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open-mmlab / OpenPCDet

OpenPCDet Toolbox for LiDAR-based 3D Object Detection.
Apache License 2.0
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Test my PVRCNN in kitti,there is just bev mAP #1161

Closed Rody1911641 closed 1 year ago

Rody1911641 commented 1 year ago

This is my result: Car AP@0.70, 0.70, 0.70: bbox AP:0.0000, 0.0000, 0.0000 bev AP:77.9522, 65.4295, 64.4617 3d AP:0.0000, 0.0000, 0.0000 aos AP:0.00, 0.00, 0.00 Car AP_R40@0.70, 0.70, 0.70: bbox AP:0.0000, 0.0000, 0.0000 bev AP:79.5713, 66.7626, 64.5092 3d AP:0.0000, 0.0000, 0.0000 aos AP:0.00, 0.00, 0.00 Car AP@0.70, 0.50, 0.50: bbox AP:0.0000, 0.0000, 0.0000 bev AP:89.4668, 86.4132, 86.2657 3d AP:0.0000, 0.0000, 0.0000 aos AP:0.00, 0.00, 0.00 Car AP_R40@0.70, 0.50, 0.50: bbox AP:0.0000, 0.0000, 0.0000 bev AP:93.9974, 88.5902, 88.6612 3d AP:0.0000, 0.0000, 0.0000 aos AP:0.00, 0.00, 0.00

This is my config: CLASS_NAMES: ['Car']

DATA_CONFIG: _BASECONFIG: cfgs/dataset_configs/kitti_car_DA.yaml CLASS_NAMES: ['Car'] FOV_POINTS_ONLY: True SHIFT_COOR: [0.0, 0.0, 1.8]

MODEL: NAME: PVRCNNPlusPlus

VFE:
    NAME: MeanVFE

BACKBONE_3D:
    NAME: VoxelBackBone8x

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: AnchorHeadSingle
    CLASS_AGNOSTIC: False

    USE_DIRECTION_CLASSIFIER: True
    DIR_OFFSET: 0.78539
    DIR_LIMIT_OFFSET: 0.0
    NUM_DIR_BINS: 2

    ANCHOR_GENERATOR_CONFIG: [
        {
            'class_name': 'car',
            'anchor_sizes': [[4.7, 2.1, 1.7]],
            'anchor_rotations': [0, 1.57],
            'anchor_bottom_heights': [0],
            'align_center': False,
            'feature_map_stride': 8,
            'matched_threshold': 0.55,
            'unmatched_threshold': 0.4
        }
    ]

    TARGET_ASSIGNER_CONFIG:
        NAME: AxisAlignedTargetAssigner
        POS_FRACTION: -1.0
        SAMPLE_SIZE: 512
        NORM_BY_NUM_EXAMPLES: False
        MATCH_HEIGHT: False
        BOX_CODER: ResidualCoder

    LOSS_CONFIG:
        LOSS_WEIGHTS: {
            'cls_weight': 1.0,
            'loc_weight': 2.0,
            'dir_weight': 0.2,
            'code_weights': [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
        }

PFE:
    NAME: VoxelSetAbstraction
    POINT_SOURCE: raw_points
    NUM_KEYPOINTS: 2048
    NUM_OUTPUT_FEATURES: 90
    SAMPLE_METHOD: SPC
    SPC_SAMPLING:
        NUM_SECTORS: 6
        SAMPLE_RADIUS_WITH_ROI: 1.6

    FEATURES_SOURCE: ['bev', 'x_conv3', 'x_conv4', 'raw_points']
    SA_LAYER:
        raw_points:
            NAME: VectorPoolAggregationModuleMSG
            NUM_GROUPS: 2
            LOCAL_AGGREGATION_TYPE: local_interpolation
            NUM_REDUCED_CHANNELS: 1
            NUM_CHANNELS_OF_LOCAL_AGGREGATION: 32
            MSG_POST_MLPS: [ 32 ]
            FILTER_NEIGHBOR_WITH_ROI: True
            RADIUS_OF_NEIGHBOR_WITH_ROI: 2.4

            GROUP_CFG_0:
                NUM_LOCAL_VOXEL: [ 2, 2, 2 ]
                MAX_NEIGHBOR_DISTANCE: 0.2
                NEIGHBOR_NSAMPLE: -1
                POST_MLPS: [ 32, 32 ]
            GROUP_CFG_1:
                NUM_LOCAL_VOXEL: [ 3, 3, 3 ]
                MAX_NEIGHBOR_DISTANCE: 0.4
                NEIGHBOR_NSAMPLE: -1
                POST_MLPS: [ 32, 32 ]

        x_conv3:
            DOWNSAMPLE_FACTOR: 4
            INPUT_CHANNELS: 64

            NAME: VectorPoolAggregationModuleMSG
            NUM_GROUPS: 2
            LOCAL_AGGREGATION_TYPE: local_interpolation
            NUM_REDUCED_CHANNELS: 32
            NUM_CHANNELS_OF_LOCAL_AGGREGATION: 32
            MSG_POST_MLPS: [128]
            FILTER_NEIGHBOR_WITH_ROI: True
            RADIUS_OF_NEIGHBOR_WITH_ROI: 4.0

            GROUP_CFG_0:
                NUM_LOCAL_VOXEL: [3, 3, 3]
                MAX_NEIGHBOR_DISTANCE: 1.2
                NEIGHBOR_NSAMPLE: -1
                POST_MLPS: [64, 64]
            GROUP_CFG_1:
                NUM_LOCAL_VOXEL: [ 3, 3, 3 ]
                MAX_NEIGHBOR_DISTANCE: 2.4
                NEIGHBOR_NSAMPLE: -1
                POST_MLPS: [ 64, 64 ]

        x_conv4:
            DOWNSAMPLE_FACTOR: 8
            INPUT_CHANNELS: 64

            NAME: VectorPoolAggregationModuleMSG
            NUM_GROUPS: 2
            LOCAL_AGGREGATION_TYPE: local_interpolation
            NUM_REDUCED_CHANNELS: 32
            NUM_CHANNELS_OF_LOCAL_AGGREGATION: 32
            MSG_POST_MLPS: [ 128 ]
            FILTER_NEIGHBOR_WITH_ROI: True
            RADIUS_OF_NEIGHBOR_WITH_ROI: 6.4

