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cagroup3d-win10-scannet

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  1. eval/epoch_1/val/default/log_eval_20230401-003735.txt +172 -0
  2. eval/epoch_1/val/default/result.pkl +2 -2
eval/epoch_1/val/default/log_eval_20230401-003735.txt ADDED
@@ -0,0 +1,172 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ 2023-04-01 00:37:35,936 INFO **********************Start logging**********************
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+ 2023-04-01 00:37:35,936 INFO CUDA_VISIBLE_DEVICES=ALL
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+ 2023-04-01 00:37:35,937 INFO total_batch_size: 16
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+ 2023-04-01 00:37:35,937 INFO cfg_file cfgs/scannet_models/CAGroup3D.yaml
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+ 2023-04-01 00:37:35,940 INFO batch_size 16
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+ 2023-04-01 00:37:35,941 INFO workers 4
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+ 2023-04-01 00:37:35,941 INFO extra_tag cagroup3d-win10-scannet-eval
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+ 2023-04-01 00:37:35,942 INFO ckpt ../output/scannet_models/CAGroup3D/cagroup3d-win10-scannet-train/ckpt/checkpoint_epoch_1.pth
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+ 2023-04-01 00:37:35,944 INFO launcher pytorch
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+ 2023-04-01 00:37:35,945 INFO tcp_port 18888
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+ 2023-04-01 00:37:35,945 INFO set_cfgs None
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+ 2023-04-01 00:37:35,946 INFO max_waiting_mins 30
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+ 2023-04-01 00:37:35,947 INFO start_epoch 0
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+ 2023-04-01 00:37:35,949 INFO eval_tag default
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+ 2023-04-01 00:37:35,949 INFO eval_all False
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+ 2023-04-01 00:37:35,950 INFO ckpt_dir None
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+ 2023-04-01 00:37:35,950 INFO save_to_file False
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+ 2023-04-01 00:37:35,951 INFO cfg.ROOT_DIR: C:\PINKAMENA\CITYU\CS5182\proj\CAGroup3D
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+ 2023-04-01 00:37:35,952 INFO cfg.LOCAL_RANK: 0
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+ 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']
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+ 2023-04-01 00:37:35,953 INFO
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+ cfg.DATA_CONFIG = edict()
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+ 2023-04-01 00:37:35,954 INFO cfg.DATA_CONFIG.DATASET: ScannetDataset
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+ 2023-04-01 00:37:35,954 INFO cfg.DATA_CONFIG.DATA_PATH: ../data/scannet_data/ScanNetV2
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+ 2023-04-01 00:37:35,954 INFO cfg.DATA_CONFIG.PROCESSED_DATA_TAG: scannet_processed_data_v0_5_0
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+ 2023-04-01 00:37:35,956 INFO cfg.DATA_CONFIG.POINT_CLOUD_RANGE: [-40, -40, -10, 40, 40, 10]
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+ 2023-04-01 00:37:35,956 INFO
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+ cfg.DATA_CONFIG.DATA_SPLIT = edict()
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+ 2023-04-01 00:37:35,957 INFO cfg.DATA_CONFIG.DATA_SPLIT.train: train
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+ 2023-04-01 00:37:35,958 INFO cfg.DATA_CONFIG.DATA_SPLIT.test: val
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+ 2023-04-01 00:37:35,958 INFO
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+ cfg.DATA_CONFIG.REPEAT = edict()
