| 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.***************** | |