| 2025/09/13 12:49:49 - mmengine - INFO - | |
| ------------------------------------------------------------ | |
| System environment: | |
| sys.platform: linux | |
| Python: 3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0] | |
| CUDA available: True | |
| numpy_random_seed: 1829955487 | |
| GPU 0: NVIDIA H100 80GB HBM3 | |
| CUDA_HOME: /usr/local/cuda | |
| NVCC: Cuda compilation tools, release 12.1, V12.1.105 | |
| GCC: gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 | |
| PyTorch: 2.1.2+cu121 | |
| PyTorch compiling details: PyTorch built with: | |
| - GCC 9.3 | |
| - C++ Version: 201703 | |
| - Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications | |
| - Intel(R) MKL-DNN v3.1.1 (Git Hash 64f6bcbcbab628e96f33a62c3e975f8535a7bde4) | |
| - OpenMP 201511 (a.k.a. OpenMP 4.5) | |
| - LAPACK is enabled (usually provided by MKL) | |
| - NNPACK is enabled | |
| - CPU capability usage: AVX512 | |
| - CUDA Runtime 12.1 | |
| - NVCC architecture flags: -gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90 | |
| - CuDNN 8.9.2 | |
| - Magma 2.6.1 | |
| - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=12.1, CUDNN_VERSION=8.9.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=old-style-cast -Wno-invalid-partial-specialization -Wno-unused-private-field -Wno-aligned-allocation-unavailable -Wno-missing-braces -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_DISABLE_GPU_ASSERTS=ON, TORCH_VERSION=2.1.2, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, | |
| TorchVision: 0.16.2+cu121 | |
| OpenCV: 4.11.0 | |
| MMEngine: 0.9.0 | |
| Runtime environment: | |
| cudnn_benchmark: False | |
| mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} | |
| dist_cfg: {'backend': 'nccl'} | |
| seed: 1829955487 | |
| Distributed launcher: none | |
| Distributed training: False | |
| GPU number: 1 | |
| ------------------------------------------------------------ | |
| 2025/09/13 12:49:50 - mmengine - INFO - Config: | |
| EPOCHS = 12 | |
| backend_args = None | |
| class_agnostic_eval = True | |
| classes_stru3d = [ | |
| 'door', | |
| 'window', | |
| ] | |
| custom_hooks = [ | |
| dict(after_iter=True, type='EmptyCacheHook'), | |
| ] | |
| custom_imports = dict(imports=[ | |
| 'tr3d', | |
| ]) | |
| data_root = '/home/jovyan/users/koodiazhnyi/msu-masters/tr3d/data/structured3d' | |
| dataset_type = 'Stru3DDataset' | |
| default_hooks = dict( | |
| checkpoint=dict( | |
| _scope_='mmdet3d', interval=1, max_keep_ckpts=2, | |
| type='CheckpointHook'), | |
| logger=dict(_scope_='mmdet3d', interval=50, type='LoggerHook'), | |
| param_scheduler=dict(_scope_='mmdet3d', type='ParamSchedulerHook'), | |
| sampler_seed=dict(_scope_='mmdet3d', type='DistSamplerSeedHook'), | |
| timer=dict(_scope_='mmdet3d', type='IterTimerHook'), | |
| visualization=dict(_scope_='mmdet3d', type='Det3DVisualizationHook')) | |
| default_scope = 'mmdet3d' | |
| env_cfg = dict( | |
| cudnn_benchmark=False, | |
| dist_cfg=dict(backend='nccl'), | |
| mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0)) | |
| launcher = 'none' | |
| load_from = None | |
| log_level = 'INFO' | |
| log_processor = dict( | |
| _scope_='mmdet3d', by_epoch=True, type='LogProcessor', window_size=50) | |
| metainfo = dict(classes=[ | |
| 'door', | |
| 'window', | |
| ]) | |
| model = dict( | |
| backbone=dict( | |
| depth=34, | |
| in_channels=3, | |
| norm='batch', | |
| num_planes=( | |
| 64, | |
| 128, | |
| 128, | |
| 128, | |
| ), | |
| type='TR3DMinkResNet'), | |
| bbox_head=dict( | |
| add_z_feat=True, | |
| angles=[ | |
| False, | |
| ], | |
| datasets=[ | |
| 'structured3d', | |
| ], | |
| datasets_classes=[ | |
| [ | |
| 'door', | |
| 'window', | |
| ], | |
| ], | |
| datasets_weights=[ | |
| 1.0, | |
| ], | |
| in_channels=128, | |
| label2level=[ | |
| [ | |
| 0, | |
| 0, | |
| ], | |
| ], | |
| layout_level=1, | |
| loss_weights=[ | |
| [ | |
| 0.75, | |
| 0.25, | |
| ], | |
| ], | |
| n_q_feats=10, | |
| n_spconv2d=3, | |
| num_layout_reg_outs=5, | |
| num_reg_outs=6, | |
| pts_center_threshold=6, | |
| pts_center_threshold_layout=6, | |
| type='TR3DHead', | |
| voxel_size=0.01), | |
| data_preprocessor=dict(type='Det3DDataPreprocessor'), | |
| neck=dict( | |
| in_channels=( | |
| 64, | |
| 128, | |
| 128, | |
| 128, | |
| ), out_channels=128, type='TR3DNeck'), | |
| test_cfg=dict( | |
| class_agnostic_eval=True, | |
| enable_double_layout_nms=True, | |
| iou_thr=0.15, | |
| iou_thr_layout=0.1, | |
| nms_pre=1000, | |
| nms_pre_layout=150, | |
| nms_radius=0.1, | |
| score_thr=0.35, | |
| score_thr_layout=0.5), | |
| train_cfg=dict(), | |
| type='MinkSingleStage3DDetector') | |
| optim_wrapper = dict( | |
| clip_grad=dict(max_norm=10, norm_type=2), | |
| optimizer=dict(lr=0.001, type='AdamW', weight_decay=0.0001), | |
| type='OptimWrapper') | |
| param_scheduler = dict( | |
| begin=0, | |
| by_epoch=True, | |
| end=12, | |
| gamma=0.1, | |
| milestones=[ | |
| 8, | |
| 11, | |
| ], | |
| type='MultiStepLR') | |
| resume = False | |
| test_cfg = dict(type='TestLoop') | |
| test_dataloader = dict( | |
| batch_size=1, | |
| dataset=dict( | |
| ann_file='structured3d_infos_val_spatial_lm_v3.pkl', | |
| backend_args=None, | |
| box_type_3d='Depth', | |
| data_root= | |
| '/home/jovyan/users/koodiazhnyi/msu-masters/tr3d/data/structured3d', | |
| metainfo=dict(classes=[ | |
| 'door', | |
| 'window', | |
| ]), | |
| pipeline=[ | |
| dict( | |
| backend_args=None, | |
| coord_type='DEPTH', | |
| load_dim=6, | |
| shift_height=False, | |
| type='LoadPointsFromFile', | |
| use_color=True, | |
| use_dim=[ | |
| 0, | |
| 1, | |
| 2, | |
| 3, | |
| 4, | |
| 5, | |
| ]), | |
| dict(type='AddLayoutLabels'), | |
| dict( | |
| flip=False, | |
| img_scale=( | |
| 1333, | |
| 800, | |
| ), | |
| pts_scale_ratio=1, | |
| transforms=[ | |
| dict( | |
| color_mean=[ | |
| 127.5, | |
| 127.5, | |
| 127.5, | |
| ], | |
| type='NormalizePointsColor'), | |
| ], | |
| type='MultiScaleFlipAug3D'), | |
| dict(type='LayoutOrientation'), | |
