cbgs_voxel0075_voxelnext.yaml

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: [-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]
    INFO_PATH: {
        'train': [nuscenes_infos_10sweeps_train.pkl],
        'test': [nuscenes_infos_10sweeps_val.pkl],
    }
    DATA_AUGMENTOR:
        DISABLE_AUG_LIST: ['placeholder']
        AUG_CONFIG_LIST:
            - NAME: gt_sampling
              DB_INFO_PATH:
                - nuscenes_dbinfos_10sweeps_withvelo.pkl
              USE_SHARED_MEMORY: False  #True  # set it to True to speed up (it costs about 15GB shared memory)
              DB_DATA_PATH:
                - nuscenes_dbinfos_10sweeps_withvelo_global.pkl.npy
              PREPARE: {
                filter_by_min_points: [
                    'car:5','truck:5', 'construction_vehicle:5', 'bus:5', 'trailer:5',
                    'barrier:5', 'motorcycle:5', 'bicycle:5', 'pedestrian:5', 'traffic_cone:5'
                ],
              }

              SAMPLE_GROUPS: [
                'car:2','truck:2', 'construction_vehicle:2', 'bus:2', 'trailer:2',
                'barrier:2', 'motorcycle:2', 'bicycle:2', 'pedestrian:2', 'traffic_cone:2'
              ]

              NUM_POINT_FEATURES: 5
              DATABASE_WITH_FAKELIDAR: False
              REMOVE_EXTRA_WIDTH: [0.0, 0.0, 0.0]
              LIMIT_WHOLE_SCENE: True

            - NAME: random_world_flip
              ALONG_AXIS_LIST: ['x', 'y']

            - NAME: random_world_rotation
              WORLD_ROT_ANGLE: [-0.78539816, 0.78539816]

            - NAME: random_world_scaling
              WORLD_SCALE_RANGE: [0.9, 1.1]
            
            - NAME: random_world_translation
              NOISE_TRANSLATE_STD: [0.5, 0.5, 0.5]
              

    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: [0.075, 0.075, 0.2]
          MAX_POINTS_PER_VOXEL: 10
          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: [
            ['car'], 
            ['truck', 'construction_vehicle'],
            ['bus', 'trailer'],
            ['barrier'],
            ['motorcycle', 'bicycle'],
            ['pedestrian', 'traffic_cone'],
        ]
        
        SHARED_CONV_CHANNEL: 128
        KERNEL_SIZE_HEAD: 1
        
        USE_BIAS_BEFORE_NORM: True
        NUM_HM_CONV: 2
        SEPARATE_HEAD_CFG:
            HEAD_ORDER: ['center', 'center_z', 'dim', 'rot', 'vel']
            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},
                'vel': {'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, 1.0, 1.0]
            }

        POST_PROCESSING:
            SCORE_THRESH: 0.1
            POST_CENTER_LIMIT_RANGE: [-61.2, -61.2, -10.0, 61.2, 61.2, 10.0]
            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: 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