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cagroup3d-win10-scannet

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cagroup3d-win10-scannet
File size: 14,496 Bytes 
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2023-04-01 00:37:35,936   INFO  **********************Start logging**********************
2023-04-01 00:37:35,936   INFO  CUDA_VISIBLE_DEVICES=ALL
2023-04-01 00:37:35,937   INFO  total_batch_size: 16
2023-04-01 00:37:35,937   INFO  cfg_file         cfgs/scannet_models/CAGroup3D.yaml
2023-04-01 00:37:35,940   INFO  batch_size       16
2023-04-01 00:37:35,941   INFO  workers          4
2023-04-01 00:37:35,941   INFO  extra_tag        cagroup3d-win10-scannet-eval
2023-04-01 00:37:35,942   INFO  ckpt             ../output/scannet_models/CAGroup3D/cagroup3d-win10-scannet-train/ckpt/checkpoint_epoch_1.pth
2023-04-01 00:37:35,944   INFO  launcher         pytorch
2023-04-01 00:37:35,945   INFO  tcp_port         18888
2023-04-01 00:37:35,945   INFO  set_cfgs         None
2023-04-01 00:37:35,946   INFO  max_waiting_mins 30
2023-04-01 00:37:35,947   INFO  start_epoch      0
2023-04-01 00:37:35,949   INFO  eval_tag         default
2023-04-01 00:37:35,949   INFO  eval_all         False
2023-04-01 00:37:35,950   INFO  ckpt_dir         None
2023-04-01 00:37:35,950   INFO  save_to_file     False
2023-04-01 00:37:35,951   INFO  cfg.ROOT_DIR: C:\PINKAMENA\CITYU\CS5182\proj\CAGroup3D
2023-04-01 00:37:35,952   INFO  cfg.LOCAL_RANK: 0
2023-04-01 00:37:35,952   INFO  cfg.CLASS_NAMES: ['cabinet', 'bed', 'chair', 'sofa', 'table', 'door', 'window', 'bookshelf', 'picture', 'counter', 'desk', 'curtain', 'refrigerator', 'showercurtrain', 'toilet', 'sink', 'bathtub', 'garbagebin']
2023-04-01 00:37:35,953   INFO  
cfg.DATA_CONFIG = edict()
2023-04-01 00:37:35,954   INFO  cfg.DATA_CONFIG.DATASET: ScannetDataset
2023-04-01 00:37:35,954   INFO  cfg.DATA_CONFIG.DATA_PATH: ../data/scannet_data/ScanNetV2
2023-04-01 00:37:35,954   INFO  cfg.DATA_CONFIG.PROCESSED_DATA_TAG: scannet_processed_data_v0_5_0
2023-04-01 00:37:35,956   INFO  cfg.DATA_CONFIG.POINT_CLOUD_RANGE: [-40, -40, -10, 40, 40, 10]
2023-04-01 00:37:35,956   INFO  
cfg.DATA_CONFIG.DATA_SPLIT = edict()
2023-04-01 00:37:35,957   INFO  cfg.DATA_CONFIG.DATA_SPLIT.train: train
2023-04-01 00:37:35,958   INFO  cfg.DATA_CONFIG.DATA_SPLIT.test: val
2023-04-01 00:37:35,958   INFO  