| dict(keys=[ | |
| 'points', | |
| ], load_meta=True, type='Pack3DDetInputs_'), | |
| ], | |
| test_mode=True, | |
| type='Stru3DDataset'), | |
| num_workers=1, | |
| sampler=dict(shuffle=False, type='DefaultSampler')) | |
| test_evaluator = dict( | |
| datasets=[ | |
| 'structured3d', | |
| ], | |
| datasets_classes=[ | |
| [ | |
| 'door', | |
| 'window', | |
| ], | |
| ], | |
| dist_thr=[ | |
| 0.4, | |
| 0.6, | |
| ], | |
| floor_and_ceiling=False, | |
| type='IndoorLayoutMetric_') | |
| test_pipeline = [ | |
| dict( | |
| backend_args=None, | |
| coord_type='DEPTH', | |
| load_dim=6, | |
| shift_height=False, | |
| type='LoadPointsFromFile', | |
| use_color=True, | |
| use_dim=[ | |
| 0, | |
| 1, | |
| 2, | |
| 3, | |
| 4, | |
| 5, | |
| ]), | |
| dict(type='AddLayoutLabels'), | |
| dict( | |
| flip=False, | |
| img_scale=( | |
| 1333, | |
| 800, | |
| ), | |
| pts_scale_ratio=1, | |
| transforms=[ | |
| dict( | |
| color_mean=[ | |
| 127.5, | |
| 127.5, | |
| 127.5, | |
| ], | |
| type='NormalizePointsColor'), | |
| ], | |
| type='MultiScaleFlipAug3D'), | |
| dict(type='LayoutOrientation'), | |
| dict(keys=[ | |
| 'points', | |
| ], load_meta=True, type='Pack3DDetInputs_'), | |
| ] | |
| train_cfg = dict(max_epochs=12, type='EpochBasedTrainLoop', val_interval=1) | |
| train_dataloader = dict( | |
| batch_size=16, | |
| dataset=dict( | |
| dataset=dict( | |
| ann_file='structured3d_infos_train_spatial_lm_v3.pkl', | |
| backend_args=None, | |
| box_type_3d='Depth', | |
| data_root= | |
| '/home/jovyan/users/koodiazhnyi/msu-masters/tr3d/data/structured3d', | |
| filter_empty_gt=False, | |
| metainfo=dict(classes=[ | |
| 'door', | |
| 'window', | |
| ]), | |
| pipeline=[ | |
| dict( | |
| backend_args=None, | |
| coord_type='DEPTH', | |
| load_dim=6, | |
| shift_height=False, | |
| type='LoadPointsFromFile', | |
| use_color=True, | |
| use_dim=[ | |
| 0, | |
| 1, | |
| 2, | |
| 3, | |
| 4, | |
| 5, | |
| ]), | |
| dict( | |
| backend_args=None, | |
| type='LoadAnnotations3D', | |
| with_bbox_3d=True, | |
| with_label_3d=True, | |
| with_mask_3d=False, | |
| with_seg_3d=False), | |
| dict(type='AddLayoutLabels'), | |
| dict(num_points=0.33, type='TR3DPointSample'), | |
| dict( | |
| flip_ratio_bev_horizontal=0.5, | |
| flip_ratio_bev_vertical=0.5, | |
| sync_2d=False, | |
| type='RandomFlip3DLayout'), | |
| dict( | |
| rot_range=[ | |
| 0, | |
| 0, | |
| ], | |
| scale_ratio_range=[ | |
| 0.85, | |
| 1.15, | |
| ], | |
| shift_height=False, | |
| translation_std=[ | |
| 0.1, | |
| 0.1, | |
| 0.1, | |
| ], | |
| type='GlobalRotScaleTransLayout'), | |
| dict( | |
| color_mean=[ | |
| 127.5, | |
| 127.5, | |
| 127.5, | |
| ], | |
| type='NormalizePointsColor'), | |
| dict(type='LayoutOrientation'), | |
| dict( | |
| keys=[ | |
| 'points', | |
| 'gt_bboxes_3d', | |
| 'gt_labels_3d', | |
| ], | |
| type='Pack3DDetInputs_'), | |
| ], | |
| type='Stru3DDataset'), | |
| times=7, | |
| type='RepeatDataset'), | |
| num_workers=8, | |
| sampler=dict(shuffle=True, type='DefaultSampler')) | |
| train_pipeline = [ | |
| dict( | |
| backend_args=None, | |
| coord_type='DEPTH', | |
| load_dim=6, | |
| shift_height=False, | |
| type='LoadPointsFromFile', | |
| use_color=True, | |
| use_dim=[ | |
| 0, | |
| 1, | |
| 2, | |
| 3, | |
| 4, | |
| 5, | |
| ]), | |
| dict( | |
| backend_args=None, | |
| type='LoadAnnotations3D', | |
| with_bbox_3d=True, | |
| with_label_3d=True, | |
| with_mask_3d=False, | |
| with_seg_3d=False), | |
| dict(type='AddLayoutLabels'), | |
| dict(num_points=0.33, type='TR3DPointSample'), | |
| dict( | |
| flip_ratio_bev_horizontal=0.5, | |
| flip_ratio_bev_vertical=0.5, | |
| sync_2d=False, | |
| type='RandomFlip3DLayout'), | |
| dict( | |
| rot_range=[ | |
| 0, | |
| 0, | |
| ], | |
| scale_ratio_range=[ | |
| 0.85, | |
| 1.15, | |
| ], | |
| shift_height=False, | |
| translation_std=[ | |
| 0.1, | |
| 0.1, | |
| 0.1, | |
| ], | |
| type='GlobalRotScaleTransLayout'), | |
| dict(color_mean=[ | |
| 127.5, | |
| 127.5, | |
| 127.5, | |
| ], type='NormalizePointsColor'), | |
| dict(type='LayoutOrientation'), | |
| dict( | |
| keys=[ | |
| 'points', | |
| 'gt_bboxes_3d', | |
| 'gt_labels_3d', | |
| ], | |
| type='Pack3DDetInputs_'), | |
| ] | |
| val_cfg = dict(type='ValLoop') | |
| val_dataloader = dict( | |
| batch_size=1, | |
| dataset=dict( | |
| ann_file='structured3d_infos_val_spatial_lm_v3.pkl', | |
| backend_args=None, | |
| box_type_3d='Depth', | |
| data_root= | |
| '/home/jovyan/users/koodiazhnyi/msu-masters/tr3d/data/structured3d', | |
| metainfo=dict(classes=[ | |
| 'door', | |
| 'window', | |
| ]), | |
| pipeline=[ | |
| dict( | |
| backend_args=None, | |
| coord_type='DEPTH', | |
| load_dim=6, | |
| shift_height=False, | |
| type='LoadPointsFromFile', | |
| use_color=True, | |
| use_dim=[ | |
| 0, | |
| 1, | |
| 2, | |
| 3, | |
| 4, | |
| 5, | |
| ]), | |
| dict(type='AddLayoutLabels'), | |
| dict( | |
| flip=False, | |
| img_scale=( | |
| 1333, | |
| 800, | |
| ), | |
| pts_scale_ratio=1, | |
| transforms=[ | |
| dict( | |
| color_mean=[ | |
| 127.5, | |
| 127.5, | |
| 127.5, | |
| ], | |
| type='NormalizePointsColor'), | |
| ], | |
| type='MultiScaleFlipAug3D'), | |
| dict(type='LayoutOrientation'), | |
| dict(keys=[ | |
| 'points', | |
| ], load_meta=True, type='Pack3DDetInputs_'), | |
| ], | |
| test_mode=True, | |
| type='Stru3DDataset'), | |
| num_workers=1, | |
| sampler=dict(shuffle=False, type='DefaultSampler')) | |
| val_evaluator = dict( | |
| datasets=[ | |
| 'structured3d', | |
| ], | |
| datasets_classes=[ | |
| [ | |
| 'door', | |
| 'window', | |
| ], | |
| ], | |
| dist_thr=[ | |
| 0.4, | |
| 0.6, | |
| ], | |
| floor_and_ceiling=False, | |
| type='IndoorLayoutMetric_') | |
| vis_backends = [ | |
| dict(type='LocalVisBackend'), | |
| ] | |
| visualizer = dict( | |
| name='visualizer', | |
| type='Det3DLocalVisualizer', | |
| vis_backends=[ | |
| dict(type='LocalVisBackend'), | |
| ]) | |
| work_dir = './work_dirs/tr3d_1xb16_structured3d_v51' | |
