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eval/epoch_12/val/default/log_eval_20230401-192759.txt
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1 |
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2023-04-01 19:27:59,514 INFO **********************Start logging**********************
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2023-04-01 19:27:59,515 INFO CUDA_VISIBLE_DEVICES=ALL
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2023-04-01 19:27:59,516 INFO total_batch_size: 16
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2023-04-01 19:27:59,516 INFO cfg_file cfgs/sunrgbd_models/CAGroup3D.yaml
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2023-04-01 19:27:59,517 INFO batch_size 16
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2023-04-01 19:27:59,517 INFO workers 4
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2023-04-01 19:27:59,518 INFO extra_tag cagroup3d-win10-sunrgbd-eval
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2023-04-01 19:27:59,519 INFO ckpt ../output/sunrgbd_models/CAGroup3D/cagroup3d-win10-sunrgbd-train/ckpt/checkpoint_epoch_12.pth
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2023-04-01 19:27:59,520 INFO launcher pytorch
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2023-04-01 19:27:59,521 INFO tcp_port 18888
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2023-04-01 19:27:59,521 INFO set_cfgs None
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2023-04-01 19:27:59,522 INFO max_waiting_mins 30
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2023-04-01 19:27:59,523 INFO start_epoch 0
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2023-04-01 19:27:59,523 INFO eval_tag default
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2023-04-01 19:27:59,524 INFO eval_all False
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2023-04-01 19:27:59,525 INFO ckpt_dir None
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2023-04-01 19:27:59,525 INFO save_to_file False
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2023-04-01 19:27:59,526 INFO cfg.ROOT_DIR: C:\PINKAMENA\CITYU\CS5182\proj\CAGroup3D
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2023-04-01 19:27:59,526 INFO cfg.LOCAL_RANK: 0
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2023-04-01 19:27:59,527 INFO cfg.CLASS_NAMES: ['bed', 'table', 'sofa', 'chair', 'toilet', 'desk', 'dresser', 'night_stand', 'bookshelf', 'bathtub']
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2023-04-01 19:27:59,527 INFO
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cfg.DATA_CONFIG = edict()
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2023-04-01 19:27:59,528 INFO cfg.DATA_CONFIG.DATASET: SunrgbdDataset
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2023-04-01 19:27:59,529 INFO cfg.DATA_CONFIG.DATA_PATH: ../data/sunrgbd_data/sunrgbd
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2023-04-01 19:27:59,530 INFO cfg.DATA_CONFIG.PROCESSED_DATA_TAG: sunrgbd_processed_data_v0_5_0
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2023-04-01 19:27:59,530 INFO cfg.DATA_CONFIG.POINT_CLOUD_RANGE: [-40, -40, -10, 40, 40, 10]
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2023-04-01 19:27:59,531 INFO
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cfg.DATA_CONFIG.DATA_SPLIT = edict()
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2023-04-01 19:27:59,532 INFO cfg.DATA_CONFIG.DATA_SPLIT.train: train
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2023-04-01 19:27:59,532 INFO cfg.DATA_CONFIG.DATA_SPLIT.test: val
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2023-04-01 19:27:59,533 INFO
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cfg.DATA_CONFIG.REPEAT = edict()
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2023-04-01 19:27:59,534 INFO cfg.DATA_CONFIG.REPEAT.train: 4
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2023-04-01 19:27:59,535 INFO cfg.DATA_CONFIG.REPEAT.test: 1
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2023-04-01 19:27:59,536 INFO
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cfg.DATA_CONFIG.INFO_PATH = edict()
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2023-04-01 19:27:59,536 INFO cfg.DATA_CONFIG.INFO_PATH.train: ['sunrgbd_infos_train.pkl']
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2023-04-01 19:27:59,537 INFO cfg.DATA_CONFIG.INFO_PATH.test: ['sunrgbd_infos_val.pkl']
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2023-04-01 19:27:59,537 INFO cfg.DATA_CONFIG.GET_ITEM_LIST: ['points']
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2023-04-01 19:27:59,538 INFO cfg.DATA_CONFIG.FILTER_EMPTY_BOXES_FOR_TRAIN: True
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2023-04-01 19:27:59,539 INFO
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cfg.DATA_CONFIG.DATA_AUGMENTOR_TRAIN = edict()
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2023-04-01 19:27:59,540 INFO cfg.DATA_CONFIG.DATA_AUGMENTOR_TRAIN.DISABLE_AUG_LIST: ['placeholder']