cfg.DATA_CONFIG.REPEAT = edict()
2023-04-01 00:37:35,959   INFO  cfg.DATA_CONFIG.REPEAT.train: 10
2023-04-01 00:37:35,959   INFO  cfg.DATA_CONFIG.REPEAT.test: 1
2023-04-01 00:37:35,961   INFO  
cfg.DATA_CONFIG.INFO_PATH = edict()
2023-04-01 00:37:35,961   INFO  cfg.DATA_CONFIG.INFO_PATH.train: ['scannet_infos_train.pkl']
2023-04-01 00:37:35,962   INFO  cfg.DATA_CONFIG.INFO_PATH.test: ['scannet_infos_val.pkl']
2023-04-01 00:37:35,963   INFO  cfg.DATA_CONFIG.GET_ITEM_LIST: ['points', 'instance_mask', 'semantic_mask']
2023-04-01 00:37:35,964   INFO  cfg.DATA_CONFIG.FILTER_EMPTY_BOXES_FOR_TRAIN: True
2023-04-01 00:37:35,965   INFO  
cfg.DATA_CONFIG.DATA_AUGMENTOR_TRAIN = edict()
2023-04-01 00:37:35,966   INFO  cfg.DATA_CONFIG.DATA_AUGMENTOR_TRAIN.DISABLE_AUG_LIST: ['placeholder']
2023-04-01 00:37:35,967   INFO  cfg.DATA_CONFIG.DATA_AUGMENTOR_TRAIN.AUG_CONFIG_LIST: [{'NAME': 'global_alignment', 'rotation_axis': 2}, {'NAME': 'point_seg_class_mapping', 'valid_cat_ids': [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16, 24, 28, 33, 34, 36, 39], 'max_cat_id': 40}, {'NAME': 'random_world_flip', 'ALONG_AXIS_LIST': ['x', 'y']}, {'NAME': 'random_world_rotation', 'WORLD_ROT_ANGLE': [-0.087266, 0.087266]}, {'NAME': 'random_world_scaling', 'WORLD_SCALE_RANGE': [0.9, 1.1]}, {'NAME': 'random_world_translation', 'ALONG_AXIS_LIST': ['x', 'y', 'z'], 'NOISE_TRANSLATE_STD': 0.1}]
2023-04-01 00:37:35,969   INFO  
cfg.DATA_CONFIG.DATA_AUGMENTOR_TEST = edict()
2023-04-01 00:37:35,970   INFO  cfg.DATA_CONFIG.DATA_AUGMENTOR_TEST.DISABLE_AUG_LIST: ['placeholder']
2023-04-01 00:37:35,970   INFO  cfg.DATA_CONFIG.DATA_AUGMENTOR_TEST.AUG_CONFIG_LIST: [{'NAME': 'global_alignment', 'rotation_axis': 2}]
2023-04-01 00:37:35,971   INFO  
cfg.DATA_CONFIG.DATA_AUGMENTOR = edict()
2023-04-01 00:37:35,971   INFO  cfg.DATA_CONFIG.DATA_AUGMENTOR.DISABLE_AUG_LIST: ['placeholder']
2023-04-01 00:37:35,972   INFO  cfg.DATA_CONFIG.DATA_AUGMENTOR.AUG_CONFIG_LIST: [{'NAME': 'global_alignment', 'rotation_axis': 2}]
2023-04-01 00:37:35,973   INFO  
cfg.DATA_CONFIG.POINT_FEATURE_ENCODING = edict()
2023-04-01 00:37:35,974   INFO  cfg.DATA_CONFIG.POINT_FEATURE_ENCODING.encoding_type: absolute_coordinates_encoding
2023-04-01 00:37:35,975   INFO  cfg.DATA_CONFIG.POINT_FEATURE_ENCODING.used_feature_list: ['x', 'y', 'z', 'r', 'g', 'b']
2023-04-01 00:37:35,976   INFO  cfg.DATA_CONFIG.POINT_FEATURE_ENCODING.src_feature_list: ['x', 'y', 'z', 'r', 'g', 'b']