| 2025/09/13 12:49:52 - mmengine - INFO - Distributed training is not used, all SyncBatchNorm (SyncBN) layers in the model will be automatically reverted to BatchNormXd layers if they are used. | |
| 2025/09/13 12:49:52 - mmengine - INFO - Hooks will be executed in the following order: | |
| before_run: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| (BELOW_NORMAL) LoggerHook | |
| -------------------- | |
| before_train: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| (NORMAL ) IterTimerHook | |
| (VERY_LOW ) CheckpointHook | |
| -------------------- | |
| before_train_epoch: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| (NORMAL ) IterTimerHook | |
| (NORMAL ) DistSamplerSeedHook | |
| (NORMAL ) EmptyCacheHook | |
| -------------------- | |
| before_train_iter: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| (NORMAL ) IterTimerHook | |
| -------------------- | |
| after_train_iter: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| (NORMAL ) IterTimerHook | |
| (NORMAL ) EmptyCacheHook | |
| (BELOW_NORMAL) LoggerHook | |
| (LOW ) ParamSchedulerHook | |
| (VERY_LOW ) CheckpointHook | |
| -------------------- | |
| after_train_epoch: | |
| (NORMAL ) IterTimerHook | |
| (NORMAL ) EmptyCacheHook | |
| (LOW ) ParamSchedulerHook | |
| (VERY_LOW ) CheckpointHook | |
| -------------------- | |
| before_val: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| -------------------- | |
| before_val_epoch: | |
| (NORMAL ) IterTimerHook | |
| (NORMAL ) EmptyCacheHook | |
| -------------------- | |
| before_val_iter: | |
| (NORMAL ) IterTimerHook | |
| -------------------- | |
| after_val_iter: | |
| (NORMAL ) IterTimerHook | |
| (NORMAL ) Det3DVisualizationHook | |
| (NORMAL ) EmptyCacheHook | |
| (BELOW_NORMAL) LoggerHook | |
| -------------------- | |
| after_val_epoch: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| (NORMAL ) IterTimerHook | |
| (NORMAL ) EmptyCacheHook | |
| (BELOW_NORMAL) LoggerHook | |
| (LOW ) ParamSchedulerHook | |
| (VERY_LOW ) CheckpointHook | |
| -------------------- | |
| after_val: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| -------------------- | |
| after_train: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| (VERY_LOW ) CheckpointHook | |
| -------------------- | |
| before_test: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| -------------------- | |
| before_test_epoch: | |
| (NORMAL ) IterTimerHook | |
| (NORMAL ) EmptyCacheHook | |
| -------------------- | |
| before_test_iter: | |
| (NORMAL ) IterTimerHook | |
| -------------------- | |
| after_test_iter: | |
| (NORMAL ) IterTimerHook | |
| (NORMAL ) Det3DVisualizationHook | |
| (NORMAL ) EmptyCacheHook | |
| (BELOW_NORMAL) LoggerHook | |
| -------------------- | |
| after_test_epoch: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| (NORMAL ) IterTimerHook | |
| (NORMAL ) EmptyCacheHook | |
| (BELOW_NORMAL) LoggerHook | |
| -------------------- | |
| after_test: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| -------------------- | |
| after_run: | |
| (BELOW_NORMAL) LoggerHook | |
| -------------------- | |
| 2025/09/13 12:49:53 - mmengine - INFO - ------------------------------ | |
| 2025/09/13 12:49:53 - mmengine - INFO - The length of training dataset: 2510 | |
| 2025/09/13 12:49:53 - mmengine - INFO - The number of instances per category in the dataset: | |
| +----------+--------+ | |
| | category | number | | |
| +----------+--------+ | |
| | door | 30101 | | |
| | window | 16551 | | |
| +----------+--------+ | |
| 2025/09/13 12:49:54 - mmengine - INFO - ------------------------------ | |
| 2025/09/13 12:49:54 - mmengine - INFO - The length of test dataset: 241 | |
| 2025/09/13 12:49:54 - mmengine - INFO - The number of instances per category in the dataset: | |
| +----------+--------+ | |
| | category | number | | |
| +----------+--------+ | |
| | door | 3222 | | |
| | window | 1650 | | |
| +----------+--------+ | |
| 2025/09/13 12:49:54 - mmengine - WARNING - The prefix is not set in metric class IndoorLayoutMetric_. | |
| Name of parameter - Initialization information | |
| backbone.conv1.kernel - torch.Size([27, 3, 64]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.norm1.bn.weight - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.norm1.bn.bias - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer1.0.conv1.kernel - torch.Size([27, 64, 64]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer1.0.norm1.bn.weight - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer1.0.norm1.bn.bias - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer1.0.conv2.kernel - torch.Size([27, 64, 64]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer1.0.norm2.bn.weight - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer1.0.norm2.bn.bias - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer1.0.downsample.0.kernel - torch.Size([1, 64, 64]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer1.0.downsample.1.bn.weight - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer1.0.downsample.1.bn.bias - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer1.1.conv1.kernel - torch.Size([27, 64, 64]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer1.1.norm1.bn.weight - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer1.1.norm1.bn.bias - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer1.1.conv2.kernel - torch.Size([27, 64, 64]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer1.1.norm2.bn.weight - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer1.1.norm2.bn.bias - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer1.2.conv1.kernel - torch.Size([27, 64, 64]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer1.2.norm1.bn.weight - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer1.2.norm1.bn.bias - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer1.2.conv2.kernel - torch.Size([27, 64, 64]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer1.2.norm2.bn.weight - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer1.2.norm2.bn.bias - torch.Size([64]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.0.conv1.kernel - torch.Size([27, 64, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer2.0.norm1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.0.norm1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.0.conv2.