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David Josef Emmerichs
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add config refactor example
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‎tools/cfgs/dataset_configs/modifiers/waymo/multiframe.yaml

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SEQUENCE_CONFIG:
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ENABLED: True
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SAMPLE_OFFSET: [-3, 0]
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TRAIN_WITH_SPEED: True
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DATA_AUGMENTOR:
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AUG_CONFIG_LIST:
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- NAME: gt_sampling
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USE_ROAD_PLANE: False
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DB_INFO_PATH:
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- waymo_processed_data_v0_5_0_waymo_dbinfos_train_sampled_1_multiframe_-4_to_0.pkl
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USE_SHARED_MEMORY: False # set it to True to speed up (it costs about 50GB? shared memory)
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DB_DATA_PATH:
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- waymo_processed_data_v0_5_0_gt_database_train_sampled_1_multiframe_-4_to_0_global.npy
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PREPARE: {
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filter_by_min_points: ['Vehicle:5', 'Pedestrian:5', 'Cyclist:5'],
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filter_by_difficulty: [-1],
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}
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SAMPLE_GROUPS: ['Vehicle:15', 'Pedestrian:10', 'Cyclist:10']
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NUM_POINT_FEATURES: 6
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REMOVE_EXTRA_WIDTH: [0.0, 0.0, 0.0]
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LIMIT_WHOLE_SCENE: True
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FILTER_OBJ_POINTS_BY_TIMESTAMP: True
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TIME_RANGE: [0.3, 0.0] # 0.3s-0.0s indicates 4 frames
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- NAME: random_world_flip
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ALONG_AXIS_LIST: ['x', 'y']
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- NAME: random_world_rotation
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WORLD_ROT_ANGLE: [-0.78539816, 0.78539816]
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- NAME: random_world_scaling
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WORLD_SCALE_RANGE: [0.95, 1.05]
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POINT_FEATURE_ENCODING:
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used_feature_list: ['x', 'y', 'z', 'intensity', 'elongation', 'timestamp']
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src_feature_list: ['x', 'y', 'z', 'intensity', 'elongation', 'timestamp']
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DATA_PROCESSOR:
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- NAME: mask_points_and_boxes_outside_range
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REMOVE_OUTSIDE_BOXES: True
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USE_CENTER_TO_FILTER: True
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- NAME: shuffle_points
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SHUFFLE_ENABLED: {
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'train': True,
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'test': True
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}
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- NAME: transform_points_to_voxels
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VOXEL_SIZE: [0.1, 0.1, 0.15]
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MAX_POINTS_PER_VOXEL: 5
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MAX_NUMBER_OF_VOXELS: {
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'train': 180000,
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'test': 400000
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}

‎tools/cfgs/waymo_models/modifiers/mppnet/16frames.yaml

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DATA_CONFIG:
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SEQUENCE_CONFIG:
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SAMPLE_OFFSET: [-15,0]
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MODEL:
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ROI_HEAD:
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TRANS_INPUT: 64
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ROI_GRID_POOL:
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MLPS: [[64,64]]
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POOL_RADIUS: [0.8]
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NSAMPLE: [16]
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Transformer:
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num_frames: 16
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sequence_stride: 4

‎tools/cfgs/waymo_models/modifiers/mppnet/4frames.yaml

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DATA_CONFIG:
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SEQUENCE_CONFIG:
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SAMPLE_OFFSET: [-3,0]
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MODEL:
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ROI_HEAD:
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TRANS_INPUT: 256
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ROI_GRID_POOL:
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MLPS: [[128,128], [128,128]]
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POOL_RADIUS: [0.8, 1.6]
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NSAMPLE: [16, 16]
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Transformer:
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num_frames: 4

