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unitr_map+lss.yaml
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unitr_map+lss.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: [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
INFO_PATH: {
'train': [nuscenes_infos_10sweeps_train.pkl],
'test': [nuscenes_infos_10sweeps_val.pkl],
}
CAMERA_CONFIG:
USE_CAMERA: True
IMAGE:
FINAL_DIM: [256,704]
RESIZE_LIM_TRAIN: [0.38, 0.55]
RESIZE_LIM_TEST: [0.48, 0.48]
MAP_CONFIG:
USE_MAP: True
CLASS_NAMES: ['drivable_area', 'ped_crossing', 'walkway', 'stop_line', 'carpark_area', 'divider']
DATA_AUGMENTOR:
DISABLE_AUG_LIST: ['placeholder']
AUG_CONFIG_LIST:
- NAME: random_world_rotation
WORLD_ROT_ANGLE: [-0.78539816, 0.78539816]
- NAME: random_world_translation
NOISE_TRANSLATE_STD: [0.5, 0.5, 0.5]
- NAME: random_world_scaling
WORLD_SCALE_RANGE: [0.9, 1.1]
- NAME: random_world_flip
ALONG_AXIS_LIST: ['x', 'y']
- NAME: imgaug
ROT_LIM: [-5.4, 5.4]
RAND_FLIP: True
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: [0.4, 0.4, 8.0]
- NAME: image_calibrate
- NAME: image_normalize
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
bgr2rgb: True
- NAME: load_bev_segmentation
classes: ['drivable_area', 'ped_crossing', 'walkway', 'stop_line', 'carpark_area', 'divider']
xbound: [-50.0, 50.0, 0.5]
ybound: [-50.0, 50.0, 0.5]
dataset_root: '../data/nuscenes/v1.0-trainval'
location: ['singapore-onenorth', 'singapore-hollandvillage', 'singapore-queenstown', 'boston-seaport']
MODEL:
NAME: UniTRMAP
MM_BACKBONE:
NAME: UniTR
PATCH_EMBED:
in_channels: 3
image_size: [256, 704]
embed_dims: 128
patch_size: 8
patch_norm: True
norm_cfg: {'type': 'LN'}
IMAGE_INPUT_LAYER:
sparse_shape: [32, 88, 1]
d_model: [128]
set_info: [[90, 4]]
window_shape: [[30, 30, 1]]
hybrid_factor: [1, 1, 1] # x, y, z
shifts_list: [[[0, 0, 0], [15, 15, 0]]]
input_image: True
LIDAR_INPUT_LAYER:
sparse_shape: [256, 256, 1]
d_model: [128]
set_info: [[90, 4]]
window_shape: [[30, 30, 1]]
hybrid_factor: [1, 1, 1] # x, y, z
shifts_list: [[[0, 0, 0], [15, 15, 0]]]
set_info: [[90, 4]]
d_model: [128]
nhead: [8]
dim_feedforward: [256]
dropout: 0.0
activation: gelu
checkpoint_blocks: [0,1,2,3]
layer_cfg: {'use_bn': False, 'split_ffn': True, 'split_residual': True}
# fuse backbone config
FUSE_BACKBONE:
IMAGE2LIDAR:
block_start: 3
block_end: 4
point_cloud_range: [-51.2, -51.2, -10.0, 51.2, 51.2, 10.0]
voxel_size: [0.4,0.4,20.0]
sample_num: 20
image2lidar_layer:
sparse_shape: [256, 256, 1]
d_model: [128]
set_info: [[90, 1]]
window_shape: [[30, 30, 1]]
hybrid_factor: [1, 1, 1]
shifts_list: [[[0, 0, 0], [15, 15, 0]]]
expand_max_voxels: 10
LIDAR2IMAGE:
block_start: 1
block_end: 3
point_cloud_range: [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
voxel_size: [0.4,0.4,8.0]
sample_num: 1
lidar2image_layer:
sparse_shape: [96, 264, 6]
d_model: [128]
set_info: [[90, 2]]
window_shape: [[30, 30, 1]]
hybrid_factor: [1, 1, 1]
shifts_list: [[[0, 0, 0], [15, 15, 0]]]
expand_max_voxels: 30
out_indices: [0, 1, 2, 3]
NECK:
NAME: GeneralizedLSSFPN
IN_CHANNELS: [128, 128, 128, 128]
OUT_CHANNELS: 256
START_LEVEL: 0
END_LEVEL: -1
NUM_OUTS: 4
USE_BIAS: True
ALIGN_CORNERS: True
VTRANSFORM:
NAME: LSSTransform
IMAGE_SIZE: [256,704]
IN_CHANNEL: 256
OUT_CHANNEL: 80
FEATURE_SIZE: [32,88]
XBOUND: [-51.2, 51.2, 0.4]
YBOUND: [-51.2, 51.2, 0.4]
ZBOUND: [-10.0, 10.0, 20.0]
DBOUND: [1.0, 60.0, 0.5]
DOWNSAMPLE: 1
USE_CONV_FOR_NO_STRIDE: True
FUSER:
NAME: ConvFuser
IN_CHANNEL: 208
OUT_CHANNEL: 128
VFE:
NAME: DynPillarVFE
WITH_DISTANCE: False
USE_ABSLOTE_XYZ: True
USE_NORM: True
NUM_FILTERS: [ 128, 128 ]
MAP_TO_BEV:
NAME: PointPillarScatter3d
INPUT_SHAPE: [256, 256, 1]
NUM_BEV_FEATURES: 128
BACKBONE_2D:
NAME: BaseBEVBackbone
LAYER_NUMS: [ 5, 5, 5, 5]
LAYER_STRIDES: [2, 2, 2, 2]
NUM_FILTERS: [128, 256, 256, 256]
UPSAMPLE_STRIDES: [1, 2, 4, 8]
NUM_UPSAMPLE_FILTERS: [256, 256, 256, 256]
USE_CONV_FOR_NO_STRIDE: True
DENSE_HEAD:
CLASS_AGNOSTIC: False
NAME: BEVSegmentationHead
GRID_TRANSFORM:
INPUT_SCOPE: [[-51.2, 51.2, 0.8], [-51.2, 51.2, 0.8]]
OUTPUT_SCOPE: [[-50, 50, 0.5], [-50, 50, 0.5]]
LOSS_CONFIG:
gamma: 2.0
alpha: -1
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: 3
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
LOSS_SCALE_FP16: 32