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer2.0.norm2.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.0.norm2.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.0.downsample.0.kernel - torch.Size([1, 64, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer2.0.downsample.1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.0.downsample.1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.1.conv1.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer2.1.norm1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.1.norm1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.1.conv2.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer2.1.norm2.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.1.norm2.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.2.conv1.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer2.2.norm1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.2.norm1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.2.conv2.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer2.2.norm2.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.2.norm2.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.3.conv1.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer2.3.norm1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.3.norm1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.3.conv2.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer2.3.norm2.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer2.3.norm2.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.0.conv1.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer3.0.norm1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.0.norm1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.0.conv2.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer3.0.norm2.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.0.norm2.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.0.downsample.0.kernel - torch.Size([1, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer3.0.downsample.1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.0.downsample.1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.1.conv1.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer3.1.norm1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.1.norm1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.1.conv2.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer3.1.norm2.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.1.norm2.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.2.conv1.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer3.2.norm1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.2.norm1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.2.conv2.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer3.2.norm2.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.2.norm2.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.3.conv1.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer3.3.norm1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.3.norm1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.3.conv2.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer3.3.norm2.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.3.norm2.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.4.conv1.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer3.4.norm1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.4.norm1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.4.conv2.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer3.4.norm2.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.4.norm2.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.5.conv1.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer3.5.norm1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.5.norm1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.5.conv2.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer3.5.norm2.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer3.5.norm2.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer4.0.conv1.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer4.0.norm1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer4.0.norm1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer4.0.conv2.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer4.0.norm2.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer4.0.norm2.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer4.0.downsample.0.kernel - torch.Size([1, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer4.0.downsample.1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer4.0.downsample.1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer4.1.conv1.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer4.1.norm1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer4.1.norm1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer4.1.conv2.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer4.1.norm2.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer4.1.norm2.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer4.2.conv1.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer4.2.norm1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer4.2.norm1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer4.2.conv2.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DMinkResNet | |
| backbone.layer4.2.norm2.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| backbone.layer4.2.norm2.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| neck.lateral_block_0.0.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DNeck | |