‎tools/cfgs/waymo_models/modifiers/mppnet/e2e_memorybank_inference.yaml

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DATA_CONFIG:
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_BASE_CONFIG_: cfgs/dataset_configs/modifiers/waymo/multiframe.yaml
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_TRANSFORM:
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- name: remove_element
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target: ROI_BOXES_PATH
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- name: remove_element
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target: USE_PREDBOX
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SAMPLED_INTERVAL: {
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'train': 5,
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'test': 1
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}
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POINT_FEATURE_ENCODING:
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encoding_type: absolute_coordinates_encoding
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used_feature_list: ['x', 'y', 'z', 'intensity', 'elongation', 'time']
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src_feature_list: ['x', 'y', 'z', 'intensity', 'elongation', 'time']
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MODEL:
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NAME: MPPNetE2E
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VFE:
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NAME: DynMeanVFE
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BACKBONE_3D:
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NAME: VoxelResBackBone8x
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MAP_TO_BEV:
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NAME: HeightCompression
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NUM_BEV_FEATURES: 256
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BACKBONE_2D:
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NAME: BaseBEVBackbone
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NUM_FRAME: 2
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LAYER_NUMS: [5, 5]
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LAYER_STRIDES: [1, 2]
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NUM_FILTERS: [128, 256]
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UPSAMPLE_STRIDES: [1, 2]
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NUM_UPSAMPLE_FILTERS: [256, 256]
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DENSE_HEAD:
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NAME: CenterHead
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CLASS_AGNOSTIC: False
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CLASS_NAMES_EACH_HEAD: [
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['Vehicle', 'Pedestrian', 'Cyclist']
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]
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SHARED_CONV_CHANNEL: 64
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USE_BIAS_BEFORE_NORM: True
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NUM_HM_CONV: 2
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SEPARATE_HEAD_CFG:
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HEAD_ORDER: ['center', 'center_z', 'dim', 'rot','vel']
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HEAD_DICT: {
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'center': {'out_channels': 2, 'num_conv': 2},
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'center_z': {'out_channels': 1, 'num_conv': 2},
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'dim': {'out_channels': 3, 'num_conv': 2},
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'rot': {'out_channels': 2, 'num_conv': 2},
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'vel': {'out_channels': 2, 'num_conv': 2},
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}
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TARGET_ASSIGNER_CONFIG:
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FEATURE_MAP_STRIDE: 8
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NUM_MAX_OBJS: 500
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GAUSSIAN_OVERLAP: 0.1
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MIN_RADIUS: 2
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LOSS_CONFIG:
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LOSS_WEIGHTS: {
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'cls_weight': 1.0,
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'loc_weight': 2.0,
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'code_weights': [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2]
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}
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POST_PROCESSING:
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SCORE_THRESH: 0.1
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POST_CENTER_LIMIT_RANGE: [-75.2, -75.2, -2, 75.2, 75.2, 4]
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MAX_OBJ_PER_SAMPLE: 500
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NMS_CONFIG:
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NMS_TYPE: nms_gpu
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NMS_THRESH: 0.7
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NMS_PRE_MAXSIZE: 4096
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NMS_POST_MAXSIZE: 500
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ROI_HEAD:
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NAME: MPPNetHeadE2E
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USE_BOX_ENCODING:
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NORM_T0: True
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ALL_YAW_T0: True
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Transformer:
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sequence_stride: 1 #16frame using 4