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2023-04-01 19:27:59,542 INFO cfg.DATA_CONFIG.DATA_AUGMENTOR_TRAIN.AUG_CONFIG_LIST: [{'NAME': 'indoor_point_sample', 'num_points': 100000}, {'NAME': 'random_world_flip', 'ALONG_AXIS_LIST': ['y']}, {'NAME': 'random_world_rotation_mmdet3d', 'WORLD_ROT_ANGLE': [-0.523599, 0.523599]}, {'NAME': 'random_world_scaling', 'WORLD_SCALE_RANGE': [0.85, 1.15]}, {'NAME': 'random_world_translation', 'ALONG_AXIS_LIST': ['x', 'y', 'z'], 'NOISE_TRANSLATE_STD': 0.1}]
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2023-04-01 19:27:59,544 INFO
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cfg.DATA_CONFIG.DATA_AUGMENTOR_TEST = edict()
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2023-04-01 19:27:59,545 INFO cfg.DATA_CONFIG.DATA_AUGMENTOR_TEST.DISABLE_AUG_LIST: ['placeholder']
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2023-04-01 19:27:59,546 INFO cfg.DATA_CONFIG.DATA_AUGMENTOR_TEST.AUG_CONFIG_LIST: [{'NAME': 'indoor_point_sample', 'num_points': 100000}]
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2023-04-01 19:27:59,547 INFO
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cfg.DATA_CONFIG.DATA_AUGMENTOR = edict()
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2023-04-01 19:27:59,548 INFO cfg.DATA_CONFIG.DATA_AUGMENTOR.DISABLE_AUG_LIST: ['placeholder']
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2023-04-01 19:27:59,548 INFO cfg.DATA_CONFIG.DATA_AUGMENTOR.AUG_CONFIG_LIST: [{'NAME': 'indoor_point_sample', 'num_points': 50000}]
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2023-04-01 19:27:59,549 INFO
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cfg.DATA_CONFIG.POINT_FEATURE_ENCODING = edict()
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2023-04-01 19:27:59,550 INFO cfg.DATA_CONFIG.POINT_FEATURE_ENCODING.encoding_type: absolute_coordinates_encoding
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2023-04-01 19:27:59,551 INFO cfg.DATA_CONFIG.POINT_FEATURE_ENCODING.used_feature_list: ['x', 'y', 'z', 'r', 'g', 'b']
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2023-04-01 19:27:59,552 INFO cfg.DATA_CONFIG.POINT_FEATURE_ENCODING.src_feature_list: ['x', 'y', 'z', 'r', 'g', 'b']
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2023-04-01 19:27:59,553 INFO cfg.DATA_CONFIG.DATA_PROCESSOR: [{'NAME': 'mask_points_and_boxes_outside_range', 'REMOVE_OUTSIDE_BOXES': False}]
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2023-04-01 19:27:59,554 INFO cfg.DATA_CONFIG._BASE_CONFIG_: cfgs/dataset_configs/sunrgbd_dataset.yaml
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2023-04-01 19:27:59,555 INFO cfg.VOXEL_SIZE: 0.02
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61 |
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2023-04-01 19:27:59,555 INFO cfg.N_CLASSES: 10
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2023-04-01 19:27:59,556 INFO cfg.SEMANTIC_THR: 0.15
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2023-04-01 19:27:59,556 INFO
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cfg.MODEL = edict()
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2023-04-01 19:27:59,557 INFO cfg.MODEL.NAME: CAGroup3D
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66 |
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2023-04-01 19:27:59,558 INFO cfg.MODEL.VOXEL_SIZE: 0.02
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2023-04-01 19:27:59,559 INFO cfg.MODEL.SEMANTIC_MIN_THR: 0.05
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2023-04-01 19:27:59,559 INFO cfg.MODEL.SEMANTIC_ITER_VALUE: 0.02
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2023-04-01 19:27:59,560 INFO cfg.MODEL.SEMANTIC_THR: 0.15
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2023-04-01 19:27:59,561 INFO
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71 |
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cfg.MODEL.BACKBONE_3D = edict()
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72 |
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2023-04-01 19:27:59,561 INFO cfg.MODEL.BACKBONE_3D.NAME: BiResNet
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73 |
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2023-04-01 19:27:59,562 INFO cfg.MODEL.BACKBONE_3D.IN_CHANNELS: 3
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74 |
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2023-04-01 19:27:59,562 INFO cfg.MODEL.BACKBONE_3D.OUT_CHANNELS: 64
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75 |
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2023-04-01 19:27:59,563 INFO
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76 |
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cfg.MODEL.DENSE_HEAD = edict()
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77 |
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2023-04-01 19:27:59,563 INFO cfg.MODEL.DENSE_HEAD.NAME: CAGroup3DHead