| neck.lateral_block_0.1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| neck.lateral_block_0.1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| neck.out_block_0.0.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DNeck | |
| neck.out_block_0.1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| neck.out_block_0.1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| neck.up_block_1.0.kernel - torch.Size([27, 128, 128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| neck.up_block_1.1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| neck.up_block_1.1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| neck.lateral_block_1.0.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DNeck | |
| neck.lateral_block_1.1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| neck.lateral_block_1.1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| neck.out_block_1.0.kernel - torch.Size([27, 128, 128]): | |
| Initialized by user-defined `init_weights` in TR3DNeck | |
| neck.out_block_1.1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| neck.out_block_1.1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| neck.up_block_2.0.kernel - torch.Size([27, 128, 128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| neck.up_block_2.1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| neck.up_block_2.1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.conv_reg.kernel - torch.Size([128, 6]): | |
| Initialized by user-defined `init_weights` in TR3DHead | |
| bbox_head.conv_reg.bias - torch.Size([1, 6]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.conv_cls.kernel - torch.Size([128, 2]): | |
| Initialized by user-defined `init_weights` in TR3DHead | |
| bbox_head.conv_cls.bias - torch.Size([1, 2]): | |
| Initialized by user-defined `init_weights` in TR3DHead | |
| bbox_head.layout_head.add_feats_encoder.0.weight - torch.Size([32, 10]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.add_feats_encoder.0.bias - torch.Size([32]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.add_feats_encoder.2.weight - torch.Size([32, 32]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.add_feats_encoder.2.bias - torch.Size([32]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.add_feats_encoder.4.weight - torch.Size([32, 32]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.add_feats_encoder.4.bias - torch.Size([32]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.add_feats_encoder.5.weight - torch.Size([32]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.add_feats_encoder.5.bias - torch.Size([32]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.out_reg_conv.0.kernel - torch.Size([160, 160]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.out_reg_conv.0.bias - torch.Size([1, 160]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.out_reg_conv.2.kernel - torch.Size([160, 5]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.out_reg_conv.2.bias - torch.Size([1, 5]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.out_cls_conv.kernel - torch.Size([128, 1]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.out_cls_conv.bias - torch.Size([1, 1]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.conv_blocks.0.0.kernel - torch.Size([9, 128, 128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.conv_blocks.0.1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.conv_blocks.0.1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.conv_blocks.1.0.kernel - torch.Size([9, 128, 128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.conv_blocks.1.1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.conv_blocks.1.1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.conv_blocks.2.0.kernel - torch.Size([9, 128, 128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.conv_blocks.2.1.bn.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.conv_blocks.2.1.bn.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.z_fusion_block.0.weight - torch.Size([128, 1]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.z_fusion_block.0.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.z_fusion_block.2.weight - torch.Size([128, 128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.z_fusion_block.2.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.z_fusion_block.4.weight - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| bbox_head.layout_head.z_fusion_block.4.bias - torch.Size([128]): | |
| The value is the same before and after calling `init_weights` of MinkSingleStage3DDetector | |
| 2025/09/13 12:49:54 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io | |
| 2025/09/13 12:49:54 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. | |
| 2025/09/13 12:49:54 - mmengine - INFO - Checkpoints will be saved to /home/jovyan/users/koodiazhnyi/msu-masters/tr3d/work_dirs/tr3d_1xb16_structured3d_v51. | |
| 2025/09/13 12:52:35 - mmengine - INFO - Epoch(train) [1][ 50/1099] lr: 1.0000e-03 eta: 11:45:55 time: 3.2239 data_time: 0.2323 memory: 29192 grad_norm: 9.3184 loss: 2.1326 bbox_loss: 0.5978 cls_loss: 0.5300 layout_loss: 0.8683 cls_layout_loss: 0.1365 | |
| 2025/09/13 12:55:11 - mmengine - INFO - Epoch(train) [1][ 100/1099] lr: 1.0000e-03 eta: 11:30:48 time: 3.1100 data_time: 0.1371 memory: 25749 grad_norm: 15.4519 loss: 1.7446 bbox_loss: 0.5438 cls_loss: 0.3832 layout_loss: 0.7605 cls_layout_loss: 0.0571 | |
| 2025/09/13 12:57:50 - mmengine - INFO - Epoch(train) [1][ 150/1099] lr: 1.0000e-03 eta: 11:29:31 time: 3.1856 data_time: 0.1648 memory: 33202 grad_norm: 18.9536 loss: 1.6705 bbox_loss: 0.5309 cls_loss: 0.3413 layout_loss: 0.7430 cls_layout_loss: 0.0553 | |
| 2025/09/13 13:00:23 - mmengine - INFO - Epoch(train) [1][ 200/1099] lr: 1.0000e-03 eta: 11:21:18 time: 3.0702 data_time: 0.1491 memory: 25550 grad_norm: 15.8186 loss: 1.4874 bbox_loss: 0.4973 cls_loss: 0.3163 layout_loss: 0.6197 cls_layout_loss: 0.0541 | |
| 2025/09/13 13:02:59 - mmengine - INFO - Epoch(train) [1][ 250/1099] lr: 1.0000e-03 eta: 11:17:23 time: 3.1173 data_time: 0.1603 memory: 26623 grad_norm: 20.0858 loss: 1.3611 bbox_loss: 0.4896 cls_loss: 0.2907 layout_loss: 0.5309 cls_layout_loss: 0.0500 | |