2023-04-01 00:37:35,976   INFO  cfg.DATA_CONFIG.DATA_PROCESSOR: [{'NAME': 'mask_points_and_boxes_outside_range', 'REMOVE_OUTSIDE_BOXES': True}]
2023-04-01 00:37:35,977   INFO  cfg.DATA_CONFIG._BASE_CONFIG_: cfgs/dataset_configs/scannet_dataset.yaml
2023-04-01 00:37:35,977   INFO  cfg.VOXEL_SIZE: 0.02
2023-04-01 00:37:35,978   INFO  cfg.N_CLASSES: 18
2023-04-01 00:37:35,979   INFO  cfg.SEMANTIC_THR: 0.15
2023-04-01 00:37:35,980   INFO  
cfg.MODEL = edict()
2023-04-01 00:37:35,981   INFO  cfg.MODEL.NAME: CAGroup3D
2023-04-01 00:37:35,982   INFO  cfg.MODEL.VOXEL_SIZE: 0.02
2023-04-01 00:37:35,983   INFO  cfg.MODEL.SEMANTIC_MIN_THR: 0.05
2023-04-01 00:37:35,983   INFO  cfg.MODEL.SEMANTIC_ITER_VALUE: 0.02
2023-04-01 00:37:35,983   INFO  cfg.MODEL.SEMANTIC_THR: 0.15
2023-04-01 00:37:35,984   INFO  
cfg.MODEL.BACKBONE_3D = edict()
2023-04-01 00:37:35,985   INFO  cfg.MODEL.BACKBONE_3D.NAME: BiResNet
2023-04-01 00:37:35,986   INFO  cfg.MODEL.BACKBONE_3D.IN_CHANNELS: 3
2023-04-01 00:37:35,986   INFO  cfg.MODEL.BACKBONE_3D.OUT_CHANNELS: 64
2023-04-01 00:37:35,987   INFO  
cfg.MODEL.DENSE_HEAD = edict()
2023-04-01 00:37:35,987   INFO  cfg.MODEL.DENSE_HEAD.NAME: CAGroup3DHead
2023-04-01 00:37:35,987   INFO  cfg.MODEL.DENSE_HEAD.IN_CHANNELS: [64, 128, 256, 512]
2023-04-01 00:37:35,988   INFO  cfg.MODEL.DENSE_HEAD.OUT_CHANNELS: 64
2023-04-01 00:37:35,988   INFO  cfg.MODEL.DENSE_HEAD.SEMANTIC_THR: 0.15
2023-04-01 00:37:35,989   INFO  cfg.MODEL.DENSE_HEAD.VOXEL_SIZE: 0.02
2023-04-01 00:37:35,989   INFO  cfg.MODEL.DENSE_HEAD.N_CLASSES: 18
2023-04-01 00:37:35,989   INFO  cfg.MODEL.DENSE_HEAD.N_REG_OUTS: 6
2023-04-01 00:37:35,990   INFO  cfg.MODEL.DENSE_HEAD.CLS_KERNEL: 9
2023-04-01 00:37:35,990   INFO  cfg.MODEL.DENSE_HEAD.WITH_YAW: False
2023-04-01 00:37:35,991   INFO  cfg.MODEL.DENSE_HEAD.USE_SEM_SCORE: False
2023-04-01 00:37:35,991   INFO  cfg.MODEL.DENSE_HEAD.EXPAND_RATIO: 3
2023-04-01 00:37:35,991   INFO  
cfg.MODEL.DENSE_HEAD.ASSIGNER = edict()
2023-04-01 00:37:35,992   INFO  cfg.MODEL.DENSE_HEAD.ASSIGNER.NAME: CAGroup3DAssigner
2023-04-01 00:37:35,992   INFO  cfg.MODEL.DENSE_HEAD.ASSIGNER.LIMIT: 27
2023-04-01 00:37:35,993   INFO  cfg.MODEL.DENSE_HEAD.ASSIGNER.TOPK: 18
2023-04-01 00:37:35,993   INFO  cfg.MODEL.DENSE_HEAD.ASSIGNER.N_SCALES: 4
2023-04-01 00:37:35,994   INFO  