            GROUP_CFG_0:
                NUM_LOCAL_VOXEL: [ 3, 3, 3 ]
                MAX_NEIGHBOR_DISTANCE: 2.4
                NEIGHBOR_NSAMPLE: -1
                POST_MLPS: [ 64, 64 ]
            GROUP_CFG_1:
                NUM_LOCAL_VOXEL: [ 3, 3, 3 ]
                MAX_NEIGHBOR_DISTANCE: 4.8
                NEIGHBOR_NSAMPLE: -1
                POST_MLPS: [ 64, 64 ]

POINT_HEAD:
    NAME: PointHeadSimple
    CLS_FC: [256, 256]
    CLASS_AGNOSTIC: True
    USE_POINT_FEATURES_BEFORE_FUSION: True
    TARGET_CONFIG:
        GT_EXTRA_WIDTH: [0.2, 0.2, 0.2]
    LOSS_CONFIG:
        LOSS_REG: smooth-l1
        LOSS_WEIGHTS: {
            'point_cls_weight': 1.0,
        }

ROI_HEAD:
    NAME: PVRCNNHead
    CLASS_AGNOSTIC: True

    SHARED_FC: [256, 256]
    CLS_FC: [256, 256]
    REG_FC: [256, 256]
    DP_RATIO: 0.3

    NMS_CONFIG:
        TRAIN:
            NMS_TYPE: nms_gpu
            MULTI_CLASSES_NMS: False
            NMS_PRE_MAXSIZE: 9000
            NMS_POST_MAXSIZE: 512
            NMS_THRESH: 0.8
        TEST:
            NMS_TYPE: nms_gpu
            MULTI_CLASSES_NMS: False
            NMS_PRE_MAXSIZE: 1024
            NMS_POST_MAXSIZE: 100
            NMS_THRESH: 0.7
            SCORE_THRESH: 0.1

    ROI_GRID_POOL:
        GRID_SIZE: 6

        NAME: VectorPoolAggregationModuleMSG
        NUM_GROUPS: 2
        LOCAL_AGGREGATION_TYPE: voxel_random_choice
        NUM_REDUCED_CHANNELS: 30
        NUM_CHANNELS_OF_LOCAL_AGGREGATION: 32
        MSG_POST_MLPS: [ 128 ]

        GROUP_CFG_0:
            NUM_LOCAL_VOXEL: [ 3, 3, 3 ]
            MAX_NEIGHBOR_DISTANCE: 0.8
            NEIGHBOR_NSAMPLE: 32
            POST_MLPS: [ 64, 64 ]
        GROUP_CFG_1:
            NUM_LOCAL_VOXEL: [ 3, 3, 3 ]
            MAX_NEIGHBOR_DISTANCE: 1.6
            NEIGHBOR_NSAMPLE: 32
            POST_MLPS: [ 64, 64 ]

    TARGET_CONFIG:
        BOX_CODER: ResidualCoder
        ROI_PER_IMAGE: 128
        FG_RATIO: 0.5

        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': 1.0,
            '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

    EVAL_METRIC: kitti

    NMS_CONFIG:
        MULTI_CLASSES_NMS: False
        NMS_TYPE: nms_gpu
        NMS_THRESH: 0.1
        NMS_PRE_MAXSIZE: 4096
        NMS_POST_MAXSIZE: 500

OPTIMIZATION: OPTIMIZER: adam_onecycle LR: 0.01 WEIGHT_DECAY: 0.001 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
Rody1911641 commented 1 year ago