| 2025/09/13 13:05:36 - mmengine - INFO - Epoch(train) [1][ 300/1099] lr: 1.0000e-03 eta: 11:14:16 time: 3.1277 data_time: 0.1312 memory: 33776 grad_norm: 19.0561 loss: 1.2665 bbox_loss: 0.4688 cls_loss: 0.2689 layout_loss: 0.4811 cls_layout_loss: 0.0478 | |
| 2025/09/13 13:08:13 - mmengine - INFO - Epoch(train) [1][ 350/1099] lr: 1.0000e-03 eta: 11:11:47 time: 3.1433 data_time: 0.1621 memory: 26211 grad_norm: 19.2816 loss: 1.1945 bbox_loss: 0.4614 cls_loss: 0.2559 layout_loss: 0.4328 cls_layout_loss: 0.0444 | |
| 2025/09/13 13:10:49 - mmengine - INFO - Epoch(train) [1][ 400/1099] lr: 1.0000e-03 eta: 11:08:48 time: 3.1261 data_time: 0.1578 memory: 26777 grad_norm: 19.2562 loss: 1.1358 bbox_loss: 0.4483 cls_loss: 0.2493 layout_loss: 0.3962 cls_layout_loss: 0.0420 | |
| 2025/09/13 13:13:31 - mmengine - INFO - Epoch(train) [1][ 450/1099] lr: 1.0000e-03 eta: 11:08:21 time: 3.2296 data_time: 0.2030 memory: 26155 grad_norm: 18.7840 loss: 1.1183 bbox_loss: 0.4369 cls_loss: 0.2409 layout_loss: 0.3982 cls_layout_loss: 0.0422 | |
| 2025/09/13 13:16:11 - mmengine - INFO - Epoch(train) [1][ 500/1099] lr: 1.0000e-03 eta: 11:06:51 time: 3.2012 data_time: 0.1603 memory: 27328 grad_norm: 19.6828 loss: 1.1131 bbox_loss: 0.4297 cls_loss: 0.2427 layout_loss: 0.4005 cls_layout_loss: 0.0402 | |
| 2025/09/13 13:18:51 - mmengine - INFO - Epoch(train) [1][ 550/1099] lr: 1.0000e-03 eta: 11:05:14 time: 3.2064 data_time: 0.1487 memory: 27534 grad_norm: 19.9812 loss: 1.0364 bbox_loss: 0.4195 cls_loss: 0.2184 layout_loss: 0.3604 cls_layout_loss: 0.0381 | |
| 2025/09/13 13:21:29 - mmengine - INFO - Epoch(train) [1][ 600/1099] lr: 1.0000e-03 eta: 11:02:39 time: 3.1613 data_time: 0.1485 memory: 26207 grad_norm: 18.4832 loss: 1.0224 bbox_loss: 0.4161 cls_loss: 0.2210 layout_loss: 0.3486 cls_layout_loss: 0.0367 | |
| 2025/09/13 13:24:12 - mmengine - INFO - Epoch(train) [1][ 650/1099] lr: 1.0000e-03 eta: 11:01:36 time: 3.2564 data_time: 0.1599 memory: 25803 grad_norm: 18.2279 loss: 0.9966 bbox_loss: 0.4021 cls_loss: 0.2140 layout_loss: 0.3434 cls_layout_loss: 0.0370 | |
| 2025/09/13 13:26:49 - mmengine - INFO - Epoch(train) [1][ 700/1099] lr: 1.0000e-03 eta: 10:58:32 time: 3.1376 data_time: 0.1412 memory: 25730 grad_norm: 20.4529 loss: 0.9695 bbox_loss: 0.4025 cls_loss: 0.2067 layout_loss: 0.3257 cls_layout_loss: 0.0346 | |
| 2025/09/13 13:29:28 - mmengine - INFO - Epoch(train) [1][ 750/1099] lr: 1.0000e-03 eta: 10:56:19 time: 3.1941 data_time: 0.1504 memory: 33947 grad_norm: 16.7543 loss: 1.0094 bbox_loss: 0.4000 cls_loss: 0.2111 layout_loss: 0.3589 cls_layout_loss: 0.0395 | |
| 2025/09/13 13:32:07 - mmengine - INFO - Epoch(train) [1][ 800/1099] lr: 1.0000e-03 eta: 10:53:53 time: 3.1819 data_time: 0.1517 memory: 29815 grad_norm: 20.2903 loss: 0.9732 bbox_loss: 0.4027 cls_loss: 0.2052 layout_loss: 0.3304 cls_layout_loss: 0.0350 | |
| 2025/09/13 13:34:44 - mmengine - INFO - Epoch(train) [1][ 850/1099] lr: 1.0000e-03 eta: 10:50:48 time: 3.1307 data_time: 0.1542 memory: 24681 grad_norm: 18.9074 loss: 0.9553 bbox_loss: 0.3920 cls_loss: 0.2032 layout_loss: 0.3258 cls_layout_loss: 0.0343 | |
| 2025/09/13 13:37:27 - mmengine - INFO - Epoch(train) [1][ 900/1099] lr: 1.0000e-03 eta: 10:49:07 time: 3.2491 data_time: 0.1810 memory: 26765 grad_norm: 11.3360 loss: 0.9649 bbox_loss: 0.3858 cls_loss: 0.2045 layout_loss: 0.3392 cls_layout_loss: 0.0355 | |
| 2025/09/13 13:40:09 - mmengine - INFO - Epoch(train) [1][ 950/1099] lr: 1.0000e-03 eta: 10:47:22 time: 3.2527 data_time: 0.1839 memory: 34914 grad_norm: 21.0052 loss: 0.9846 bbox_loss: 0.4026 cls_loss: 0.2004 layout_loss: 0.3468 cls_layout_loss: 0.0347 | |
| 2025/09/13 13:42:44 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 13:42:44 - mmengine - INFO - Epoch(train) [1][1000/1099] lr: 1.0000e-03 eta: 10:43:58 time: 3.0989 data_time: 0.1791 memory: 26806 grad_norm: 23.3966 loss: 0.9196 bbox_loss: 0.3985 cls_loss: 0.1904 layout_loss: 0.2984 cls_layout_loss: 0.0324 | |
| 2025/09/13 13:45:24 - mmengine - INFO - Epoch(train) [1][1050/1099] lr: 1.0000e-03 eta: 10:41:37 time: 3.2015 data_time: 0.1768 memory: 25043 grad_norm: 15.5485 loss: 0.9071 bbox_loss: 0.3754 cls_loss: 0.1936 layout_loss: 0.3057 cls_layout_loss: 0.0323 | |
| 2025/09/13 13:47:58 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 13:47:58 - mmengine - INFO - Saving checkpoint at 1 epochs | |
| 2025/09/13 13:48:40 - mmengine - INFO - Epoch(val) [1][ 50/241] eta: 0:02:39 time: 0.8371 data_time: 0.0977 memory: 26286 | |
| 2025/09/13 13:49:17 - mmengine - INFO - Epoch(val) [1][100/241] eta: 0:01:50 time: 0.7241 data_time: 0.0770 memory: 1369 | |
| 2025/09/13 13:49:58 - mmengine - INFO - Epoch(val) [1][150/241] eta: 0:01:12 time: 0.8324 data_time: 0.0807 memory: 1230 | |
| 2025/09/13 13:50:37 - mmengine - INFO - Epoch(val) [1][200/241] eta: 0:00:32 time: 0.7671 data_time: 0.0830 memory: 1081 | |
| 2025/09/13 13:52:14 - mmengine - INFO - | |
| +---------+-------------+-------------+ | |
| | Layouts | F1 @.25 IoU | F1 @.50 IoU | | |
| +---------+-------------+-------------+ | |
| | wall | 0.8017 | 0.7587 | | |
| | door | 0.8517 | 0.8432 | | |
| | window | 0.7778 | 0.7628 | | |
| +---------+-------------+-------------+ | |
| | Overall | 0.8104 | 0.7882 | | |
| +---------+-------------+-------------+ | |
| 2025/09/13 13:52:14 - mmengine - INFO - Epoch(val) [1][241/241] structured3d: {'layout': {'wall_f1_25': 0.8016858904256758, 'wall_f1_50': 0.8016858904256758, 'door_f1_25': 0.8517388530806652, 'door_f1_50': 0.8517388530806652, 'window_f1_25': 0.7778354591812932, 'window_f1_50': 0.7778354591812932, 'f1_25': 0.8104200675625447, 'f1_50': 0.7882330456312149}} data_time: 0.0836 time: 0.8073 | |
| 2025/09/13 13:54:52 - mmengine - INFO - Epoch(train) [2][ 50/1099] lr: 1.0000e-03 eta: 10:36:04 time: 3.1713 data_time: 0.2631 memory: 27430 grad_norm: 14.9634 loss: 0.8698 bbox_loss: 0.3701 cls_loss: 0.1816 layout_loss: 0.2868 cls_layout_loss: 0.0314 | |
