cbgs_bevfusion.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]
  CAMERA_CONFIG:
      USE_CAMERA: True
      IMAGE:
        FINAL_DIM: [256,704]
        RESIZE_LIM_TRAIN: [0.38, 0.55]
        RESIZE_LIM_TEST: [0.48, 0.48]

  DATA_AUGMENTOR:
    DISABLE_AUG_LIST: ['placeholder']
    AUG_CONFIG_LIST:
      - 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]
      
      - 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
      VOXEL_SIZE: [0.075, 0.075, 0.2]
      MAX_POINTS_PER_VOXEL: 10
      MAX_NUMBER_OF_VOXELS: {
        'train': 120000,
        'test': 160000
      }

    - NAME: image_calibrate
    
    - NAME: image_normalize
      mean: [0.485, 0.456, 0.406]
      std: [0.229, 0.224, 0.225]


MODEL:
  NAME: BevFusion

  VFE:
    NAME: MeanVFE

  BACKBONE_3D:
    NAME: VoxelResBackBone8x
    USE_BIAS: False

  MAP_TO_BEV:
    NAME: HeightCompression
    NUM_BEV_FEATURES: 256
  
  IMAGE_BACKBONE:
    NAME: SwinTransformer
    EMBED_DIMS: 96
    DEPTHS: [2, 2, 6, 2]
    NUM_HEADS: [3, 6, 12, 24]
    WINDOW_SIZE: 7
    MLP_RATIO: 4
    DROP_RATE: 0.
    ATTN_DROP_RATE: 0.
    DROP_PATH_RATE: 0.2
    PATCH_NORM: True
    OUT_INDICES: [1, 2, 3]
    WITH_CP: False
    CONVERT_WEIGHTS: True
    INIT_CFG:
      type: Pretrained
      # checkpoint: swint-nuimages-pretrained.pth
      checkpoint: /slurm_data/shichen/package/tomopc_cu111/OpenPCDet/tmp/pretrained/swint-nuimages-pretrained.pth
  
  NECK:
    NAME: GeneralizedLSSFPN
    IN_CHANNELS: [192, 384, 768]
    OUT_CHANNELS: 256
    START_LEVEL: 0
    END_LEVEL: -1
    NUM_OUTS: 3
  
  VTRANSFORM:
    NAME: DepthLSSTransform
    IMAGE_SIZE: [256, 704]
    IN_CHANNEL: 256
    OUT_CHANNEL: 80
    FEATURE_SIZE: [32, 88]
    XBOUND: [-54.0, 54.0, 0.3]
    YBOUND: [-54.0, 54.0, 0.3]
    ZBOUND: [-10.0, 10.0, 20.0]
    DBOUND: [1.0, 60.0, 0.5]
    DOWNSAMPLE: 2
  
  FUSER:
    NAME: ConvFuser
    IN_CHANNEL: 336
    OUT_CHANNEL: 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]
    USE_CONV_FOR_NO_STRIDE: True


  DENSE_HEAD:
    CLASS_AGNOSTIC: False
    NAME: TransFusionHead

    USE_BIAS_BEFORE_NORM: False

    NUM_PROPOSALS: 200
    HIDDEN_CHANNEL: 128
    NUM_CLASSES: 10
    NUM_HEADS: 8
    NMS_KERNEL_SIZE: 3
    FFN_CHANNEL: 256
    DROPOUT: 0.1
    BN_MOMENTUM: 0.1
    ACTIVATION: relu

    NUM_HM_CONV: 2
    SEPARATE_HEAD_CFG:
      HEAD_ORDER: ['center', 'height', 'dim', 'rot', 'vel']
      HEAD_DICT: {
          'center': {'out_channels': 2, 'num_conv': 2},
          'height': {'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
      DATASET: nuScenes
      GAUSSIAN_OVERLAP: 0.1
      MIN_RADIUS: 2
      HUNGARIAN_ASSIGNER:
        cls_cost: {'gamma': 2.0, 'alpha': 0.25, 'weight': 0.15}
        reg_cost: {'weight': 0.25}
        iou_cost: {'weight': 0.25}
    
    LOSS_CONFIG:
      LOSS_WEIGHTS: {
              'cls_weight': 1.0,
              'bbox_weight': 0.25,
              'hm_weight': 1.0,
              'code_weights': [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2]
          }
      LOSS_CLS:
        use_sigmoid: True
        gamma: 2.0
        alpha: 0.25
      
    POST_PROCESSING:
      SCORE_THRESH: 0.0
      POST_CENTER_RANGE: [-61.2, -61.2, -10.0, 61.2, 61.2, 10.0]

  POST_PROCESSING:
    RECALL_THRESH_LIST: [0.3, 0.5, 0.7]
    SCORE_THRESH: 0.1
    OUTPUT_RAW_SCORE: False

    EVAL_METRIC: kitti



OPTIMIZATION:
  BATCH_SIZE_PER_GPU: 3
  NUM_EPOCHS: 6

  OPTIMIZER: adam_cosineanneal
  LR: 0.0001
  WEIGHT_DECAY: 0.01
  MOMENTUM: 0.9
  BETAS: [0.9, 0.999]

  MOMS: [0.9, 0.8052631]
  PCT_START: 0.4
  WARMUP_ITER: 500

  DECAY_STEP_LIST: [35, 45]
  LR_WARMUP: False
  WARMUP_EPOCH: 1

  GRAD_NORM_CLIP: 35

  LOSS_SCALE_FP16: 32