2022-11-01 03:23:22,191 INFO **Start logging** 2022-11-01 03:23:22,192 INFO CUDA_VISIBLE_DEVICES=ALL 2022-11-01 03:23:22,192 INFO cfg_file cfgs/kitti_models/DAfaster.yaml 2022-11-01 03:23:22,192 INFO batch_size 24 2022-11-01 03:23:22,192 INFO workers 4 2022-11-01 03:23:22,192 INFO extra_tag pvrcnn++_intensity_ROS 2022-11-01 03:23:22,192 INFO ckpt /opt/data/private/3D-Detection/OpenPCDet/output/nuscenes_models/DAfaster/pvrcnn++_intensity_ROS/ckpt/checkpoint_epoch_30.pth 2022-11-01 03:23:22,192 INFO pretrained_model None 2022-11-01 03:23:22,192 INFO launcher none 2022-11-01 03:23:22,193 INFO tcp_port 18888 2022-11-01 03:23:22,193 INFO local_rank 0 2022-11-01 03:23:22,193 INFO set_cfgs None 2022-11-01 03:23:22,193 INFO max_waiting_mins 30 2022-11-01 03:23:22,193 INFO start_epoch 0 2022-11-01 03:23:22,193 INFO eval_tag default 2022-11-01 03:23:22,193 INFO eval_all False 2022-11-01 03:23:22,193 INFO ckpt_dir None 2022-11-01 03:23:22,193 INFO save_to_file False 2022-11-01 03:23:22,193 INFO infer_time False 2022-11-01 03:23:22,194 INFO cfg.ROOT_DIR: /opt/data/private/3D-Detection/OpenPCDet 2022-11-01 03:23:22,194 INFO cfg.LOCAL_RANK: 0 2022-11-01 03:23:22,194 INFO cfg.CLASS_NAMES: ['Car'] 2022-11-01 03:23:22,194 INFO
cfg.DATA_CONFIG = edict() 2022-11-01 03:23:22,194 INFO cfg.DATA_CONFIG.DATASET: KittiDataset 2022-11-01 03:23:22,194 INFO cfg.DATA_CONFIG.DATA_PATH: ../data/kitti 2022-11-01 03:23:22,194 INFO cfg.DATA_CONFIG.POINT_CLOUD_RANGE: [-75.2, -75.2, -2, 75.2, 75.2, 4] 2022-11-01 03:23:22,194 INFO
cfg.DATA_CONFIG.DATA_SPLIT = edict() 2022-11-01 03:23:22,194 INFO cfg.DATA_CONFIG.DATA_SPLIT.train: train 2022-11-01 03:23:22,194 INFO cfg.DATA_CONFIG.DATA_SPLIT.test: val 2022-11-01 03:23:22,195 INFO
cfg.DATA_CONFIG.INFO_PATH = edict() 2022-11-01 03:23:22,195 INFO cfg.DATA_CONFIG.INFO_PATH.train: ['kitti_infos_train.pkl'] 2022-11-01 03:23:22,195 INFO cfg.DATA_CONFIG.INFO_PATH.test: ['kitti_infos_val.pkl'] 2022-11-01 03:23:22,195 INFO
cfg.DATA_CONFIG.DATA_AUGMENTOR = edict() 2022-11-01 03:23:22,195 INFO cfg.DATA_CONFIG.DATA_AUGMENTOR.DISABLE_AUG_LIST: ['random_object_scaling', 'random_object_rotation'] 2022-11-01 03:23:22,195 INFO cfg.DATA_CONFIG.DATA_AUGMENTOR.AUG_CONFIG_LIST: [{'NAME': 'random_object_scaling', 'SCALE_UNIFORM_NOISE': [0.9, 1.1]}, {'NAME': 'random_object_rotation', 'ROT_PROB': 1.0, 'ROT_UNIFORM_NOISE': [-0.78539816, 0.78539816]}, {'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]}] 2022-11-01 03:23:22,195 INFO
cfg.DATA_CONFIG.POINT_FEATURE_ENCODING = edict() 2022-11-01 03:23:22,195 INFO cfg.DATA_CONFIG.POINT_FEATURE_ENCODING.encoding_type: absolute_coordinates_encoding 2022-11-01 03:23:22,195 INFO cfg.DATA_CONFIG.POINT_FEATURE_ENCODING.used_feature_list: ['x', 'y', 'z', 'intensity'] 2022-11-01 03:23:22,195 INFO cfg.DATA_CONFIG.POINT_FEATURE_ENCODING.src_feature_list: ['x', 'y', 'z', 'intensity'] 2022-11-01 03:23:22,196 INFO cfg.DATA_CONFIG.DATA_PROCESSOR: [{'NAME': 'mask_points_and_boxes_outside_range', 'REMOVE_OUTSIDE_BOXES': True}, {'NAME': 'shuffle_points', 'SHUFFLE_ENABLED': {'train': True, 'test': False}}, {'NAME': 'transform_points_to_voxels', 'VOXEL_SIZE': [0.1, 0.1, 0.15], 'MAX_POINTS_PER_VOXEL': 5, 'MAX_NUMBER_OF_VOXELS': {'train': 80000, 'test': 90000}}] 2022-11-01 03:23:22,196 INFO
cfg.DATA_CONFIG.TEST = edict() 2022-11-01 03:23:22,196 INFO
cfg.DATA_CONFIG.TEST.BOX_FILTER = edict() 2022-11-01 03:23:22,196 INFO cfg.DATA_CONFIG.TEST.BOX_FILTER.USE_IMAGE_AREA_FILTER: True 2022-11-01 03:23:22,196 INFO cfg.DATA_CONFIG.TEST.BOX_FILTER.FOV_FILTER: True 2022-11-01 03:23:22,196 INFO cfg.DATA_CONFIG.TEST.BOX_FILTER.LIMIT_RANGE: [-75.2, -75.2, -2, 75.2, 75.2, 4] 2022-11-01 03:23:22,196 INFO cfg.DATA_CONFIG._BASECONFIG: cfgs/dataset_configs/kitti_car_DA.yaml 2022-11-01 03:23:22,196 INFO cfg.DATA_CONFIG.CLASS_NAMES: ['Car'] 2022-11-01 03:23:22,196 INFO cfg.DATA_CONFIG.FOV_POINTS_ONLY: True 2022-11-01 03:23:22,196 INFO cfg.DATA_CONFIG.SHIFT_COOR: [0.0, 0.0, 1.8] 2022-11-01 03:23:22,196 INFO cfg.DATA_CONFIG.MAX_SWEEPS: 1 2022-11-01 03:23:22,196 INFO cfg.DATA_CONFIG.PRED_VELOCITY: False 2022-11-01 03:23:22,197 INFO cfg.DATA_CONFIG.BALANCED_RESAMPLING: False 2022-11-01 03:23:22,197 INFO
cfg.MODEL = edict() 2022-11-01 03:23:22,197 INFO cfg.MODEL.NAME: PVRCNNPlusPlus 2022-11-01 03:23:22,197 INFO
cfg.MODEL.VFE = edict() 2022-11-01 03:23:22,197 INFO cfg.MODEL.VFE.NAME: MeanVFE 2022-11-01 03:23:22,197 INFO
cfg.MODEL.BACKBONE_3D = edict() 2022-11-01 03:23:22,197 INFO cfg.MODEL.BACKBONE_3D.NAME: VoxelBackBone8x 2022-11-01 03:23:22,197 INFO
cfg.MODEL.MAP_TO_BEV = edict() 2022-11-01 03:23:22,197 INFO cfg.MODEL.MAP_TO_BEV.NAME: HeightCompression 2022-11-01 03:23:22,197 INFO cfg.MODEL.MAP_TO_BEV.NUM_BEV_FEATURES: 256 2022-11-01 03:23:22,198 INFO