| 2025/09/13 13:57:33 - mmengine - INFO - Epoch(train) [2][ 100/1099] lr: 1.0000e-03 eta: 10:33:51 time: 3.2202 data_time: 0.2075 memory: 26628 grad_norm: 15.2659 loss: 0.8886 bbox_loss: 0.3743 cls_loss: 0.1843 layout_loss: 0.2982 cls_layout_loss: 0.0318 | |
| 2025/09/13 14:00:16 - mmengine - INFO - Epoch(train) [2][ 150/1099] lr: 1.0000e-03 eta: 10:31:47 time: 3.2444 data_time: 0.1800 memory: 29871 grad_norm: 14.6373 loss: 0.8841 bbox_loss: 0.3695 cls_loss: 0.1853 layout_loss: 0.2980 cls_layout_loss: 0.0313 | |
| 2025/09/13 14:02:50 - mmengine - INFO - Epoch(train) [2][ 200/1099] lr: 1.0000e-03 eta: 10:28:31 time: 3.0954 data_time: 0.1357 memory: 27881 grad_norm: 14.6564 loss: 0.8575 bbox_loss: 0.3690 cls_loss: 0.1829 layout_loss: 0.2756 cls_layout_loss: 0.0300 | |
| 2025/09/13 14:05:26 - mmengine - INFO - Epoch(train) [2][ 250/1099] lr: 1.0000e-03 eta: 10:25:31 time: 3.1230 data_time: 0.1686 memory: 26169 grad_norm: 13.0837 loss: 0.8534 bbox_loss: 0.3583 cls_loss: 0.1757 layout_loss: 0.2891 cls_layout_loss: 0.0303 | |
| 2025/09/13 14:08:03 - mmengine - INFO - Epoch(train) [2][ 300/1099] lr: 1.0000e-03 eta: 10:22:38 time: 3.1348 data_time: 0.1507 memory: 36044 grad_norm: 13.7084 loss: 0.8719 bbox_loss: 0.3631 cls_loss: 0.1849 layout_loss: 0.2933 cls_layout_loss: 0.0307 | |
| 2025/09/13 14:10:42 - mmengine - INFO - Epoch(train) [2][ 350/1099] lr: 1.0000e-03 eta: 10:20:01 time: 3.1719 data_time: 0.1567 memory: 29802 grad_norm: 15.5127 loss: 0.8344 bbox_loss: 0.3590 cls_loss: 0.1715 layout_loss: 0.2741 cls_layout_loss: 0.0298 | |
| 2025/09/13 14:13:21 - mmengine - INFO - Epoch(train) [2][ 400/1099] lr: 1.0000e-03 eta: 10:17:30 time: 3.1884 data_time: 0.1578 memory: 27716 grad_norm: 11.3239 loss: 0.8369 bbox_loss: 0.3557 cls_loss: 0.1737 layout_loss: 0.2775 cls_layout_loss: 0.0300 | |
| 2025/09/13 14:15:57 - mmengine - INFO - Epoch(train) [2][ 450/1099] lr: 1.0000e-03 eta: 10:14:30 time: 3.1131 data_time: 0.1652 memory: 27806 grad_norm: 14.1903 loss: 0.8433 bbox_loss: 0.3578 cls_loss: 0.1774 layout_loss: 0.2781 cls_layout_loss: 0.0300 | |
| 2025/09/13 14:18:33 - mmengine - INFO - Epoch(train) [2][ 500/1099] lr: 1.0000e-03 eta: 10:11:38 time: 3.1302 data_time: 0.1939 memory: 26894 grad_norm: 19.3871 loss: 0.8109 bbox_loss: 0.3612 cls_loss: 0.1641 layout_loss: 0.2572 cls_layout_loss: 0.0284 | |
| 2025/09/13 14:21:10 - mmengine - INFO - Epoch(train) [2][ 550/1099] lr: 1.0000e-03 eta: 10:08:45 time: 3.1238 data_time: 0.1662 memory: 25521 grad_norm: 11.0723 loss: 0.8446 bbox_loss: 0.3597 cls_loss: 0.1807 layout_loss: 0.2750 cls_layout_loss: 0.0293 | |
| 2025/09/13 14:23:50 - mmengine - INFO - Epoch(train) [2][ 600/1099] lr: 1.0000e-03 eta: 10:06:19 time: 3.2028 data_time: 0.1799 memory: 28920 grad_norm: 12.0865 loss: 0.8226 bbox_loss: 0.3504 cls_loss: 0.1727 layout_loss: 0.2707 cls_layout_loss: 0.0288 | |
| 2025/09/13 14:26:28 - mmengine - INFO - Epoch(train) [2][ 650/1099] lr: 1.0000e-03 eta: 10:03:40 time: 3.1630 data_time: 0.1884 memory: 29793 grad_norm: 15.8633 loss: 0.8167 bbox_loss: 0.3529 cls_loss: 0.1700 layout_loss: 0.2657 cls_layout_loss: 0.0281 | |
| 2025/09/13 14:29:04 - mmengine - INFO - Epoch(train) [2][ 700/1099] lr: 1.0000e-03 eta: 10:00:44 time: 3.1106 data_time: 0.1728 memory: 28310 grad_norm: 16.1020 loss: 0.7943 bbox_loss: 0.3510 cls_loss: 0.1640 layout_loss: 0.2521 cls_layout_loss: 0.0272 | |
| 2025/09/13 14:31:39 - mmengine - INFO - Epoch(train) [2][ 750/1099] lr: 1.0000e-03 eta: 9:57:48 time: 3.1070 data_time: 0.1481 memory: 29672 grad_norm: 13.2598 loss: 0.8128 bbox_loss: 0.3532 cls_loss: 0.1714 layout_loss: 0.2596 cls_layout_loss: 0.0286 | |
| 2025/09/13 14:34:16 - mmengine - INFO - Epoch(train) [2][ 800/1099] lr: 1.0000e-03 eta: 9:55:02 time: 3.1391 data_time: 0.1515 memory: 27498 grad_norm: 12.3919 loss: 0.8170 bbox_loss: 0.3489 cls_loss: 0.1673 layout_loss: 0.2720 cls_layout_loss: 0.0287 | |
| 2025/09/13 14:36:51 - mmengine - INFO - Epoch(train) [2][ 850/1099] lr: 1.0000e-03 eta: 9:52:09 time: 3.1091 data_time: 0.1592 memory: 31462 grad_norm: 12.3094 loss: 0.8003 bbox_loss: 0.3430 cls_loss: 0.1702 layout_loss: 0.2595 cls_layout_loss: 0.0277 | |
| 2025/09/13 14:39:27 - mmengine - INFO - Epoch(train) [2][ 900/1099] lr: 1.0000e-03 eta: 9:49:21 time: 3.1255 data_time: 0.1652 memory: 29827 grad_norm: 12.8247 loss: 0.8095 bbox_loss: 0.3466 cls_loss: 0.1673 layout_loss: 0.2673 cls_layout_loss: 0.0284 | |
| 2025/09/13 14:39:30 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 14:42:08 - mmengine - INFO - Epoch(train) [2][ 950/1099] lr: 1.0000e-03 eta: 9:46:57 time: 3.2118 data_time: 0.1558 memory: 27809 grad_norm: 10.9599 loss: 0.7900 bbox_loss: 0.3386 cls_loss: 0.1648 layout_loss: 0.2591 cls_layout_loss: 0.0274 | |
| 2025/09/13 14:44:52 - mmengine - INFO - Epoch(train) [2][1000/1099] lr: 1.0000e-03 eta: 9:44:47 time: 3.2703 data_time: 0.1554 memory: 33632 grad_norm: 12.4292 loss: 0.7835 bbox_loss: 0.3377 cls_loss: 0.1589 layout_loss: 0.2601 cls_layout_loss: 0.0268 | |
| 2025/09/13 14:47:29 - mmengine - INFO - Epoch(train) [2][1050/1099] lr: 1.0000e-03 eta: 9:42:04 time: 3.1453 data_time: 0.1923 memory: 27538 grad_norm: 12.3213 loss: 0.8025 bbox_loss: 0.3414 cls_loss: 0.1662 layout_loss: 0.2675 cls_layout_loss: 0.0274 | |
| 2025/09/13 14:49:59 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 14:49:59 - mmengine - INFO - Saving checkpoint at 2 epochs | |
| 2025/09/13 14:50:41 - mmengine - INFO - Epoch(val) [2][ 50/241] eta: 0:02:36 time: 0.8192 data_time: 0.0691 memory: 30380 | |
| 2025/09/13 14:51:15 - mmengine - INFO - Epoch(val) [2][100/241] eta: 0:01:44 time: 0.6686 data_time: 0.0978 memory: 1369 | |
| 2025/09/13 14:51:54 - mmengine - INFO - Epoch(val) [2][150/241] eta: 0:01:08 time: 0.7812 data_time: 0.0803 memory: 1230 | |
| 2025/09/13 14:52:31 - mmengine - INFO - Epoch(val) [2][200/241] eta: 0:00:30 time: 0.7529 data_time: 0.0986 memory: 1081 | |
| 2025/09/13 14:54:07 - mmengine - INFO - | |