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78 |
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2023-04-01 19:27:59,564 INFO cfg.MODEL.DENSE_HEAD.IN_CHANNELS: [64, 128, 256, 512]
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79 |
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2023-04-01 19:27:59,564 INFO cfg.MODEL.DENSE_HEAD.OUT_CHANNELS: 64
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80 |
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2023-04-01 19:27:59,565 INFO cfg.MODEL.DENSE_HEAD.SEMANTIC_THR: 0.15
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81 |
+
2023-04-01 19:27:59,565 INFO cfg.MODEL.DENSE_HEAD.VOXEL_SIZE: 0.02
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82 |
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2023-04-01 19:27:59,565 INFO cfg.MODEL.DENSE_HEAD.N_CLASSES: 10
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83 |
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2023-04-01 19:27:59,566 INFO cfg.MODEL.DENSE_HEAD.N_REG_OUTS: 8
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84 |
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2023-04-01 19:27:59,566 INFO cfg.MODEL.DENSE_HEAD.CLS_KERNEL: 9
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85 |
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2023-04-01 19:27:59,567 INFO cfg.MODEL.DENSE_HEAD.WITH_YAW: True
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86 |
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2023-04-01 19:27:59,567 INFO cfg.MODEL.DENSE_HEAD.USE_SEM_SCORE: False
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87 |
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2023-04-01 19:27:59,568 INFO cfg.MODEL.DENSE_HEAD.EXPAND_RATIO: 3
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88 |
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2023-04-01 19:27:59,568 INFO
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89 |
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cfg.MODEL.DENSE_HEAD.ASSIGNER = edict()
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90 |
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2023-04-01 19:27:59,569 INFO cfg.MODEL.DENSE_HEAD.ASSIGNER.NAME: CAGroup3DAssigner
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91 |
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2023-04-01 19:27:59,569 INFO cfg.MODEL.DENSE_HEAD.ASSIGNER.LIMIT: 27
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92 |
+
2023-04-01 19:27:59,569 INFO cfg.MODEL.DENSE_HEAD.ASSIGNER.TOPK: 18
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93 |
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2023-04-01 19:27:59,570 INFO cfg.MODEL.DENSE_HEAD.ASSIGNER.N_SCALES: 4
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94 |
+
2023-04-01 19:27:59,570 INFO
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95 |
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cfg.MODEL.DENSE_HEAD.LOSS_OFFSET = edict()
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96 |
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2023-04-01 19:27:59,571 INFO cfg.MODEL.DENSE_HEAD.LOSS_OFFSET.NAME: SmoothL1Loss
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97 |
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2023-04-01 19:27:59,571 INFO cfg.MODEL.DENSE_HEAD.LOSS_OFFSET.BETA: 0.04
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98 |
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2023-04-01 19:27:59,571 INFO cfg.MODEL.DENSE_HEAD.LOSS_OFFSET.REDUCTION: sum
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99 |
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2023-04-01 19:27:59,572 INFO cfg.MODEL.DENSE_HEAD.LOSS_OFFSET.LOSS_WEIGHT: 0.2
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100 |
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2023-04-01 19:27:59,572 INFO
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101 |
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cfg.MODEL.DENSE_HEAD.LOSS_BBOX = edict()
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102 |
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2023-04-01 19:27:59,572 INFO cfg.MODEL.DENSE_HEAD.LOSS_BBOX.NAME: IoU3DLoss
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103 |
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2023-04-01 19:27:59,573 INFO cfg.MODEL.DENSE_HEAD.LOSS_BBOX.WITH_YAW: True
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104 |
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2023-04-01 19:27:59,573 INFO cfg.MODEL.DENSE_HEAD.LOSS_BBOX.LOSS_WEIGHT: 1.0
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105 |
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2023-04-01 19:27:59,573 INFO
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106 |
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cfg.MODEL.DENSE_HEAD.NMS_CONFIG = edict()
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107 |