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+ 2023-04-01 00:37:35,959 INFO cfg.DATA_CONFIG.REPEAT.train: 10
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+ 2023-04-01 00:37:35,959 INFO cfg.DATA_CONFIG.REPEAT.test: 1
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+ 2023-04-01 00:37:35,961 INFO
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+ cfg.DATA_CONFIG.INFO_PATH = edict()
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+ 2023-04-01 00:37:35,961 INFO cfg.DATA_CONFIG.INFO_PATH.train: ['scannet_infos_train.pkl']
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+ 2023-04-01 00:37:35,962 INFO cfg.DATA_CONFIG.INFO_PATH.test: ['scannet_infos_val.pkl']
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+ 2023-04-01 00:37:35,963 INFO cfg.DATA_CONFIG.GET_ITEM_LIST: ['points', 'instance_mask', 'semantic_mask']
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+ 2023-04-01 00:37:35,964 INFO cfg.DATA_CONFIG.FILTER_EMPTY_BOXES_FOR_TRAIN: True
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+ 2023-04-01 00:37:35,965 INFO
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+ cfg.DATA_CONFIG.DATA_AUGMENTOR_TRAIN = edict()
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+ 2023-04-01 00:37:35,966 INFO cfg.DATA_CONFIG.DATA_AUGMENTOR_TRAIN.DISABLE_AUG_LIST: ['placeholder']
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+ 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}]
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+ 2023-04-01 00:37:35,969 INFO
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+ cfg.DATA_CONFIG.DATA_AUGMENTOR_TEST = edict()
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+ 2023-04-01 00:37:35,970 INFO cfg.DATA_CONFIG.DATA_AUGMENTOR_TEST.DISABLE_AUG_LIST: ['placeholder']
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+ 2023-04-01 00:37:35,970 INFO cfg.DATA_CONFIG.DATA_AUGMENTOR_TEST.AUG_CONFIG_LIST: [{'NAME': 'global_alignment', 'rotation_axis': 2}]
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+ 2023-04-01 00:37:35,971 INFO
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+ cfg.DATA_CONFIG.DATA_AUGMENTOR = edict()
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+ 2023-04-01 00:37:35,971 INFO cfg.DATA_CONFIG.DATA_AUGMENTOR.DISABLE_AUG_LIST: ['placeholder']
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+ 2023-04-01 00:37:35,972 INFO cfg.DATA_CONFIG.DATA_AUGMENTOR.AUG_CONFIG_LIST: [{'NAME': 'global_alignment', 'rotation_axis': 2}]
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+ 2023-04-01 00:37:35,973 INFO
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+ cfg.DATA_CONFIG.POINT_FEATURE_ENCODING = edict()
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+ 2023-04-01 00:37:35,974 INFO cfg.DATA_CONFIG.POINT_FEATURE_ENCODING.encoding_type: absolute_coordinates_encoding
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+ 2023-04-01 00:37:35,975 INFO cfg.DATA_CONFIG.POINT_FEATURE_ENCODING.used_feature_list: ['x', 'y', 'z', 'r', 'g', 'b']
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+ 2023-04-01 00:37:35,976 INFO cfg.DATA_CONFIG.POINT_FEATURE_ENCODING.src_feature_list: ['x', 'y', 'z', 'r', 'g', 'b']
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+ 2023-04-01 00:37:35,976 INFO cfg.DATA_CONFIG.DATA_PROCESSOR: [{'NAME': 'mask_points_and_boxes_outside_range', 'REMOVE_OUTSIDE_BOXES': True}]
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+ 2023-04-01 00:37:35,977 INFO cfg.DATA_CONFIG._BASE_CONFIG_: cfgs/dataset_configs/scannet_dataset.yaml
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+ 2023-04-01 00:37:35,977 INFO cfg.VOXEL_SIZE: 0.02
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+ 2023-04-01 00:37:35,978 INFO cfg.N_CLASSES: 18
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+ 2023-04-01 00:37:35,979 INFO cfg.SEMANTIC_THR: 0.15
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+ 2023-04-01 00:37:35,980 INFO
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+ cfg.MODEL = edict()
