centerpoint.yaml

CLASS_NAMES: ['Car', 'Bus', 'Truck', 'Pedestrian', 'Cyclist']

DATA_CONFIG:
    _BASE_CONFIG_: cfgs/dataset_configs/once_dataset.yaml

MODEL:
    NAME: CenterPoint

    VFE:
        NAME: MeanVFE

    BACKBONE_3D:
        NAME: VoxelResBackBone8x

    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: CenterHead
        CLASS_AGNOSTIC: False

        CLASS_NAMES_EACH_HEAD: [
            ['Car', 'Bus', 'Truck', 'Pedestrian', 'Cyclist']
        ]

        SHARED_CONV_CHANNEL: 64
        USE_BIAS_BEFORE_NORM: True  # TODO
        NUM_HM_CONV: 2  # TODO
        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},
            }


        # DATASET: once
        # MODE: 3d

        TARGET_ASSIGNER_CONFIG:
            FEATURE_MAP_STRIDE: 8
            NUM_MAX_OBJS: 500
            GAUSSIAN_OVERLAP: 0.1
            MIN_RADIUS: 2
            # tasks: *tasks_head
            DENSE_REG: 1
            # mapping: {
            #   "Car": 1,
            #   "Bus": 2,
            #   "Truck": 3,
            #   "Pedestrian": 4,
            #   "Cyclist": 5
            # }

        LOSS_CONFIG:
            LOSS_WEIGHTS: {
                'cls_weight': 1.0,
                'loc_weight': 1.0,
                # weight: 0.25
                'code_weights': [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
            }

        # TEST_CONFIG:
        #   pc_range: [-75.2, -75.2]
        #   out_size_factor: 8
        #   voxel_size: [0.1, 0.1]
        #   nms:
        #     train:
        #       use_iou_3d_nms: True
        #       use_rotate_nms: False
        #       use_maxpool_nms: False
        #       use_circle_nms: False
        #       min_radius: [4, 10, 12, 0.175, 0.85]
        #       nms_iou_threshold: 0.8
        #       nms_pre_max_size: 1500
        #       nms_post_max_size: 80
        #     test:
        #       use_iou_3d_nms: True
        #       use_rotate_nms: False
        #       use_maxpool_nms: False
        #       use_circle_nms: False
        #       min_radius: [4, 10, 12, 0.175, 0.85]
        #       nms_iou_threshold: 0.01
        #       nms_pre_max_size: 500
        #       nms_post_max_size: 83

        POST_PROCESSING:
            SCORE_THRESH: 0.1
            POST_CENTER_LIMIT_RANGE: [-75.2, -75.2, -5.0, 75.2, 75.2, 3.0]
            MAX_OBJ_PER_SAMPLE: 500
            NMS_CONFIG:
                MULTI_CLASSES_NMS: False
                NMS_TYPE: nms_gpu
                NMS_THRESH: 0.01
                NMS_PRE_MAXSIZE: 4096
                NMS_POST_MAXSIZE: 500
            

    POST_PROCESSING:
      RECALL_THRESH_LIST: [0.3, 0.5, 0.7]

      OUTPUT_RAW_SCORE: False

      EVAL_METRIC: once

OPTIMIZATION:
    BATCH_SIZE_PER_GPU: 4
    NUM_EPOCHS: 80

    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: 35