unitr_map.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: [-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: []

    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