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+ 2023-04-01 00:37:35,981 INFO cfg.MODEL.NAME: CAGroup3D
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+ 2023-04-01 00:37:35,982 INFO cfg.MODEL.VOXEL_SIZE: 0.02
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+ 2023-04-01 00:37:35,983 INFO cfg.MODEL.SEMANTIC_MIN_THR: 0.05
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+ 2023-04-01 00:37:35,983 INFO cfg.MODEL.SEMANTIC_ITER_VALUE: 0.02
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+ 2023-04-01 00:37:35,983 INFO cfg.MODEL.SEMANTIC_THR: 0.15
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+ 2023-04-01 00:37:35,984 INFO
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+ cfg.MODEL.BACKBONE_3D = edict()
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+ 2023-04-01 00:37:35,985 INFO cfg.MODEL.BACKBONE_3D.NAME: BiResNet
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+ 2023-04-01 00:37:35,986 INFO cfg.MODEL.BACKBONE_3D.IN_CHANNELS: 3
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+ 2023-04-01 00:37:35,986 INFO cfg.MODEL.BACKBONE_3D.OUT_CHANNELS: 64
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+ 2023-04-01 00:37:35,987 INFO
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+ cfg.MODEL.DENSE_HEAD = edict()
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+ 2023-04-01 00:37:35,987 INFO cfg.MODEL.DENSE_HEAD.NAME: CAGroup3DHead
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+ 2023-04-01 00:37:35,987 INFO cfg.MODEL.DENSE_HEAD.IN_CHANNELS: [64, 128, 256, 512]
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+ 2023-04-01 00:37:35,988 INFO cfg.MODEL.DENSE_HEAD.OUT_CHANNELS: 64
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+ 2023-04-01 00:37:35,988 INFO cfg.MODEL.DENSE_HEAD.SEMANTIC_THR: 0.15
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+ 2023-04-01 00:37:35,989 INFO cfg.MODEL.DENSE_HEAD.VOXEL_SIZE: 0.02
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+ 2023-04-01 00:37:35,989 INFO cfg.MODEL.DENSE_HEAD.N_CLASSES: 18
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+ 2023-04-01 00:37:35,989 INFO cfg.MODEL.DENSE_HEAD.N_REG_OUTS: 6
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+ 2023-04-01 00:37:35,990 INFO cfg.MODEL.DENSE_HEAD.CLS_KERNEL: 9
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+ 2023-04-01 00:37:35,990 INFO cfg.MODEL.DENSE_HEAD.WITH_YAW: False
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+ 2023-04-01 00:37:35,991 INFO cfg.MODEL.DENSE_HEAD.USE_SEM_SCORE: False
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+ 2023-04-01 00:37:35,991 INFO cfg.MODEL.DENSE_HEAD.EXPAND_RATIO: 3
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+ 2023-04-01 00:37:35,991 INFO
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+ cfg.MODEL.DENSE_HEAD.ASSIGNER = edict()
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+ 2023-04-01 00:37:35,992 INFO cfg.MODEL.DENSE_HEAD.ASSIGNER.NAME: CAGroup3DAssigner
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+ 2023-04-01 00:37:35,992 INFO cfg.MODEL.DENSE_HEAD.ASSIGNER.LIMIT: 27
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+ 2023-04-01 00:37:35,993 INFO cfg.MODEL.DENSE_HEAD.ASSIGNER.TOPK: 18
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+ 2023-04-01 00:37:35,993 INFO cfg.MODEL.DENSE_HEAD.ASSIGNER.N_SCALES: 4
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+ 2023-04-01 00:37:35,994 INFO
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+ cfg.MODEL.DENSE_HEAD.LOSS_OFFSET = edict()
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+ 2023-04-01 00:37:35,994 INFO cfg.MODEL.DENSE_HEAD.LOSS_OFFSET.NAME: SmoothL1Loss
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+ 2023-04-01 00:37:35,995 INFO cfg.MODEL.DENSE_HEAD.LOSS_OFFSET.BETA: 0.04
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+ 2023-04-01 00:37:35,995 INFO cfg.MODEL.DENSE_HEAD.LOSS_OFFSET.REDUCTION: sum