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2023-04-01 19:27:59,574 INFO cfg.MODEL.DENSE_HEAD.NMS_CONFIG.SCORE_THR: 0.01
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108 |
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2023-04-01 19:27:59,574 INFO cfg.MODEL.DENSE_HEAD.NMS_CONFIG.NMS_PRE: 1000
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109 |
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2023-04-01 19:27:59,574 INFO cfg.MODEL.DENSE_HEAD.NMS_CONFIG.IOU_THR: 0.5
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110 |
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2023-04-01 19:27:59,575 INFO
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111 |
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cfg.MODEL.ROI_HEAD = edict()
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112 |
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2023-04-01 19:27:59,576 INFO cfg.MODEL.ROI_HEAD.NAME: CAGroup3DRoIHead
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113 |
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2023-04-01 19:27:59,576 INFO cfg.MODEL.ROI_HEAD.NUM_CLASSES: 10
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114 |
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2023-04-01 19:27:59,576 INFO cfg.MODEL.ROI_HEAD.MIDDLE_FEATURE_SOURCE: [3]
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115 |
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2023-04-01 19:27:59,577 INFO cfg.MODEL.ROI_HEAD.GRID_SIZE: 7
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116 |
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2023-04-01 19:27:59,577 INFO cfg.MODEL.ROI_HEAD.VOXEL_SIZE: 0.02
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117 |
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2023-04-01 19:27:59,577 INFO cfg.MODEL.ROI_HEAD.COORD_KEY: 2
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118 |
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2023-04-01 19:27:59,578 INFO cfg.MODEL.ROI_HEAD.MLPS: [[64, 128, 128]]
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119 |
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2023-04-01 19:27:59,578 INFO cfg.MODEL.ROI_HEAD.CODE_SIZE: 7
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120 |
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2023-04-01 19:27:59,578 INFO cfg.MODEL.ROI_HEAD.ENCODE_SINCOS: True
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121 |
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2023-04-01 19:27:59,579 INFO cfg.MODEL.ROI_HEAD.ROI_PER_IMAGE: 128
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122 |
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2023-04-01 19:27:59,579 INFO cfg.MODEL.ROI_HEAD.ROI_FG_RATIO: 0.9
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123 |
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2023-04-01 19:27:59,579 INFO cfg.MODEL.ROI_HEAD.REG_FG_THRESH: 0.3
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124 |
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2023-04-01 19:27:59,580 INFO cfg.MODEL.ROI_HEAD.ROI_CONV_KERNEL: 5
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125 |
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2023-04-01 19:27:59,580 INFO cfg.MODEL.ROI_HEAD.ENLARGE_RATIO: False
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126 |
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2023-04-01 19:27:59,580 INFO cfg.MODEL.ROI_HEAD.USE_IOU_LOSS: True
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127 |
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2023-04-01 19:27:59,581 INFO cfg.MODEL.ROI_HEAD.USE_GRID_OFFSET: False
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128 |
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2023-04-01 19:27:59,581 INFO cfg.MODEL.ROI_HEAD.USE_SIMPLE_POOLING: True
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129 |
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2023-04-01 19:27:59,581 INFO cfg.MODEL.ROI_HEAD.USE_CENTER_POOLING: True
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130 |
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2023-04-01 19:27:59,582 INFO
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131 |
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cfg.MODEL.ROI_HEAD.LOSS_WEIGHTS = edict()
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132 |
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2023-04-01 19:27:59,582 INFO cfg.MODEL.ROI_HEAD.LOSS_WEIGHTS.RCNN_CLS_WEIGHT: 1.0
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133 |
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2023-04-01 19:27:59,582 INFO cfg.MODEL.ROI_HEAD.LOSS_WEIGHTS.RCNN_REG_WEIGHT: 0.5
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134 |
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2023-04-01 19:27:59,583 INFO cfg.MODEL.ROI_HEAD.LOSS_WEIGHTS.RCNN_IOU_WEIGHT: 1.0
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135 |
