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cbgs_voxel01_voxelnext_headkernel3.yaml 3.28 KB
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Add support for VoxelNeXt (#1309)  
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CLASS_NAMES: ['Regular_vehicle', 'Pedestrian', 'Bicyclist', 'Motorcyclist', 'Wheeled_rider',
            'Bollard', 'Construction_cone', 'Sign', 'Construction_barrel', 'Stop_sign', 'Mobile_pedestrian_crossing_sign',
            'Large_vehicle', 'Bus', 'Box_truck', 'Truck', 'Vehicular_trailer', 'Truck_cab', 'School_bus', 'Articulated_bus', 
            'Message_board_trailer', 'Bicycle', 'Motorcycle', 'Wheeled_device', 'Wheelchair', 'Stroller', 'Dog']

DATA_CONFIG:
    _BASE_CONFIG_: cfgs/dataset_configs/argo2_dataset.yaml

    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
          VOXEL_SIZE: [0.1, 0.1, 0.2]
          MAX_POINTS_PER_VOXEL: 20
          MAX_NUMBER_OF_VOXELS: {
            'train': 120000,
            'test': 160000
          }

MODEL:
    NAME: VoxelNeXt

    VFE:
        NAME: MeanVFE

    BACKBONE_3D:
        NAME: VoxelResBackBone8xVoxelNeXt

    DENSE_HEAD:
        NAME: VoxelNeXtHead
        CLASS_AGNOSTIC: False
        INPUT_FEATURES: 128

        CLASS_NAMES_EACH_HEAD: [
            ['Regular_vehicle',],
            ['Pedestrian', 'Bicyclist', 'Motorcyclist', 'Wheeled_rider'],
            ['Bollard', 'Construction_cone', 'Sign', 'Construction_barrel', 'Stop_sign', 'Mobile_pedestrian_crossing_sign'],
            ['Large_vehicle', 'Bus', 'Box_truck', 'Truck', 'Vehicular_trailer', 'Truck_cab', 'School_bus', 'Articulated_bus', 'Message_board_trailer'],
            ['Bicycle', 'Motorcycle', 'Wheeled_device', 'Wheelchair', 'Stroller'],
            ['Dog'],
        ]

        KERNEL_SIZE_HEAD: 3
        SHARED_CONV_CHANNEL: 128
        USE_BIAS_BEFORE_NORM: True
        NUM_HM_CONV: 2
        SEPARATE_HEAD_CFG:
            HEAD_ORDER: ['center', 'center_z', 'dim', 'rot']
            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},
            }

        TARGET_ASSIGNER_CONFIG:
            FEATURE_MAP_STRIDE: 8
            NUM_MAX_OBJS: 500
            GAUSSIAN_OVERLAP: 0.1
            MIN_RADIUS: 2

        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]
            }

        POST_PROCESSING:
            SCORE_THRESH: 0.1
            POST_CENTER_LIMIT_RANGE: [-200, -200, -20, 200, 200, 20]
            MAX_OBJ_PER_SAMPLE: 500
            NMS_CONFIG:
                NMS_TYPE: nms_gpu
                NMS_THRESH: 0.2
                NMS_PRE_MAXSIZE: 1000
                NMS_POST_MAXSIZE: 83

    POST_PROCESSING:
        RECALL_THRESH_LIST: [0.3, 0.5, 0.7]

        EVAL_METRIC: kitti



OPTIMIZATION:
    BATCH_SIZE_PER_GPU: 4
    NUM_EPOCHS: 6

    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