cfg.MODEL.BACKBONE_2D = edict() 2022-11-01 03:23:22,198 INFO cfg.MODEL.BACKBONE_2D.NAME: BaseBEVBackbone 2022-11-01 03:23:22,198 INFO cfg.MODEL.BACKBONE_2D.LAYER_NUMS: [5, 5] 2022-11-01 03:23:22,198 INFO cfg.MODEL.BACKBONE_2D.LAYER_STRIDES: [1, 2] 2022-11-01 03:23:22,198 INFO cfg.MODEL.BACKBONE_2D.NUM_FILTERS: [128, 256] 2022-11-01 03:23:22,198 INFO cfg.MODEL.BACKBONE_2D.UPSAMPLE_STRIDES: [1, 2] 2022-11-01 03:23:22,198 INFO cfg.MODEL.BACKBONE_2D.NUM_UPSAMPLE_FILTERS: [256, 256] 2022-11-01 03:23:22,198 INFO
cfg.MODEL.DENSE_HEAD = edict() 2022-11-01 03:23:22,198 INFO cfg.MODEL.DENSE_HEAD.NAME: AnchorHeadSingle 2022-11-01 03:23:22,198 INFO cfg.MODEL.DENSE_HEAD.CLASS_AGNOSTIC: False 2022-11-01 03:23:22,198 INFO cfg.MODEL.DENSE_HEAD.USE_DIRECTION_CLASSIFIER: True 2022-11-01 03:23:22,199 INFO cfg.MODEL.DENSE_HEAD.DIR_OFFSET: 0.78539 2022-11-01 03:23:22,199 INFO cfg.MODEL.DENSE_HEAD.DIR_LIMIT_OFFSET: 0.0 2022-11-01 03:23:22,199 INFO cfg.MODEL.DENSE_HEAD.NUM_DIR_BINS: 2 2022-11-01 03:23:22,199 INFO cfg.MODEL.DENSE_HEAD.ANCHOR_GENERATOR_CONFIG: [{'class_name': 'car', 'anchor_sizes': [[4.7, 2.1, 1.7]], 'anchor_rotations': [0, 1.57], 'anchor_bottom_heights': [0], 'align_center': False, 'feature_map_stride': 8, 'matched_threshold': 0.55, 'unmatched_threshold': 0.4}] 2022-11-01 03:23:22,199 INFO
cfg.MODEL.DENSE_HEAD.TARGET_ASSIGNER_CONFIG = edict() 2022-11-01 03:23:22,199 INFO cfg.MODEL.DENSE_HEAD.TARGET_ASSIGNER_CONFIG.NAME: AxisAlignedTargetAssigner 2022-11-01 03:23:22,199 INFO cfg.MODEL.DENSE_HEAD.TARGET_ASSIGNER_CONFIG.POS_FRACTION: -1.0 2022-11-01 03:23:22,199 INFO cfg.MODEL.DENSE_HEAD.TARGET_ASSIGNER_CONFIG.SAMPLE_SIZE: 512 2022-11-01 03:23:22,199 INFO cfg.MODEL.DENSE_HEAD.TARGET_ASSIGNER_CONFIG.NORM_BY_NUM_EXAMPLES: False 2022-11-01 03:23:22,199 INFO cfg.MODEL.DENSE_HEAD.TARGET_ASSIGNER_CONFIG.MATCH_HEIGHT: False 2022-11-01 03:23:22,200 INFO cfg.MODEL.DENSE_HEAD.TARGET_ASSIGNER_CONFIG.BOX_CODER: ResidualCoder 2022-11-01 03:23:22,200 INFO
cfg.MODEL.DENSE_HEAD.LOSS_CONFIG = edict() 2022-11-01 03:23:22,200 INFO
cfg.MODEL.DENSE_HEAD.LOSS_CONFIG.LOSS_WEIGHTS = edict() 2022-11-01 03:23:22,200 INFO cfg.MODEL.DENSE_HEAD.LOSS_CONFIG.LOSS_WEIGHTS.cls_weight: 1.0 2022-11-01 03:23:22,200 INFO cfg.MODEL.DENSE_HEAD.LOSS_CONFIG.LOSS_WEIGHTS.loc_weight: 2.0 2022-11-01 03:23:22,200 INFO cfg.MODEL.DENSE_HEAD.LOSS_CONFIG.LOSS_WEIGHTS.dir_weight: 0.2 2022-11-01 03:23:22,200 INFO cfg.MODEL.DENSE_HEAD.LOSS_CONFIG.LOSS_WEIGHTS.code_weights: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0] 2022-11-01 03:23:22,200 INFO
cfg.MODEL.PFE = edict() 2022-11-01 03:23:22,200 INFO cfg.MODEL.PFE.NAME: VoxelSetAbstraction 2022-11-01 03:23:22,200 INFO cfg.MODEL.PFE.POINT_SOURCE: raw_points 2022-11-01 03:23:22,201 INFO cfg.MODEL.PFE.NUM_KEYPOINTS: 2048 2022-11-01 03:23:22,201 INFO cfg.MODEL.PFE.NUM_OUTPUT_FEATURES: 90 2022-11-01 03:23:22,201 INFO cfg.MODEL.PFE.SAMPLE_METHOD: SPC 2022-11-01 03:23:22,201 INFO
cfg.MODEL.PFE.SPC_SAMPLING = edict() 2022-11-01 03:23:22,201 INFO cfg.MODEL.PFE.SPC_SAMPLING.NUM_SECTORS: 6 2022-11-01 03:23:22,201 INFO cfg.MODEL.PFE.SPC_SAMPLING.SAMPLE_RADIUS_WITH_ROI: 1.6 2022-11-01 03:23:22,201 INFO cfg.MODEL.PFE.FEATURES_SOURCE: ['bev', 'x_conv3', 'x_conv4', 'raw_points'] 2022-11-01 03:23:22,201 INFO
cfg.MODEL.PFE.SA_LAYER = edict() 2022-11-01 03:23:22,201 INFO
cfg.MODEL.PFE.SA_LAYER.raw_points = edict() 2022-11-01 03:23:22,201 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.NAME: VectorPoolAggregationModuleMSG 2022-11-01 03:23:22,202 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.NUM_GROUPS: 2 2022-11-01 03:23:22,202 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.LOCAL_AGGREGATION_TYPE: local_interpolation 2022-11-01 03:23:22,202 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.NUM_REDUCED_CHANNELS: 1 2022-11-01 03:23:22,202 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.NUM_CHANNELS_OF_LOCAL_AGGREGATION: 32 2022-11-01 03:23:22,202 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.MSG_POST_MLPS: [32] 2022-11-01 03:23:22,202 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.FILTER_NEIGHBOR_WITH_ROI: True 2022-11-01 03:23:22,202 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.RADIUS_OF_NEIGHBOR_WITH_ROI: 2.4 2022-11-01 03:23:22,202 INFO
cfg.MODEL.PFE.SA_LAYER.raw_points.GROUP_CFG_0 = edict() 2022-11-01 03:23:22,202 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.GROUP_CFG_0.NUM_LOCAL_VOXEL: [2, 2, 2] 2022-11-01 03:23:22,202 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.GROUP_CFG_0.MAX_NEIGHBOR_DISTANCE: 0.2 2022-11-01 03:23:22,202 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.GROUP_CFG_0.NEIGHBOR_NSAMPLE: -1 2022-11-01 03:23:22,203 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.GROUP_CFG_0.POST_MLPS: [32, 32] 2022-11-01 03:23:22,203 INFO