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2023-04-01 19:27:59,584 INFO cfg.MODEL.ROI_HEAD.LOSS_WEIGHTS.CODE_WEIGHT: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
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136 |
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2023-04-01 19:27:59,584 INFO
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cfg.MODEL.POST_PROCESSING = edict()
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138 |
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2023-04-01 19:27:59,585 INFO cfg.MODEL.POST_PROCESSING.RECALL_THRESH_LIST: [0.25, 0.5]
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139 |
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2023-04-01 19:27:59,585 INFO cfg.MODEL.POST_PROCESSING.EVAL_METRIC: scannet
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140 |
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2023-04-01 19:27:59,585 INFO
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cfg.OPTIMIZATION = edict()
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142 |
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2023-04-01 19:27:59,586 INFO cfg.OPTIMIZATION.BATCH_SIZE_PER_GPU: 16
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143 |
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2023-04-01 19:27:59,586 INFO cfg.OPTIMIZATION.NUM_EPOCHS: 1
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144 |
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2023-04-01 19:27:59,586 INFO cfg.OPTIMIZATION.OPTIMIZER: adamW
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145 |
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2023-04-01 19:27:59,587 INFO cfg.OPTIMIZATION.LR: 0.001
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146 |
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2023-04-01 19:27:59,587 INFO cfg.OPTIMIZATION.WEIGHT_DECAY: 0.0001
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147 |
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2023-04-01 19:27:59,587 INFO cfg.OPTIMIZATION.DECAY_STEP_LIST: [8, 11]
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148 |
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2023-04-01 19:27:59,587 INFO cfg.OPTIMIZATION.LR_DECAY: 0.1
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149 |
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2023-04-01 19:27:59,588 INFO cfg.OPTIMIZATION.GRAD_NORM_CLIP: 10
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150 |
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2023-04-01 19:27:59,588 INFO cfg.OPTIMIZATION.PCT_START: 0.4
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151 |
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2023-04-01 19:27:59,588 INFO cfg.OPTIMIZATION.DIV_FACTOR: 10
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152 |
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2023-04-01 19:27:59,589 INFO cfg.OPTIMIZATION.LR_CLIP: 1e-07
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153 |
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2023-04-01 19:27:59,589 INFO cfg.OPTIMIZATION.LR_WARMUP: False
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154 |
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2023-04-01 19:27:59,589 INFO cfg.OPTIMIZATION.WARMUP_EPOCH: 1
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155 |
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2023-04-01 19:27:59,589 INFO cfg.TAG: CAGroup3D
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156 |
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2023-04-01 19:27:59,590 INFO cfg.EXP_GROUP_PATH: sunrgbd_models
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157 |
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2023-04-01 19:27:59,590 INFO Loading SUNRGBD dataset
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158 |
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2023-04-01 19:27:59,747 INFO Total samples for SUNRGBD dataset: 5050
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2023-04-01 19:28:01,314 INFO ==> Loading parameters from checkpoint ../output/sunrgbd_models/CAGroup3D/cagroup3d-win10-sunrgbd-train/ckpt/checkpoint_epoch_12.pth to CPU
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2023-04-01 19:28:01,922 INFO ==> Checkpoint trained from version: pcdet+0.5.2+0000000
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2023-04-01 19:28:02,005 INFO ==> Done (loaded 638/638)
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2023-04-01 19:28:02,415 INFO *************** EPOCH 12 EVALUATION *****************
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163 |
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2023-04-02 00:04:15,050 INFO *************** Performance of EPOCH 12 *****************
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164 |
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2023-04-02 00:04:15,051 INFO Generate label finished(sec_per_example: 3.2807 second).