‎tools/cfgs/waymo_models/mppnet.yaml

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CLASS_NAMES: ['Vehicle', 'Pedestrian', 'Cyclist']
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DATA_CONFIG:
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_BASE_CONFIG_: cfgs/dataset_configs/waymo_dataset.yaml
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PROCESSED_DATA_TAG: 'waymo_processed_data_v0_5_0'
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SAMPLED_INTERVAL: {
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'train': 1,
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'test': 1
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}
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FILTER_EMPTY_BOXES_FOR_TRAIN: True
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DISABLE_NLZ_FLAG_ON_POINTS: True
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SEQUENCE_CONFIG:
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ENABLED: True
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SAMPLE_OFFSET: [-3,0]
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USE_PREDBOX: True
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ROI_BOXES_PATH: {
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'train': '../output/xxxxx/train/result.pkl', # example: predicted boxes of RPN in training set
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'test': '../output/xxxxx/val/result.pkl', # example: predicted boxes of RPN in evalulation set
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}
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DATA_AUGMENTOR:
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DISABLE_AUG_LIST: [ 'placeholder' ]
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AUG_CONFIG_LIST:
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- NAME: random_world_flip
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ALONG_AXIS_LIST: [ 'x', 'y' ]
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- NAME: random_world_rotation
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WORLD_ROT_ANGLE: [ -0.78539816, 0.78539816 ]
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- NAME: random_world_scaling
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WORLD_SCALE_RANGE: [ 0.95, 1.05 ]
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DATA_PROCESSOR:
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- NAME: mask_points_and_boxes_outside_range
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REMOVE_OUTSIDE_BOXES: True
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- NAME: shuffle_points
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SHUFFLE_ENABLED: {
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'train': True,
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'test': True
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}
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POINT_FEATURE_ENCODING: {
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encoding_type: absolute_coordinates_encoding,
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used_feature_list: ['x', 'y', 'z', 'intensity', 'elongation', 'time'],
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src_feature_list: ['x', 'y', 'z', 'intensity', 'elongation', 'time'],
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}
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MODEL:
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NAME: MPPNet
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ROI_HEAD:
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NAME: MPPNetHead
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TRANS_INPUT: 256
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CLASS_AGNOSTIC: True
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USE_BOX_ENCODING:
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ENABLED: True
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AVG_STAGE1_SCORE: True
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USE_TRAJ_EMPTY_MASK: True
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USE_AUX_LOSS: True
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IOU_WEIGHT: [0.5,0.4]
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ROI_GRID_POOL:
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GRID_SIZE: 4
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MLPS: [[128,128], [128,128]]
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POOL_RADIUS: [0.8, 1.6]
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NSAMPLE: [16, 16]
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POOL_METHOD: max_pool
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_TRANSFORM:
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name: copy
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src: TRANS_INPUT
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dest: Transformer.hidden_dim
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Transformer:
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num_lidar_points: 128
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num_proxy_points: 64 # GRID_SIZE*GRID_SIZE*GRID_SIZE
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pos_hidden_dim: 64
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enc_layers: 3
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dim_feedforward: 512
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dropout: 0.1
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nheads: 4
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pre_norm: False
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num_frames: 4
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num_groups: 4
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use_grid_pos:
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enabled: True
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init_type: index
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use_mlp_mixer:
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enabled: True
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hidden_dim: 16
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TARGET_CONFIG:
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BOX_CODER: ResidualCoder
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ROI_PER_IMAGE: 96
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FG_RATIO: 0.5
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REG_AUG_METHOD: single
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ROI_FG_AUG_TIMES: 10
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RATIO: 0.2
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USE_ROI_AUG: True
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USE_TRAJ_AUG:
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ENABLED: True
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THRESHOD: 0.8
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SAMPLE_ROI_BY_EACH_CLASS: True
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CLS_SCORE_TYPE: roi_iou
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CLS_FG_THRESH: 0.75
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CLS_BG_THRESH: 0.25
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CLS_BG_THRESH_LO: 0.1
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HARD_BG_RATIO: 0.8
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REG_FG_THRESH: 0.55
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LOSS_CONFIG:
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CLS_LOSS: BinaryCrossEntropy
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REG_LOSS: smooth-l1
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CORNER_LOSS_REGULARIZATION: True
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LOSS_WEIGHTS: {
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'rcnn_cls_weight': 1.0,
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'rcnn_reg_weight': 1.0,
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'rcnn_corner_weight': 2.0,
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'traj_reg_weight': [2.0, 2.0, 2.0],
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'code_weights': [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
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}
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POST_PROCESSING:
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RECALL_THRESH_LIST: [0.3, 0.5, 0.7]
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SCORE_THRESH: 0.1
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OUTPUT_RAW_SCORE: False
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SAVE_BBOX: False
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EVAL_METRIC: waymo
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NOT_APPLY_NMS_FOR_VEL: True
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NMS_CONFIG:
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MULTI_CLASSES_NMS: False
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NMS_TYPE: nms_gpu
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NMS_THRESH: 0.7
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NMS_PRE_MAXSIZE: 4096
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NMS_POST_MAXSIZE: 500
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OPTIMIZATION:
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BATCH_SIZE_PER_GPU: 2
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NUM_EPOCHS: 6
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OPTIMIZER: adam_onecycle
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LR: 0.003
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WEIGHT_DECAY: 0.01
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MOMENTUM: 0.9
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MOMS: [0.95, 0.85]
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PCT_START: 0.4
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DIV_FACTOR: 10
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DECAY_STEP_LIST: [35, 45]
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LR_DECAY: 0.1
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LR_CLIP: 0.0000001
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LR_WARMUP: False
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WARMUP_EPOCH: 1
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GRAD_NORM_CLIP: 10
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