cfg.MODEL.PFE.SA_LAYER.raw_points.GROUP_CFG_1 = edict() 2022-11-01 03:23:22,203 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.GROUP_CFG_1.NUM_LOCAL_VOXEL: [3, 3, 3] 2022-11-01 03:23:22,203 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.GROUP_CFG_1.MAX_NEIGHBOR_DISTANCE: 0.4 2022-11-01 03:23:22,203 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.GROUP_CFG_1.NEIGHBOR_NSAMPLE: -1 2022-11-01 03:23:22,203 INFO cfg.MODEL.PFE.SA_LAYER.raw_points.GROUP_CFG_1.POST_MLPS: [32, 32] 2022-11-01 03:23:22,203 INFO
cfg.MODEL.PFE.SA_LAYER.x_conv3 = edict() 2022-11-01 03:23:22,203 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.DOWNSAMPLE_FACTOR: 4 2022-11-01 03:23:22,203 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.INPUT_CHANNELS: 64 2022-11-01 03:23:22,203 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.NAME: VectorPoolAggregationModuleMSG 2022-11-01 03:23:22,204 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.NUM_GROUPS: 2 2022-11-01 03:23:22,204 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.LOCAL_AGGREGATION_TYPE: local_interpolation 2022-11-01 03:23:22,204 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.NUM_REDUCED_CHANNELS: 32 2022-11-01 03:23:22,204 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.NUM_CHANNELS_OF_LOCAL_AGGREGATION: 32 2022-11-01 03:23:22,204 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.MSG_POST_MLPS: [128] 2022-11-01 03:23:22,204 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.FILTER_NEIGHBOR_WITH_ROI: True 2022-11-01 03:23:22,204 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.RADIUS_OF_NEIGHBOR_WITH_ROI: 4.0 2022-11-01 03:23:22,204 INFO
cfg.MODEL.PFE.SA_LAYER.x_conv3.GROUP_CFG_0 = edict() 2022-11-01 03:23:22,204 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.GROUP_CFG_0.NUM_LOCAL_VOXEL: [3, 3, 3] 2022-11-01 03:23:22,204 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.GROUP_CFG_0.MAX_NEIGHBOR_DISTANCE: 1.2 2022-11-01 03:23:22,204 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.GROUP_CFG_0.NEIGHBOR_NSAMPLE: -1 2022-11-01 03:23:22,205 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.GROUP_CFG_0.POST_MLPS: [64, 64] 2022-11-01 03:23:22,205 INFO
cfg.MODEL.PFE.SA_LAYER.x_conv3.GROUP_CFG_1 = edict() 2022-11-01 03:23:22,205 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.GROUP_CFG_1.NUM_LOCAL_VOXEL: [3, 3, 3] 2022-11-01 03:23:22,205 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.GROUP_CFG_1.MAX_NEIGHBOR_DISTANCE: 2.4 2022-11-01 03:23:22,205 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.GROUP_CFG_1.NEIGHBOR_NSAMPLE: -1 2022-11-01 03:23:22,205 INFO cfg.MODEL.PFE.SA_LAYER.x_conv3.GROUP_CFG_1.POST_MLPS: [64, 64] 2022-11-01 03:23:22,205 INFO
cfg.MODEL.PFE.SA_LAYER.x_conv4 = edict() 2022-11-01 03:23:22,205 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.DOWNSAMPLE_FACTOR: 8 2022-11-01 03:23:22,205 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.INPUT_CHANNELS: 64 2022-11-01 03:23:22,205 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.NAME: VectorPoolAggregationModuleMSG 2022-11-01 03:23:22,206 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.NUM_GROUPS: 2 2022-11-01 03:23:22,206 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.LOCAL_AGGREGATION_TYPE: local_interpolation 2022-11-01 03:23:22,206 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.NUM_REDUCED_CHANNELS: 32 2022-11-01 03:23:22,206 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.NUM_CHANNELS_OF_LOCAL_AGGREGATION: 32 2022-11-01 03:23:22,206 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.MSG_POST_MLPS: [128] 2022-11-01 03:23:22,206 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.FILTER_NEIGHBOR_WITH_ROI: True 2022-11-01 03:23:22,206 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.RADIUS_OF_NEIGHBOR_WITH_ROI: 6.4 2022-11-01 03:23:22,206 INFO
cfg.MODEL.PFE.SA_LAYER.x_conv4.GROUP_CFG_0 = edict() 2022-11-01 03:23:22,206 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.GROUP_CFG_0.NUM_LOCAL_VOXEL: [3, 3, 3] 2022-11-01 03:23:22,206 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.GROUP_CFG_0.MAX_NEIGHBOR_DISTANCE: 2.4 2022-11-01 03:23:22,206 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.GROUP_CFG_0.NEIGHBOR_NSAMPLE: -1 2022-11-01 03:23:22,207 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.GROUP_CFG_0.POST_MLPS: [64, 64] 2022-11-01 03:23:22,207 INFO
cfg.MODEL.PFE.SA_LAYER.x_conv4.GROUP_CFG_1 = edict() 2022-11-01 03:23:22,207 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.GROUP_CFG_1.NUM_LOCAL_VOXEL: [3, 3, 3] 2022-11-01 03:23:22,207 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.GROUP_CFG_1.MAX_NEIGHBOR_DISTANCE: 4.8 2022-11-01 03:23:22,207 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.GROUP_CFG_1.NEIGHBOR_NSAMPLE: -1 2022-11-01 03:23:22,207 INFO cfg.MODEL.PFE.SA_LAYER.x_conv4.GROUP_CFG_1.POST_MLPS: [64, 64] 2022-11-01 03:23:22,207 INFO
