CRB-active-3Ddet
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Published
20 hours ago •
Luoyadan
Luoyadan
ONE-STAGE detector cfg
Thanks for sharing such an excellent work. Currently, there is only the cfg for PVRCNN. Is it possible to also share the configuration of One-stage methods? I tried to configure one, but it seems the current version of crb_sampling.py is not directly appliacable to the one-stage methods since it have a different loss function structure. Thx!
Hi,
You can try this config file but you have to carefully modify some code in the detectors/models to pass the required variables to queried strategies. Also, we use secondiou which is an extended one-stage model because CRB require dropout layer which is already included in the secondiou config file :
CLASS_NAMES: ['car','truck', 'construction_vehicle', 'bus', 'trailer',
'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone']
DATA_CONFIG:
_BASE_CONFIG_: cfgs/dataset_configs/nuscenes_dataset.yaml
MODEL:
NAME: SECONDNetIoU
VFE:
NAME: MeanVFE
BACKBONE_3D:
NAME: VoxelBackBone8x
MAP_TO_BEV:
NAME: HeightCompression
NUM_BEV_FEATURES: 256
BACKBONE_2D:
NAME: BaseBEVBackbone
LAYER_NUMS: [5, 5]
LAYER_STRIDES: [1, 2]
NUM_FILTERS: [128, 256]
UPSAMPLE_STRIDES: [1, 2]
NUM_UPSAMPLE_FILTERS: [256, 256]
DENSE_HEAD:
NAME: AnchorHeadMulti
CLASS_AGNOSTIC: False
DIR_OFFSET: 0.78539
DIR_LIMIT_OFFSET: 0.0
NUM_DIR_BINS: 2
USE_MULTIHEAD: True
SEPARATE_MULTIHEAD: False
ANCHOR_GENERATOR_CONFIG: [
{
'class_name': car,
'anchor_sizes': [[4.63, 1.97, 1.74]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-0.95],
'align_center': False,
'feature_map_stride': 8,
'matched_threshold': 0.6,
'unmatched_threshold': 0.45
},
{
'class_name': truck,
'anchor_sizes': [[6.93, 2.51, 2.84]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-0.6],
'align_center': False,
'feature_map_stride': 8,
'matched_threshold': 0.55,
'unmatched_threshold': 0.4
},
{
'class_name': construction_vehicle,
'anchor_sizes': [[6.37, 2.85, 3.19]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-0.225],
'align_center': False,
'feature_map_stride': 8,
'matched_threshold': 0.5,
'unmatched_threshold': 0.35
},
{
'class_name': bus,
'anchor_sizes': [[10.5, 2.94, 3.47]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-0.085],
'align_center': False,
'feature_map_stride': 8,
'matched_threshold': 0.55,
'unmatched_threshold': 0.4
},
{
'class_name': trailer,
'anchor_sizes': [[12.29, 2.90, 3.87]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [0.115],
'align_center': False,
'feature_map_stride': 8,
'matched_threshold': 0.5,
'unmatched_threshold': 0.35
},
{
'class_name': barrier,
'anchor_sizes': [[0.50, 2.53, 0.98]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-1.33],
'align_center': False,
'feature_map_stride': 8,
'matched_threshold': 0.55,
'unmatched_threshold': 0.4
},
{
'class_name': motorcycle,