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+ 2023-04-01 00:37:35,995 INFO cfg.MODEL.DENSE_HEAD.LOSS_OFFSET.LOSS_WEIGHT: 1.0
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+ 2023-04-01 00:37:35,996 INFO
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+ cfg.MODEL.DENSE_HEAD.LOSS_BBOX = edict()
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+ 2023-04-01 00:37:35,997 INFO cfg.MODEL.DENSE_HEAD.LOSS_BBOX.NAME: IoU3DLoss
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+ 2023-04-01 00:37:35,997 INFO cfg.MODEL.DENSE_HEAD.LOSS_BBOX.WITH_YAW: False
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+ 2023-04-01 00:37:35,997 INFO cfg.MODEL.DENSE_HEAD.LOSS_BBOX.LOSS_WEIGHT: 1.0
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+ 2023-04-01 00:37:35,998 INFO
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+ cfg.MODEL.DENSE_HEAD.NMS_CONFIG = edict()
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+ 2023-04-01 00:37:35,998 INFO cfg.MODEL.DENSE_HEAD.NMS_CONFIG.SCORE_THR: 0.01
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+ 2023-04-01 00:37:35,999 INFO cfg.MODEL.DENSE_HEAD.NMS_CONFIG.NMS_PRE: 1000
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+ 2023-04-01 00:37:36,000 INFO cfg.MODEL.DENSE_HEAD.NMS_CONFIG.IOU_THR: 0.5
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+ 2023-04-01 00:37:36,000 INFO
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+ cfg.MODEL.ROI_HEAD = edict()
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+ 2023-04-01 00:37:36,001 INFO cfg.MODEL.ROI_HEAD.NAME: CAGroup3DRoIHead
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+ 2023-04-01 00:37:36,001 INFO cfg.MODEL.ROI_HEAD.NUM_CLASSES: 18
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+ 2023-04-01 00:37:36,002 INFO cfg.MODEL.ROI_HEAD.MIDDLE_FEATURE_SOURCE: [3]
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+ 2023-04-01 00:37:36,002 INFO cfg.MODEL.ROI_HEAD.GRID_SIZE: 7
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+ 2023-04-01 00:37:36,003 INFO cfg.MODEL.ROI_HEAD.VOXEL_SIZE: 0.02
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+ 2023-04-01 00:37:36,003 INFO cfg.MODEL.ROI_HEAD.COORD_KEY: 2
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+ 2023-04-01 00:37:36,004 INFO cfg.MODEL.ROI_HEAD.MLPS: [[64, 128, 128]]
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+ 2023-04-01 00:37:36,005 INFO cfg.MODEL.ROI_HEAD.CODE_SIZE: 6
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+ 2023-04-01 00:37:36,005 INFO cfg.MODEL.ROI_HEAD.ENCODE_SINCOS: False
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+ 2023-04-01 00:37:36,007 INFO cfg.MODEL.ROI_HEAD.ROI_PER_IMAGE: 128
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+ 2023-04-01 00:37:36,008 INFO cfg.MODEL.ROI_HEAD.ROI_FG_RATIO: 0.9
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+ 2023-04-01 00:37:36,009 INFO cfg.MODEL.ROI_HEAD.REG_FG_THRESH: 0.3
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+ 2023-04-01 00:37:36,009 INFO cfg.MODEL.ROI_HEAD.ROI_CONV_KERNEL: 5
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+ 2023-04-01 00:37:36,010 INFO cfg.MODEL.ROI_HEAD.ENLARGE_RATIO: False
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+ 2023-04-01 00:37:36,010 INFO cfg.MODEL.ROI_HEAD.USE_IOU_LOSS: False
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+ 2023-04-01 00:37:36,011 INFO cfg.MODEL.ROI_HEAD.USE_GRID_OFFSET: False
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+ 2023-04-01 00:37:36,011 INFO cfg.MODEL.ROI_HEAD.USE_SIMPLE_POOLING: True
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+ 2023-04-01 00:37:36,012 INFO cfg.MODEL.ROI_HEAD.USE_CENTER_POOLING: True
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+ 2023-04-01 00:37:36,012 INFO
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+ cfg.MODEL.ROI_HEAD.LOSS_WEIGHTS = edict()
132
+ 2023-04-01 00:37:36,013 INFO cfg.MODEL.ROI_HEAD.LOSS_WEIGHTS.RCNN_CLS_WEIGHT: 1.0