cfg.MODEL.POINT_HEAD = edict() 2022-11-01 03:23:22,207 INFO cfg.MODEL.POINT_HEAD.NAME: PointHeadSimple 2022-11-01 03:23:22,207 INFO cfg.MODEL.POINT_HEAD.CLS_FC: [256, 256] 2022-11-01 03:23:22,207 INFO cfg.MODEL.POINT_HEAD.CLASS_AGNOSTIC: True 2022-11-01 03:23:22,208 INFO cfg.MODEL.POINT_HEAD.USE_POINT_FEATURES_BEFORE_FUSION: True 2022-11-01 03:23:22,208 INFO
cfg.MODEL.POINT_HEAD.TARGET_CONFIG = edict() 2022-11-01 03:23:22,208 INFO cfg.MODEL.POINT_HEAD.TARGET_CONFIG.GT_EXTRA_WIDTH: [0.2, 0.2, 0.2] 2022-11-01 03:23:22,208 INFO
cfg.MODEL.POINT_HEAD.LOSS_CONFIG = edict() 2022-11-01 03:23:22,208 INFO cfg.MODEL.POINT_HEAD.LOSS_CONFIG.LOSS_REG: smooth-l1 2022-11-01 03:23:22,208 INFO
cfg.MODEL.POINT_HEAD.LOSS_CONFIG.LOSS_WEIGHTS = edict() 2022-11-01 03:23:22,208 INFO cfg.MODEL.POINT_HEAD.LOSS_CONFIG.LOSS_WEIGHTS.point_cls_weight: 1.0 2022-11-01 03:23:22,208 INFO
cfg.MODEL.ROI_HEAD = edict() 2022-11-01 03:23:22,208 INFO cfg.MODEL.ROI_HEAD.NAME: PVRCNNHead 2022-11-01 03:23:22,208 INFO cfg.MODEL.ROI_HEAD.CLASS_AGNOSTIC: True 2022-11-01 03:23:22,208 INFO cfg.MODEL.ROI_HEAD.SHARED_FC: [256, 256] 2022-11-01 03:23:22,209 INFO cfg.MODEL.ROI_HEAD.CLS_FC: [256, 256] 2022-11-01 03:23:22,209 INFO cfg.MODEL.ROI_HEAD.REG_FC: [256, 256] 2022-11-01 03:23:22,209 INFO cfg.MODEL.ROI_HEAD.DP_RATIO: 0.3 2022-11-01 03:23:22,209 INFO
cfg.MODEL.ROI_HEAD.NMS_CONFIG = edict() 2022-11-01 03:23:22,209 INFO
cfg.MODEL.ROI_HEAD.NMS_CONFIG.TRAIN = edict() 2022-11-01 03:23:22,209 INFO cfg.MODEL.ROI_HEAD.NMS_CONFIG.TRAIN.NMS_TYPE: nms_gpu 2022-11-01 03:23:22,209 INFO cfg.MODEL.ROI_HEAD.NMS_CONFIG.TRAIN.MULTI_CLASSES_NMS: False 2022-11-01 03:23:22,209 INFO cfg.MODEL.ROI_HEAD.NMS_CONFIG.TRAIN.NMS_PRE_MAXSIZE: 9000 2022-11-01 03:23:22,209 INFO cfg.MODEL.ROI_HEAD.NMS_CONFIG.TRAIN.NMS_POST_MAXSIZE: 512 2022-11-01 03:23:22,209 INFO cfg.MODEL.ROI_HEAD.NMS_CONFIG.TRAIN.NMS_THRESH: 0.8 2022-11-01 03:23:22,210 INFO
cfg.MODEL.ROI_HEAD.NMS_CONFIG.TEST = edict() 2022-11-01 03:23:22,210 INFO cfg.MODEL.ROI_HEAD.NMS_CONFIG.TEST.NMS_TYPE: nms_gpu 2022-11-01 03:23:22,210 INFO cfg.MODEL.ROI_HEAD.NMS_CONFIG.TEST.MULTI_CLASSES_NMS: False 2022-11-01 03:23:22,210 INFO cfg.MODEL.ROI_HEAD.NMS_CONFIG.TEST.NMS_PRE_MAXSIZE: 1024 2022-11-01 03:23:22,210 INFO cfg.MODEL.ROI_HEAD.NMS_CONFIG.TEST.NMS_POST_MAXSIZE: 100 2022-11-01 03:23:22,210 INFO cfg.MODEL.ROI_HEAD.NMS_CONFIG.TEST.NMS_THRESH: 0.5 2022-11-01 03:23:22,210 INFO cfg.MODEL.ROI_HEAD.NMS_CONFIG.TEST.SCORE_THRESH: 0.1 2022-11-01 03:23:22,210 INFO
cfg.MODEL.ROI_HEAD.ROI_GRID_POOL = edict() 2022-11-01 03:23:22,210 INFO cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.GRID_SIZE: 6 2022-11-01 03:23:22,210 INFO cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.NAME: VectorPoolAggregationModuleMSG 2022-11-01 03:23:22,211 INFO cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.NUM_GROUPS: 2 2022-11-01 03:23:22,211 INFO cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.LOCAL_AGGREGATION_TYPE: voxel_random_choice 2022-11-01 03:23:22,211 INFO cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.NUM_REDUCED_CHANNELS: 30 2022-11-01 03:23:22,211 INFO cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.NUM_CHANNELS_OF_LOCAL_AGGREGATION: 32 2022-11-01 03:23:22,211 INFO cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.MSG_POST_MLPS: [128] 2022-11-01 03:23:22,211 INFO
cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.GROUP_CFG_0 = edict() 2022-11-01 03:23:22,211 INFO cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.GROUP_CFG_0.NUM_LOCAL_VOXEL: [3, 3, 3] 2022-11-01 03:23:22,211 INFO cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.GROUP_CFG_0.MAX_NEIGHBOR_DISTANCE: 0.8 2022-11-01 03:23:22,211 INFO cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.GROUP_CFG_0.NEIGHBOR_NSAMPLE: 32 2022-11-01 03:23:22,211 INFO cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.GROUP_CFG_0.POST_MLPS: [64, 64] 2022-11-01 03:23:22,211 INFO
cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.GROUP_CFG_1 = edict() 2022-11-01 03:23:22,212 INFO cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.GROUP_CFG_1.NUM_LOCAL_VOXEL: [3, 3, 3] 2022-11-01 03:23:22,212 INFO cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.GROUP_CFG_1.MAX_NEIGHBOR_DISTANCE: 1.6 2022-11-01 03:23:22,212 INFO cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.GROUP_CFG_1.NEIGHBOR_NSAMPLE: 32 2022-11-01 03:23:22,212 INFO cfg.MODEL.ROI_HEAD.ROI_GRID_POOL.GROUP_CFG_1.POST_MLPS: [64, 64] 2022-11-01 03:23:22,212 INFO
cfg.MODEL.ROI_HEAD.TARGET_CONFIG = edict() 2022-11-01 03:23:22,212 INFO cfg.MODEL.ROI_HEAD.TARGET_CONFIG.BOX_CODER: ResidualCoder 2022-11-01 03:23:22,212 INFO cfg.MODEL.ROI_HEAD.TARGET_CONFIG.ROI_PER_IMAGE: 128 2022-11-01 03:23:22,212 INFO cfg.MODEL.ROI_HEAD.TARGET_CONFIG.FG_RATIO: 0.5 2022-11-01 03:23:22,212 INFO cfg.MODEL.ROI_HEAD.TARGET_CONFIG.SAMPLE_ROI_BY_EACH_CLASS: True 2022-11-01 03:23:22,212 INFO cfg.MODEL.ROI_HEAD.TARGET_CONFIG.CLS_SCORE_TYPE: roi_iou 2022-11-01 03:23:22,213 INFO cfg.MODEL.ROI_HEAD.TARGET_CONFIG.CLS_FG_THRESH: 0.75 2022-11-01 03:23:22,213 INFO cfg.MODEL.ROI_HEAD.TARGET_CONFIG.CLS_BG_THRESH: 0.25 2022-11-01 03:23:22,213 INFO cfg.MODEL.ROI_HEAD.TARGET_CONFIG.CLS_BG_THRESH_LO: 0.1 2022-11-01 03:23:22,213 INFO cfg.MODEL.ROI_HEAD.TARGET_CONFIG.HARD_BG_RATIO: 0.8 2022-11-01 03:23:22,213 INFO cfg.MODEL.ROI_HEAD.TARGET_CONFIG.REG_FG_THRESH: 0.55 2022-11-01 03:23:22,213 INFO