cfg.MODEL.DENSE_HEAD.LOSS_OFFSET = edict()
2023-04-01 00:37:35,994   INFO  cfg.MODEL.DENSE_HEAD.LOSS_OFFSET.NAME: SmoothL1Loss
2023-04-01 00:37:35,995   INFO  cfg.MODEL.DENSE_HEAD.LOSS_OFFSET.BETA: 0.04
2023-04-01 00:37:35,995   INFO  cfg.MODEL.DENSE_HEAD.LOSS_OFFSET.REDUCTION: sum
2023-04-01 00:37:35,995   INFO  cfg.MODEL.DENSE_HEAD.LOSS_OFFSET.LOSS_WEIGHT: 1.0
2023-04-01 00:37:35,996   INFO  
cfg.MODEL.DENSE_HEAD.LOSS_BBOX = edict()
2023-04-01 00:37:35,997   INFO  cfg.MODEL.DENSE_HEAD.LOSS_BBOX.NAME: IoU3DLoss
2023-04-01 00:37:35,997   INFO  cfg.MODEL.DENSE_HEAD.LOSS_BBOX.WITH_YAW: False
2023-04-01 00:37:35,997   INFO  cfg.MODEL.DENSE_HEAD.LOSS_BBOX.LOSS_WEIGHT: 1.0
2023-04-01 00:37:35,998   INFO  
cfg.MODEL.DENSE_HEAD.NMS_CONFIG = edict()
2023-04-01 00:37:35,998   INFO  cfg.MODEL.DENSE_HEAD.NMS_CONFIG.SCORE_THR: 0.01
2023-04-01 00:37:35,999   INFO  cfg.MODEL.DENSE_HEAD.NMS_CONFIG.NMS_PRE: 1000
2023-04-01 00:37:36,000   INFO  cfg.MODEL.DENSE_HEAD.NMS_CONFIG.IOU_THR: 0.5
2023-04-01 00:37:36,000   INFO  
cfg.MODEL.ROI_HEAD = edict()
2023-04-01 00:37:36,001   INFO  cfg.MODEL.ROI_HEAD.NAME: CAGroup3DRoIHead
2023-04-01 00:37:36,001   INFO  cfg.MODEL.ROI_HEAD.NUM_CLASSES: 18
2023-04-01 00:37:36,002   INFO  cfg.MODEL.ROI_HEAD.MIDDLE_FEATURE_SOURCE: [3]
2023-04-01 00:37:36,002   INFO  cfg.MODEL.ROI_HEAD.GRID_SIZE: 7
2023-04-01 00:37:36,003   INFO  cfg.MODEL.ROI_HEAD.VOXEL_SIZE: 0.02
2023-04-01 00:37:36,003   INFO  cfg.MODEL.ROI_HEAD.COORD_KEY: 2
2023-04-01 00:37:36,004   INFO  cfg.MODEL.ROI_HEAD.MLPS: [[64, 128, 128]]
2023-04-01 00:37:36,005   INFO  cfg.MODEL.ROI_HEAD.CODE_SIZE: 6
2023-04-01 00:37:36,005   INFO  cfg.MODEL.ROI_HEAD.ENCODE_SINCOS: False
2023-04-01 00:37:36,007   INFO  cfg.MODEL.ROI_HEAD.ROI_PER_IMAGE: 128
2023-04-01 00:37:36,008   INFO  cfg.MODEL.ROI_HEAD.ROI_FG_RATIO: 0.9
2023-04-01 00:37:36,009   INFO  cfg.MODEL.ROI_HEAD.REG_FG_THRESH: 0.3
2023-04-01 00:37:36,009   INFO  cfg.MODEL.ROI_HEAD.ROI_CONV_KERNEL: 5
2023-04-01 00:37:36,010   INFO  cfg.MODEL.ROI_HEAD.ENLARGE_RATIO: False
2023-04-01 00:37:36,010   INFO  cfg.MODEL.ROI_HEAD.USE_IOU_LOSS: False
2023-04-01 00:37:36,011   INFO  cfg.MODEL.ROI_HEAD.USE_GRID_OFFSET: False
2023-04-01 00:37:36,011   INFO  cfg.MODEL.ROI_HEAD.USE_SIMPLE_POOLING: True
2023-04-01 00:37:36,012   INFO  cfg.MODEL.ROI_HEAD.USE_CENTER_POOLING: True
2023-04-01 00:37:36,012   INFO  
cfg.MODEL.ROI_HEAD.LOSS_WEIGHTS = edict()