'anchor_sizes': [[2.11, 0.77, 1.47]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-1.085],
'align_center': False,
'feature_map_stride': 8,
'matched_threshold': 0.5,
'unmatched_threshold': 0.3
},
{
'class_name': bicycle,
'anchor_sizes': [[1.70, 0.60, 1.28]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-1.18],
'align_center': False,
'feature_map_stride': 8,
'matched_threshold': 0.5,
'unmatched_threshold': 0.35
},
{
'class_name': pedestrian,
'anchor_sizes': [[0.73, 0.67, 1.77]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-0.935],
'align_center': False,
'feature_map_stride': 8,
'matched_threshold': 0.6,
'unmatched_threshold': 0.4
},
{
'class_name': traffic_cone,
'anchor_sizes': [[0.41, 0.41, 1.07]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-1.285],
'align_center': False,
'feature_map_stride': 8,
'matched_threshold': 0.6,
'unmatched_threshold': 0.4
},
]
SHARED_CONV_NUM_FILTER: 64
RPN_HEAD_CFGS: [
{
'HEAD_CLS_NAME': ['car'],
},
{
'HEAD_CLS_NAME': ['truck', 'construction_vehicle'],
},
{
'HEAD_CLS_NAME': ['bus', 'trailer'],
},
{
'HEAD_CLS_NAME': ['barrier'],
},
{
'HEAD_CLS_NAME': ['motorcycle', 'bicycle'],
},
{
'HEAD_CLS_NAME': ['pedestrian', 'traffic_cone'],
},
]
SEPARATE_REG_CONFIG:
NUM_MIDDLE_CONV: 1
NUM_MIDDLE_FILTER: 64
REG_LIST: ['reg:2', 'height:1', 'size:3', 'angle:2', 'velo:2']
TARGET_ASSIGNER_CONFIG:
NAME: AxisAlignedTargetAssigner
POS_FRACTION: -1.0
SAMPLE_SIZE: 512
NORM_BY_NUM_EXAMPLES: False
MATCH_HEIGHT: False
BOX_CODER: ResidualCoder
BOX_CODER_CONFIG: {
'code_size': 9,
'encode_angle_by_sincos': True
}
LOSS_CONFIG:
REG_LOSS_TYPE: WeightedL1Loss
LOSS_WEIGHTS: {
'pos_cls_weight': 1.0,
'neg_cls_weight': 2.0,
'cls_weight': 1.0,
'loc_weight': 0.25,
'dir_weight': 0.2,
'code_weights': [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2]
}
ROI_HEAD:
NAME: SECONDHead
CLASS_AGNOSTIC: True
SAMPLING_ROUND: 5
SHARED_FC: [256, 256]
IOU_FC: [256, 256]
DP_RATIO: 0.3
NMS_CONFIG:
TRAIN:
NMS_TYPE: nms_gpu
MULTI_CLASSES_NMS: False
NMS_PRE_MAXSIZE: 9000
NMS_POST_MAXSIZE: 512
NMS_THRESH: 0.8
TEST:
NMS_TYPE: nms_gpu
MULTI_CLASSES_NMS: False
NMS_PRE_MAXSIZE: 1024
NMS_POST_MAXSIZE: 128
NMS_THRESH: 0.7
ROI_GRID_POOL:
GRID_SIZE: 7
IN_CHANNEL: 512
DOWNSAMPLE_RATIO: 8
TARGET_CONFIG:
BOX_CODER: ResidualCoder
ROI_PER_IMAGE: 128
FG_RATIO: 0.5
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:
IOU_LOSS: BinaryCrossEntropy
LOSS_WEIGHTS: {
'rcnn_iou_weight': 1.0,
'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
EVAL_METRIC: kitti
NMS_CONFIG:
MULTI_CLASSES_NMS: True
NMS_TYPE: nms_gpu
NMS_THRESH: 0.2
NMS_PRE_MAXSIZE: 1000
NMS_POST_MAXSIZE: 83
OPTIMIZATION:
BATCH_SIZE_PER_GPU: 4
NUM_EPOCHS: 20
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
ACTIVE_TRAIN:
METHOD: greedy_boxbadge
AGGREGATION: mean
PRE_TRAIN_SAMPLE_NUMS: 1000
PRE_TRAIN_EPOCH_NUMS: 40
TRAIN_RESUME: True
SELECT_NUMS: 1000
SELECT_LABEL_EPOCH_INTERVAL: 40
TOTAL_BUDGET_NUMS: 4000
ACTIVE_CONFIG:
K1: 3
K2: 2