cfg.MODEL.ROI_HEAD.LOSS_CONFIG = edict() 2022-11-01 03:23:22,213 INFO cfg.MODEL.ROI_HEAD.LOSS_CONFIG.CLS_LOSS: BinaryCrossEntropy 2022-11-01 03:23:22,213 INFO cfg.MODEL.ROI_HEAD.LOSS_CONFIG.REG_LOSS: smooth-l1 2022-11-01 03:23:22,213 INFO cfg.MODEL.ROI_HEAD.LOSS_CONFIG.CORNER_LOSS_REGULARIZATION: True 2022-11-01 03:23:22,213 INFO
cfg.MODEL.ROI_HEAD.LOSS_CONFIG.LOSS_WEIGHTS = edict() 2022-11-01 03:23:22,213 INFO cfg.MODEL.ROI_HEAD.LOSS_CONFIG.LOSS_WEIGHTS.rcnn_cls_weight: 1.0 2022-11-01 03:23:22,214 INFO cfg.MODEL.ROI_HEAD.LOSS_CONFIG.LOSS_WEIGHTS.rcnn_reg_weight: 1.0 2022-11-01 03:23:22,214 INFO cfg.MODEL.ROI_HEAD.LOSS_CONFIG.LOSS_WEIGHTS.rcnn_corner_weight: 1.0 2022-11-01 03:23:22,214 INFO cfg.MODEL.ROI_HEAD.LOSS_CONFIG.LOSS_WEIGHTS.code_weights: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0] 2022-11-01 03:23:22,214 INFO
cfg.MODEL.POST_PROCESSING = edict() 2022-11-01 03:23:22,214 INFO cfg.MODEL.POST_PROCESSING.RECALL_THRESH_LIST: [0.3, 0.5, 0.7] 2022-11-01 03:23:22,214 INFO cfg.MODEL.POST_PROCESSING.SCORE_THRESH: 0.1 2022-11-01 03:23:22,214 INFO cfg.MODEL.POST_PROCESSING.OUTPUT_RAW_SCORE: False 2022-11-01 03:23:22,214 INFO cfg.MODEL.POST_PROCESSING.EVAL_METRIC: kitti 2022-11-01 03:23:22,214 INFO
cfg.MODEL.POST_PROCESSING.NMS_CONFIG = edict() 2022-11-01 03:23:22,214 INFO cfg.MODEL.POST_PROCESSING.NMS_CONFIG.MULTI_CLASSES_NMS: False 2022-11-01 03:23:22,215 INFO cfg.MODEL.POST_PROCESSING.NMS_CONFIG.NMS_TYPE: nms_gpu 2022-11-01 03:23:22,215 INFO cfg.MODEL.POST_PROCESSING.NMS_CONFIG.NMS_THRESH: 0.1 2022-11-01 03:23:22,215 INFO cfg.MODEL.POST_PROCESSING.NMS_CONFIG.NMS_PRE_MAXSIZE: 4096 2022-11-01 03:23:22,215 INFO cfg.MODEL.POST_PROCESSING.NMS_CONFIG.NMS_POST_MAXSIZE: 500 2022-11-01 03:23:22,215 INFO
cfg.OPTIMIZATION = edict() 2022-11-01 03:23:22,215 INFO cfg.OPTIMIZATION.OPTIMIZER: adam_onecycle 2022-11-01 03:23:22,215 INFO cfg.OPTIMIZATION.LR: 0.01 2022-11-01 03:23:22,215 INFO cfg.OPTIMIZATION.WEIGHT_DECAY: 0.001 2022-11-01 03:23:22,215 INFO cfg.OPTIMIZATION.MOMENTUM: 0.9 2022-11-01 03:23:22,215 INFO cfg.OPTIMIZATION.MOMS: [0.95, 0.85] 2022-11-01 03:23:22,216 INFO cfg.OPTIMIZATION.PCT_START: 0.4 2022-11-01 03:23:22,216 INFO cfg.OPTIMIZATION.DIV_FACTOR: 10 2022-11-01 03:23:22,216 INFO cfg.OPTIMIZATION.DECAY_STEP_LIST: [35, 45] 2022-11-01 03:23:22,216 INFO cfg.OPTIMIZATION.LR_DECAY: 0.1 2022-11-01 03:23:22,216 INFO cfg.OPTIMIZATION.LR_CLIP: 1e-07 2022-11-01 03:23:22,216 INFO cfg.OPTIMIZATION.LR_WARMUP: False 2022-11-01 03:23:22,216 INFO cfg.OPTIMIZATION.WARMUP_EPOCH: 1 2022-11-01 03:23:22,216 INFO cfg.OPTIMIZATION.GRAD_NORM_CLIP: 10 2022-11-01 03:23:22,216 INFO cfg.TAG: DAfaster 2022-11-01 03:23:22,216 INFO cfg.EXP_GROUP_PATH: kitti_models 2022-11-01 03:23:22,225 INFO Loading KITTI dataset 2022-11-01 03:23:22,451 INFO Total samples for KITTI dataset: 3769 2022-11-01 03:23:26,723 INFO ==> Loading parameters from checkpoint /opt/data/private/3D-Detection/OpenPCDet/output/nuscenes_models/DAfaster/pvrcnn++_intensity_ROS/ckpt/checkpoint_epoch_30.pth to GPU 2022-11-01 03:23:26,841 INFO ==> Checkpoint trained from version: pcdet+0.6.0+f221374 2022-11-01 03:23:26,883 INFO ==> Done (loaded 391/391) 2022-11-01 03:23:26,902 INFO * EPOCH 30 EVALUATION *** eval: 0%| | 0/158 [00:00<?, ?it/s]../pcdet/models/roi_heads/pvrcnn_head.py:161: UserWarning: This overload of nonzero is deprecated: nonzero() Consider using one of the following signatures instead: nonzero(*, bool as_tuple) (Triggered internally at /pytorch/torch/csrc/utils/python_arg_parser.cpp:882.) dense_idx = faked_features.nonzero() # (N, 3) [x_idx, y_idx, z_idx] eval: 100%|###########################################################################################################| 158/158 [07:46<00:00, 2.95s/it, recall_0.3=(13781, 13810) / 14385] 2022-11-01 03:31:13,162 INFO * Performance of EPOCH 30 *** 2022-11-01 03:31:13,202 INFO Generate label finished(sec_per_example: 0.1237 second). 2022-11-01 03:31:13,203 INFO recall_roi_0.3: 0.958012 2022-11-01 03:31:13,203 INFO recall_rcnn_0.3: 0.960028 2022-11-01 03:31:13,203 INFO recall_roi_0.5: 0.806952 2022-11-01 03:31:13,203 INFO recall_rcnn_0.5: 0.869308 2022-11-01 03:31:13,203 INFO recall_roi_0.7: 0.214946 2022-11-01 03:31:13,203 INFO recall_rcnn_0.7: 0.353285 2022-11-01 03:31:13,210 INFO Average predicted number of objects(3769 samples): 10.273 /usr/local/lib/python3.6/dist-packages/numba/core/typed_passes.py:327: NumbaPerformanceWarning: The keyword argument 'parallel=True' was specified but no transformation for parallel execution was possible.