2023-04-01 00:37:36,013   INFO  cfg.MODEL.ROI_HEAD.LOSS_WEIGHTS.RCNN_CLS_WEIGHT: 1.0
2023-04-01 00:37:36,014   INFO  cfg.MODEL.ROI_HEAD.LOSS_WEIGHTS.RCNN_REG_WEIGHT: 1.0
2023-04-01 00:37:36,014   INFO  cfg.MODEL.ROI_HEAD.LOSS_WEIGHTS.RCNN_IOU_WEIGHT: 1.0
2023-04-01 00:37:36,015   INFO  cfg.MODEL.ROI_HEAD.LOSS_WEIGHTS.CODE_WEIGHT: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
2023-04-01 00:37:36,015   INFO  
cfg.MODEL.POST_PROCESSING = edict()
2023-04-01 00:37:36,016   INFO  cfg.MODEL.POST_PROCESSING.RECALL_THRESH_LIST: [0.25, 0.5]
2023-04-01 00:37:36,017   INFO  cfg.MODEL.POST_PROCESSING.EVAL_METRIC: scannet
2023-04-01 00:37:36,018   INFO  
cfg.OPTIMIZATION = edict()
2023-04-01 00:37:36,019   INFO  cfg.OPTIMIZATION.BATCH_SIZE_PER_GPU: 16
2023-04-01 00:37:36,019   INFO  cfg.OPTIMIZATION.NUM_EPOCHS: 1
2023-04-01 00:37:36,019   INFO  cfg.OPTIMIZATION.OPTIMIZER: adamW
2023-04-01 00:37:36,019   INFO  cfg.OPTIMIZATION.LR: 0.001
2023-04-01 00:37:36,020   INFO  cfg.OPTIMIZATION.WEIGHT_DECAY: 0.0001
2023-04-01 00:37:36,020   INFO  cfg.OPTIMIZATION.DECAY_STEP_LIST: [7, 9]
2023-04-01 00:37:36,020   INFO  cfg.OPTIMIZATION.LR_DECAY: 0.1
2023-04-01 00:37:36,021   INFO  cfg.OPTIMIZATION.GRAD_NORM_CLIP: 10
2023-04-01 00:37:36,021   INFO  cfg.OPTIMIZATION.PCT_START: 0.4
2023-04-01 00:37:36,022   INFO  cfg.OPTIMIZATION.DIV_FACTOR: 10
2023-04-01 00:37:36,023   INFO  cfg.OPTIMIZATION.LR_CLIP: 1e-07
2023-04-01 00:37:36,024   INFO  cfg.OPTIMIZATION.LR_WARMUP: False
2023-04-01 00:37:36,024   INFO  cfg.OPTIMIZATION.WARMUP_EPOCH: 1
2023-04-01 00:37:36,025   INFO  cfg.TAG: CAGroup3D
2023-04-01 00:37:36,025   INFO  cfg.EXP_GROUP_PATH: scannet_models
2023-04-01 00:37:36,026   INFO  Loading SCANNET dataset
2023-04-01 00:37:36,070   INFO  Total samples for SCANNET dataset: 312
2023-04-01 00:37:37,961   INFO  ==> Loading parameters from checkpoint ../output/scannet_models/CAGroup3D/cagroup3d-win10-scannet-train/ckpt/checkpoint_epoch_1.pth to CPU
2023-04-01 00:37:44,989   INFO  ==> Checkpoint trained from version: pcdet+0.5.2+4ae8a35+py6af8eab
2023-04-01 00:37:45,137   INFO  ==> Done (loaded 838/838)
2023-04-01 00:37:46,123   INFO  *************** EPOCH 1 EVALUATION *****************
2023-04-01 02:31:46,714   INFO  *************** Performance of EPOCH 1 *****************
2023-04-01 02:31:46,716   INFO  Generate label finished(sec_per_example: 21.9079 second).
