CLASS_NAMES: ['Vehicle', 'Pedestrian', 'Cyclist'] DATA_CONFIG: _BASE_CONFIG_: cfgs/dataset_configs/waymo_dataset.yaml PROCESSED_DATA_TAG: 'waymo_processed_data_v0_5_0' SAMPLED_INTERVAL: { 'train': 1, 'test': 1 } FILTER_EMPTY_BOXES_FOR_TRAIN: True DISABLE_NLZ_FLAG_ON_POINTS: True SEQUENCE_CONFIG: ENABLED: True SAMPLE_OFFSET: [-3,0] USE_PREDBOX: True ROI_BOXES_PATH: { 'train': '../output/xxxxx/train/result.pkl', # example: predicted boxes of RPN in training set 'test': '../output/xxxxx/val/result.pkl', # example: predicted boxes of RPN in evalulation set } 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: [ 0.95, 1.05 ] DATA_PROCESSOR: - NAME: mask_points_and_boxes_outside_range REMOVE_OUTSIDE_BOXES: True - NAME: shuffle_points SHUFFLE_ENABLED: { 'train': True, 'test': True } POINT_FEATURE_ENCODING: { encoding_type: absolute_coordinates_encoding, used_feature_list: ['x', 'y', 'z', 'intensity', 'elongation','time'], src_feature_list: ['x', 'y', 'z', 'intensity', 'elongation','time'], } MODEL: NAME: MPPNet ROI_HEAD: NAME: MPPNetHead TRANS_INPUT: 256 CLASS_AGNOSTIC: True USE_BOX_ENCODING: ENABLED: True AVG_STAGE1_SCORE: True USE_TRAJ_EMPTY_MASK: True USE_AUX_LOSS: True IOU_WEIGHT: [0.5,0.4] ROI_GRID_POOL: GRID_SIZE: 4 MLPS: [[128,128], [128,128]] POOL_RADIUS: [0.8, 1.6] NSAMPLE: [16, 16] POOL_METHOD: max_pool Transformer: num_lidar_points: 128 num_proxy_points: 64 # GRID_SIZE*GRID_SIZE*GRID_SIZE pos_hidden_dim: 64 enc_layers: 3 dim_feedforward: 512 hidden_dim: 256 #equal to ROI_HEAD.TRANS_INPUT dropout: 0.1 nheads: 4 pre_norm: False num_frames: 4 num_groups: 4 use_grid_pos: enabled: True init_type: index use_mlp_mixer: enabled: True hidden_dim: 16 TARGET_CONFIG: BOX_CODER: ResidualCoder ROI_PER_IMAGE: 96 FG_RATIO: 0.5 REG_AUG_METHOD: single ROI_FG_AUG_TIMES: 10 RATIO: 0.2 USE_ROI_AUG: True USE_TRAJ_AUG: ENABLED: True THRESHOD: 0.8 SAMPLE_ROI_BY_EACH_CLASS: True CLS_SCORE_TYPE: roi_iou CLS_FG_THRESH: 0.75 CLS_BG_THRESH: 0.25 CLS_BG_THRESH_LO: 0.1 HARD_BG_RATIO: 0.8 REG_FG_THRESH: 0.55 LOSS_CONFIG: CLS_LOSS: BinaryCrossEntropy REG_LOSS: smooth-l1 CORNER_LOSS_REGULARIZATION: True LOSS_WEIGHTS: { 'rcnn_cls_weight': 1.0, 'rcnn_reg_weight': 1.0, 'rcnn_corner_weight': 2.0, 'traj_reg_weight': [2.0, 2.0, 2.0], 'code_weights': [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0] } POST_PROCESSING: RECALL_THRESH_LIST: [0.3, 0.5, 0.7] SCORE_THRESH: 0.1 OUTPUT_RAW_SCORE: False SAVE_BBOX: False EVAL_METRIC: waymo NOT_APPLY_NMS_FOR_VEL: True NMS_CONFIG: MULTI_CLASSES_NMS: False NMS_TYPE: nms_gpu NMS_THRESH: 0.7 NMS_PRE_MAXSIZE: 4096 NMS_POST_MAXSIZE: 500 OPTIMIZATION: BATCH_SIZE_PER_GPU: 2 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