To find out why, try turning on parallel diagnostics, see https://numba.pydata.org/numba-doc/latest/user/parallel.html#diagnostics for help.

File "../pcdet/datasets/kitti/kitti_object_eval_python/eval.py", line 122: @numba.jit(nopython=True, parallel=True) def d3_box_overlap_kernel(boxes, qboxes, rinc, criterion=-1): ^

state.func_ir.loc)) /usr/local/lib/python3.6/dist-packages/numba/core/typed_passes.py:327: NumbaPerformanceWarning: The keyword argument 'parallel=True' was specified but no transformation for parallel execution was possible.

To find out why, try turning on parallel diagnostics, see https://numba.pydata.org/numba-doc/latest/user/parallel.html#diagnostics for help.

File "../pcdet/datasets/kitti/kitti_object_eval_python/eval.py", line 122: @numba.jit(nopython=True, parallel=True) def d3_box_overlap_kernel(boxes, qboxes, rinc, criterion=-1): ^

state.func_ir.loc)) 2022-11-01 03:31:34,528 INFO Car AP@0.70, 0.70, 0.70: bbox AP:0.0000, 0.0000, 0.0000 bev AP:77.9522, 65.4295, 64.4617 3d AP:0.0000, 0.0000, 0.0000 aos AP:0.00, 0.00, 0.00 Car AP_R40@0.70, 0.70, 0.70: bbox AP:0.0000, 0.0000, 0.0000 bev AP:79.5713, 66.7626, 64.5092 3d AP:0.0000, 0.0000, 0.0000 aos AP:0.00, 0.00, 0.00 Car AP@0.70, 0.50, 0.50: bbox AP:0.0000, 0.0000, 0.0000 bev AP:89.4668, 86.4132, 86.2657 3d AP:0.0000, 0.0000, 0.0000 aos AP:0.00, 0.00, 0.00 Car AP_R40@0.70, 0.50, 0.50: bbox AP:0.0000, 0.0000, 0.0000 bev AP:93.9974, 88.5902, 88.6612 3d AP:0.0000, 0.0000, 0.0000 aos AP:0.00, 0.00, 0.00

liyn69 commented 10 months ago

hello, can you teach me how to solve this problem

Rody-NKCS commented 10 months ago

你好，我已经不做这个方向了，凭借记忆，我记得是因为，我在训练时对点云z坐标加上了一定的偏移，而测试时忘记加上同样的偏移，所以bev视角下测试结果是对的，但3DAP就不对了。