2023-04-01 02:31:46,716   INFO  recall_roi_0.25: 0.000000
2023-04-01 02:31:46,717   INFO  recall_rcnn_0.25: 0.000000
2023-04-01 02:31:46,717   INFO  recall_roi_0.5: 0.000000
2023-04-01 02:31:46,718   INFO  recall_rcnn_0.5: 0.000000
2023-04-01 02:31:46,720   INFO  Average predicted number of objects(312 samples): 307.683
2023-04-01 02:32:02,586   INFO  {'cabinet_AP_0.25': 0.00020054943161085248, 'bed_AP_0.25': 0.42014947533607483, 'chair_AP_0.25': 0.0, 'sofa_AP_0.25': 0.01556780282407999, 'table_AP_0.25': 0.011284402571618557, 'door_AP_0.25': 4.396647636895068e-05, 'window_AP_0.25': 0.0009544664644636214, 'bookshelf_AP_0.25': 0.009515471756458282, 'picture_AP_0.25': 0.0, 'counter_AP_0.25': 0.0, 'desk_AP_0.25': 0.004060885403305292, 'curtain_AP_0.25': 0.003624277887865901, 'refrigerator_AP_0.25': 0.0, 'showercurtrain_AP_0.25': 0.005170575808733702, 'toilet_AP_0.25': 0.0, 'sink_AP_0.25': 0.0, 'bathtub_AP_0.25': 0.0, 'garbagebin_AP_0.25': 0.00020618356938939542, 'mAP_0.25': 0.02615433558821678, 'cabinet_rec_0.25': 0.01881720430107527, 'bed_rec_0.25': 0.6296296296296297, 'chair_rec_0.25': 0.0, 'sofa_rec_0.25': 0.18556701030927836, 'table_rec_0.25': 0.12, 'door_rec_0.25': 0.006423982869379015, 'window_rec_0.25': 0.014184397163120567, 'bookshelf_rec_0.25': 0.12987012987012986, 'picture_rec_0.25': 0.0, 'counter_rec_0.25': 0.0, 'desk_rec_0.25': 0.11811023622047244, 'curtain_rec_0.25': 0.08955223880597014, 'refrigerator_rec_0.25': 0.0, 'showercurtrain_rec_0.25': 0.10714285714285714, 'toilet_rec_0.25': 0.0, 'sink_rec_0.25': 0.0, 'bathtub_rec_0.25': 0.0, 'garbagebin_rec_0.25': 0.03018867924528302, 'mAR_0.25': 0.08052702030873309, 'cabinet_AP_0.50': 0.0, 'bed_AP_0.50': 0.019029777497053146, 'chair_AP_0.50': 0.0, 'sofa_AP_0.50': 0.0, 'table_AP_0.50': 0.0, 'door_AP_0.50': 0.0, 'window_AP_0.50': 0.0, 'bookshelf_AP_0.50': 0.0, 'picture_AP_0.50': 0.0, 'counter_AP_0.50': 0.0, 'desk_AP_0.50': 0.0, 'curtain_AP_0.50': 0.0, 'refrigerator_AP_0.50': 0.0, 'showercurtrain_AP_0.50': 0.0, 'toilet_AP_0.50': 0.0, 'sink_AP_0.50': 0.0, 'bathtub_AP_0.50': 0.0, 'garbagebin_AP_0.50': 0.0, 'mAP_0.50': 0.00105720991268754, 'cabinet_rec_0.50': 0.0, 'bed_rec_0.50': 0.13580246913580246, 'chair_rec_0.50': 0.0, 'sofa_rec_0.50': 0.0, 'table_rec_0.50': 0.0, 'door_rec_0.50': 0.0, 'window_rec_0.50': 0.0, 'bookshelf_rec_0.50': 0.0, 'picture_rec_0.50': 0.0, 'counter_rec_0.50': 0.0, 'desk_rec_0.50': 0.0, 'curtain_rec_0.50': 0.0, 'refrigerator_rec_0.50': 0.0, 'showercurtrain_rec_0.50': 0.0, 'toilet_rec_0.50': 0.0, 'sink_rec_0.50': 0.0, 'bathtub_rec_0.50': 0.0, 'garbagebin_rec_0.50': 0.0, 'mAR_0.50': 0.0075445816186556925}
2023-04-01 02:32:02,595   INFO  Result is save to C:\PINKAMENA\CITYU\CS5182\proj\CAGroup3D\output\scannet_models\CAGroup3D\cagroup3d-win10-scannet-eval\eval\epoch_1\val\default
2023-04-01 02:32:02,596   INFO  ****************Evaluation done.*****************