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2023-04-02 00:04:15,051 INFO recall_roi_0.25: 0.000000
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2023-04-02 00:04:15,052 INFO recall_rcnn_0.25: 0.000000
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2023-04-02 00:04:15,053 INFO recall_roi_0.5: 0.000000
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2023-04-02 00:04:15,053 INFO recall_rcnn_0.5: 0.000000
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2023-04-02 00:04:15,058 INFO Average predicted number of objects(5050 samples): 88.007
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2023-04-02 00:04:43,371 INFO {'bed_AP_0.25': 0.8857589960098267, 'table_AP_0.25': 0.590636670589447, 'sofa_AP_0.25': 0.7279834747314453, 'chair_AP_0.25': 0.8261127471923828, 'toilet_AP_0.25': 0.9085497856140137, 'desk_AP_0.25': 0.4028821587562561, 'dresser_AP_0.25': 0.39120715856552124, 'night_stand_AP_0.25': 0.6928218603134155, 'bookshelf_AP_0.25': 0.346212774515152, 'bathtub_AP_0.25': 0.8180574774742126, 'mAP_0.25': 0.659022331237793, 'bed_rec_0.25': 0.9728155339805825, 'table_rec_0.25': 0.9557069846678024, 'sofa_rec_0.25': 0.9617224880382775, 'chair_rec_0.25': 0.9517771565495208, 'toilet_rec_0.25': 0.9862068965517241, 'desk_rec_0.25': 0.9091392136025505, 'dresser_rec_0.25': 0.9174311926605505, 'night_stand_rec_0.25': 0.9333333333333333, 'bookshelf_rec_0.25': 0.8014184397163121, 'bathtub_rec_0.25': 0.9387755102040817, 'mAR_0.25': 0.9328326749304734, 'bed_AP_0.50': 0.6525242924690247, 'table_AP_0.50': 0.3740265369415283, 'sofa_AP_0.50': 0.6063357591629028, 'chair_AP_0.50': 0.6926975250244141, 'toilet_AP_0.50': 0.7042118310928345, 'desk_AP_0.50': 0.17653562128543854, 'dresser_AP_0.50': 0.30782946944236755, 'night_stand_AP_0.50': 0.5847228765487671, 'bookshelf_AP_0.50': 0.16873708367347717, 'bathtub_AP_0.50': 0.5251516103744507, 'mAP_0.50': 0.47927722334861755, 'bed_rec_0.50': 0.7398058252427184, 'table_rec_0.50': 0.659710391822828, 'sofa_rec_0.50': 0.7894736842105263, 'chair_rec_0.50': 0.8108027156549521, 'toilet_rec_0.50': 0.7862068965517242, 'desk_rec_0.50': 0.5143464399574921, 'dresser_rec_0.50': 0.6422018348623854, 'night_stand_rec_0.50': 0.7450980392156863, 'bookshelf_rec_0.50': 0.425531914893617, 'bathtub_rec_0.50': 0.673469387755102, 'mAR_0.50': 0.6786647130167032}
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2023-04-02 00:04:43,376 INFO Result is save to C:\PINKAMENA\CITYU\CS5182\proj\CAGroup3D\output\sunrgbd_models\CAGroup3D\cagroup3d-win10-sunrgbd-eval\eval\epoch_12\val\default
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2023-04-02 00:04:43,377 INFO ****************Evaluation done.*****************
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eval/epoch_12/val/default/result.pkl
ADDED
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size 65701817
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