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hgsfusion_tj4d.yaml
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# 本配置文件为 caddn + pillarnet + 无bev backbone + 无深度预测 + 多层image view feature + SE特征融合 + image backbone冻结权重
# 使用虚拟点k=5 + 分类标签 + one hot + 2d占用网络 + focal loss + 比pillarnet大的bev feat
# 训练 15 epo
CLASS_NAMES: ['Car', 'Pedestrian', 'Cyclist', 'Truck']
DATA_CONFIG:
_BASE_CONFIG_: ./tools/cfgs/dataset_configs/tj4d_fusion.yaml
# POINT_CLOUD_RANGE: [2, -30.08, -3.0, 46.8, 30.08, 1.0]
POINT_CLOUD_RANGE: [0, -39.68, -4, 69.12, 39.68, 2]
GET_ITEM_LIST: ["points", "images", "calib_matricies", "gt_boxes2d"]
USE_VIRTUAL_POINTS: True
VIRTUAL_POINT_PREFIX: 'mask_maskformer_with_label_k_1_gauss_k_4_uniform'
POINT_FEATURE_ENCODING: {
encoding_type: absolute_coordinates_encoding,
used_feature_list: ['x', 'y', 'z', 'V_r', 'Range', 'Power', 'Alpha', 'Beta', 'label1', 'label2', 'label3', 'label4', 'label5', 'label6', 'label7', 'label8', 'idf1', 'idf2'],
src_feature_list: ['x', 'y', 'z', 'V_r', 'Range', 'Power', 'Alpha', 'Beta', 'label1', 'label2', 'label3', 'label4', 'label5', 'label6', 'label7', 'label8', 'idf1', 'idf2'],
}
DATA_PROCESSOR:
- NAME: mask_points_and_boxes_outside_range
REMOVE_OUTSIDE_BOXES: True
- NAME: calculate_grid_size
VOXEL_SIZE: [0.32, 0.32, 0.32] # grid size for image, bev shape 160*160
- NAME: shuffle_points # PP_radar
SHUFFLE_ENABLED: {
'train': True,
'test': False
}
DATA_AUGMENTOR:
DISABLE_AUG_LIST: ['gt_sampling']
AUG_CONFIG_LIST:
- NAME: random_world_flip # PP_radar
ALONG_AXIS_LIST: ['x']
- NAME: random_image_flip_fusion
ALONG_AXIS_LIST: ['horizontal']
- NAME: random_world_scaling # PP_radar
WORLD_SCALE_RANGE: [0.95, 1.05]
MODEL:
NAME: CaDDN
FusionVFE:
NAME: FusionVFE
ImageVFE:
NAME: ImageVFE
USE_DEPTH: False
FFN:
NAME: DepthFFN
DDN:
NAME: DDNDeepLabV3
BACKBONE_NAME: ResNet101
ARGS: {
"freeze_backbone": True,
"feat_extract_layer": ["layer1", "layer2", "layer3", "layer4"],
"pretrained_path": "../checkpoints/deeplabv3_resnet101_coco-586e9e4e.pth"
}
CHANNEL_REDUCE: {
"in_channels": [256, 512, 1024, 2048],
"out_channels": 64,
"kernel_size": 1,
"stride": 1,
"bias": False
}
DISCRETIZE: {
"mode": LID,
"num_bins": 80,
"depth_min": 1.0,
"depth_max": 51.2
}
LOSS:
NAME: DDNLoss
ARGS: {
'weight': 3.0,
'alpha': 0.25,
'gamma': 2.0,
'fg_weight': 13,
'bg_weight': 1
}
F2V:
NAME: FrustumToVoxelMultiScale
FEATURE_NUM: 4
FUSE_MODE: CONCAT
OUT_CHANNELS: 128
SAMPLER: {
"mode": "bilinear",
"padding_mode": "zeros"
}
RadarBackbone:
NAME: PillarNet
READER:
USE_VIRTUAL_POINT: True
PILLAR_SIZE: 0.32
NUM_FILTERS: [32]
NUM_INPUT_FEATURES: 31 # x y z rcs v v_r time
PC_RANGE: [0, -39.68, -4, 69.12, 39.68, 2]
DATASET: 'tj4d'
BACKBONE:
IN_PLANES: 32
DS_FACTOR: 4
OUT_INDICES: [0, 1, 2]
NECK:
IN_CHANNELS: [160, 192]
OUT_CHANNELS: [128, 128]
SCALE_FACTOR: 2
RadarOccupancy:
NAME: RadarOccupancy2DV2
RADAR_INPUT_CHANNELS: 128
USE_OCC_LOSS: True
USE_ASPP: True
ASPP_SHAPE: 3
MAP_TO_BEV:
NUM_BEV_FEATURES: 128
ARGS: {
"kernel_size": 1,
"stride": 1,
"bias": False
}
NUM_OUT_BEV_FEATURES: 128
FUSION_AFTER_BEV:
NAME: FusionAfterBEVSEDirect
NUM_BEV_FEATURES: 256
RADAR_IN_CHANNELS: 128
IMAGE_OUT_CHANNELS: 128
RADAR_OUT_CHANNELS: 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': [[4.56, 1.84, 1.70]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-1.78],
'align_center': False,
'feature_map_stride': 1,
'matched_threshold': 0.6,
'unmatched_threshold': 0.45
},
{
'class_name': 'Truck',
'anchor_sizes': [[10.76, 2.66, 3.47]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-1.78],
'align_center': False,
'feature_map_stride': 1,
'matched_threshold': 0.6,
'unmatched_threshold': 0.45
},
{
'class_name': 'Pedestrian',
'anchor_sizes': [[0.8, 0.6, 1.69]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-0.6],
'align_center': False,
'feature_map_stride': 1,
'matched_threshold': 0.5,
'unmatched_threshold': 0.35
},
{
'class_name': 'Cyclist',
'anchor_sizes': [[1.77, 0.78, 1.60]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-0.6],
'align_center': False,
'feature_map_stride': 1,
'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: 2
NUM_EPOCHS: 40
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