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+ 2023-04-01 00:37:36,014 INFO cfg.MODEL.ROI_HEAD.LOSS_WEIGHTS.RCNN_REG_WEIGHT: 1.0
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+ 2023-04-01 00:37:36,014 INFO cfg.MODEL.ROI_HEAD.LOSS_WEIGHTS.RCNN_IOU_WEIGHT: 1.0
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+ 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]
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+ 2023-04-01 00:37:36,015 INFO
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+ cfg.MODEL.POST_PROCESSING = edict()
138
+ 2023-04-01 00:37:36,016 INFO cfg.MODEL.POST_PROCESSING.RECALL_THRESH_LIST: [0.25, 0.5]
139
+ 2023-04-01 00:37:36,017 INFO cfg.MODEL.POST_PROCESSING.EVAL_METRIC: scannet
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+ 2023-04-01 00:37:36,018 INFO
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+ cfg.OPTIMIZATION = edict()
142
+ 2023-04-01 00:37:36,019 INFO cfg.OPTIMIZATION.BATCH_SIZE_PER_GPU: 16
143
+ 2023-04-01 00:37:36,019 INFO cfg.OPTIMIZATION.NUM_EPOCHS: 1
144
+ 2023-04-01 00:37:36,019 INFO cfg.OPTIMIZATION.OPTIMIZER: adamW
145
+ 2023-04-01 00:37:36,019 INFO cfg.OPTIMIZATION.LR: 0.001
146
+ 2023-04-01 00:37:36,020 INFO cfg.OPTIMIZATION.WEIGHT_DECAY: 0.0001
147
+ 2023-04-01 00:37:36,020 INFO cfg.OPTIMIZATION.DECAY_STEP_LIST: [7, 9]
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+ 2023-04-01 00:37:36,020 INFO cfg.OPTIMIZATION.LR_DECAY: 0.1
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+ 2023-04-01 00:37:36,021 INFO cfg.OPTIMIZATION.GRAD_NORM_CLIP: 10
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+ 2023-04-01 00:37:36,021 INFO cfg.OPTIMIZATION.PCT_START: 0.4
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+ 2023-04-01 00:37:36,022 INFO cfg.OPTIMIZATION.DIV_FACTOR: 10
152
+ 2023-04-01 00:37:36,023 INFO cfg.OPTIMIZATION.LR_CLIP: 1e-07
153
+ 2023-04-01 00:37:36,024 INFO cfg.OPTIMIZATION.LR_WARMUP: False
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+ 2023-04-01 00:37:36,024 INFO cfg.OPTIMIZATION.WARMUP_EPOCH: 1
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+ 2023-04-01 00:37:36,025 INFO cfg.TAG: CAGroup3D
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+ 2023-04-01 00:37:36,025 INFO cfg.EXP_GROUP_PATH: scannet_models
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+ 2023-04-01 00:37:36,026 INFO Loading SCANNET dataset
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+ 2023-04-01 00:37:36,070 INFO Total samples for SCANNET dataset: 312
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+ 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
160
+ 2023-04-01 00:37:44,989 INFO ==> Checkpoint trained from version: pcdet+0.5.2+4ae8a35+py6af8eab
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+ 2023-04-01 00:37:45,137 INFO ==> Done (loaded 838/838)
162
+ 2023-04-01 00:37:46,123 INFO *************** EPOCH 1 EVALUATION *****************
163
+ 2023-04-01 02:31:46,714 INFO *************** Performance of EPOCH 1 *****************
164
+ 2023-04-01 02:31:46,716 INFO Generate label finished(sec_per_example: 21.9079 second).
165
+ 2023-04-01 02:31:46,716 INFO recall_roi_0.25: 0.000000
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+ 2023-04-01 02:31:46,717 INFO recall_rcnn_0.25: 0.000000
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+ 2023-04-01 02:31:46,717 INFO recall_roi_0.5: 0.000000
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+ 2023-04-01 02:31:46,718 INFO recall_rcnn_0.5: 0.000000
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+ 2023-04-01 02:31:46,720 INFO Average predicted number of objects(312 samples): 307.683
170
+ 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}
171
+ 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
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+ 2023-04-01 02:32:02,596 INFO ****************Evaluation done.*****************
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