: 0.5
RCNN_IOU_WEIGHT: 1.0
CODE_WEIGHT: [1., 1., 1., 1., 1., 1., 1., 1.]
POST_PROCESSING:
RECALL_THRESH_LIST: [0.25, 0.5]
EVAL_METRIC: scannet
OPTIMIZATION:
BATCH_SIZE_PER_GPU: 8 # 4x4 or 8x2
NUM_EPOCHS: 14
OPTIMIZER: adamW
LR: 0.001
WEIGHT_DECAY: 0.0001
DECAY_STEP_LIST: [8, 11]
LR_DECAY: 0.1
GRAD_NORM_CLIP: 10
# no use
PCT_START: 0.4
DIV_FACTOR: 10
LR_CLIP: 0.0000001
LR_WARMUP: False
WARMUP_EPOCH: 1