| +---------+-------------+-------------+ | |
| | Layouts | F1 @.25 IoU | F1 @.50 IoU | | |
| +---------+-------------+-------------+ | |
| | wall | 0.8248 | 0.7920 | | |
| | door | 0.8874 | 0.8784 | | |
| | window | 0.8189 | 0.7978 | | |
| +---------+-------------+-------------+ | |
| | Overall | 0.8437 | 0.8227 | | |
| +---------+-------------+-------------+ | |
| 2025/09/13 14:54:07 - mmengine - INFO - Epoch(val) [2][241/241] structured3d: {'layout': {'wall_f1_25': 0.8247947830014796, 'wall_f1_50': 0.8247947830014796, 'door_f1_25': 0.8874413840752182, 'door_f1_50': 0.8874413840752182, 'window_f1_25': 0.8189078864986725, 'window_f1_50': 0.8189078864986725, 'f1_25': 0.8437146845251234, 'f1_50': 0.822717278745543}} data_time: 0.0825 time: 0.7659 | |
| 2025/09/13 14:56:51 - mmengine - INFO - Epoch(train) [3][ 50/1099] lr: 1.0000e-03 eta: 9:36:54 time: 3.2799 data_time: 0.2795 memory: 28956 grad_norm: 11.7121 loss: 0.7695 bbox_loss: 0.3386 cls_loss: 0.1563 layout_loss: 0.2478 cls_layout_loss: 0.0268 | |
| 2025/09/13 14:59:22 - mmengine - INFO - Epoch(train) [3][ 100/1099] lr: 1.0000e-03 eta: 9:33:44 time: 3.0284 data_time: 0.1268 memory: 27584 grad_norm: 10.4452 loss: 0.7595 bbox_loss: 0.3359 cls_loss: 0.1588 layout_loss: 0.2386 cls_layout_loss: 0.0262 | |
| 2025/09/13 15:01:59 - mmengine - INFO - Epoch(train) [3][ 150/1099] lr: 1.0000e-03 eta: 9:31:01 time: 3.1397 data_time: 0.1756 memory: 26712 grad_norm: 13.0512 loss: 0.7818 bbox_loss: 0.3360 cls_loss: 0.1650 layout_loss: 0.2542 cls_layout_loss: 0.0266 | |
| 2025/09/13 15:04:40 - mmengine - INFO - Epoch(train) [3][ 200/1099] lr: 1.0000e-03 eta: 9:28:36 time: 3.2173 data_time: 0.1589 memory: 32135 grad_norm: 10.5807 loss: 0.7753 bbox_loss: 0.3346 cls_loss: 0.1590 layout_loss: 0.2554 cls_layout_loss: 0.0263 | |
| 2025/09/13 15:07:25 - mmengine - INFO - Epoch(train) [3][ 250/1099] lr: 1.0000e-03 eta: 9:26:26 time: 3.2900 data_time: 0.1776 memory: 26889 grad_norm: 14.1275 loss: 0.7560 bbox_loss: 0.3371 cls_loss: 0.1545 layout_loss: 0.2385 cls_layout_loss: 0.0259 | |
| 2025/09/13 15:10:06 - mmengine - INFO - Epoch(train) [3][ 300/1099] lr: 1.0000e-03 eta: 9:24:03 time: 3.2359 data_time: 0.1563 memory: 33934 grad_norm: 10.0496 loss: 0.7705 bbox_loss: 0.3322 cls_loss: 0.1541 layout_loss: 0.2578 cls_layout_loss: 0.0264 | |
| 2025/09/13 15:12:50 - mmengine - INFO - Epoch(train) [3][ 350/1099] lr: 1.0000e-03 eta: 9:21:46 time: 3.2683 data_time: 0.1900 memory: 32598 grad_norm: 12.4778 loss: 0.7493 bbox_loss: 0.3330 cls_loss: 0.1532 layout_loss: 0.2373 cls_layout_loss: 0.0258 | |
| 2025/09/13 15:15:34 - mmengine - INFO - Epoch(train) [3][ 400/1099] lr: 1.0000e-03 eta: 9:19:30 time: 3.2779 data_time: 0.1770 memory: 28900 grad_norm: 11.5219 loss: 0.7444 bbox_loss: 0.3280 cls_loss: 0.1495 layout_loss: 0.2417 cls_layout_loss: 0.0251 | |
| 2025/09/13 15:18:15 - mmengine - INFO - Epoch(train) [3][ 450/1099] lr: 1.0000e-03 eta: 9:17:03 time: 3.2284 data_time: 0.1766 memory: 27066 grad_norm: 11.6814 loss: 0.7328 bbox_loss: 0.3309 cls_loss: 0.1511 layout_loss: 0.2258 cls_layout_loss: 0.0251 | |
| 2025/09/13 15:20:57 - mmengine - INFO - Epoch(train) [3][ 500/1099] lr: 1.0000e-03 eta: 9:14:37 time: 3.2347 data_time: 0.1524 memory: 28346 grad_norm: 10.5252 loss: 0.7590 bbox_loss: 0.3306 cls_loss: 0.1532 layout_loss: 0.2496 cls_layout_loss: 0.0257 | |
| 2025/09/13 15:23:38 - mmengine - INFO - Epoch(train) [3][ 550/1099] lr: 1.0000e-03 eta: 9:12:05 time: 3.2080 data_time: 0.1527 memory: 26013 grad_norm: 13.2540 loss: 0.7418 bbox_loss: 0.3282 cls_loss: 0.1484 layout_loss: 0.2399 cls_layout_loss: 0.0253 | |
| 2025/09/13 15:26:19 - mmengine - INFO - Epoch(train) [3][ 600/1099] lr: 1.0000e-03 eta: 9:09:38 time: 3.2338 data_time: 0.1815 memory: 28684 grad_norm: 9.1707 loss: 0.7516 bbox_loss: 0.3228 cls_loss: 0.1479 layout_loss: 0.2554 cls_layout_loss: 0.0254 | |
| 2025/09/13 15:28:54 - mmengine - INFO - Epoch(train) [3][ 650/1099] lr: 1.0000e-03 eta: 9:06:46 time: 3.1058 data_time: 0.1322 memory: 27856 grad_norm: 9.9702 loss: 0.7387 bbox_loss: 0.3219 cls_loss: 0.1503 layout_loss: 0.2415 cls_layout_loss: 0.0250 | |
| 2025/09/13 15:31:35 - mmengine - INFO - Epoch(train) [3][ 700/1099] lr: 1.0000e-03 eta: 9:04:13 time: 3.2016 data_time: 0.1474 memory: 28139 grad_norm: 10.1922 loss: 0.7315 bbox_loss: 0.3256 cls_loss: 0.1497 layout_loss: 0.2314 cls_layout_loss: 0.0247 | |
| 2025/09/13 15:34:21 - mmengine - INFO - Epoch(train) [3][ 750/1099] lr: 1.0000e-03 eta: 9:02:01 time: 3.3271 data_time: 0.1509 memory: 30625 grad_norm: 10.4234 loss: 0.7564 bbox_loss: 0.3303 cls_loss: 0.1564 layout_loss: 0.2442 cls_layout_loss: 0.0255 | |
| 2025/09/13 15:36:57 - mmengine - INFO - Epoch(train) [3][ 800/1099] lr: 1.0000e-03 eta: 8:59:12 time: 3.1167 data_time: 0.1500 memory: 26731 grad_norm: 10.6396 loss: 0.7178 bbox_loss: 0.3241 cls_loss: 0.1464 layout_loss: 0.2231 cls_layout_loss: 0.0242 | |
| 2025/09/13 15:37:03 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 15:39:35 - mmengine - INFO - Epoch(train) [3][ 850/1099] lr: 1.0000e-03 eta: 8:56:30 time: 3.1566 data_time: 0.1816 memory: 26593 grad_norm: 10.3285 loss: 0.7261 bbox_loss: 0.3247 cls_loss: 0.1479 layout_loss: 0.2291 cls_layout_loss: 0.0244 | |
| 2025/09/13 15:42:18 - mmengine - INFO - Epoch(train) [3][ 900/1099] lr: 1.0000e-03 eta: 8:54:07 time: 3.2687 data_time: 0.1844 memory: 35031 grad_norm: 9.5217 loss: 0.7382 bbox_loss: 0.3208 cls_loss: 0.1503 layout_loss: 0.2421 cls_layout_loss: 0.0250 | |
| 2025/09/13 15:44:55 - mmengine - INFO - Epoch(train) [3][ 950/1099] lr: 1.0000e-03 eta: 8:51:23 time: 3.1429 data_time: 0.1447 memory: 26394 grad_norm: 9.9423 loss: 0.7300 bbox_loss: 0.3237 cls_loss: 0.1547 layout_loss: 0.2266 cls_layout_loss: 0.0250 | |
| 2025/09/13 15:47:32 - mmengine - INFO - Epoch(train) [3][1000/1099] lr: 1.0000e-03 eta: 8:48:37 time: 3.1335 data_time: 0.1487 memory: 27577 grad_norm: 8.3437 loss: 0.7152 bbox_loss: 0.3217 cls_loss: 0.1460 layout_loss: 0.2229 cls_layout_loss: 0.0245 | |
| 2025/09/13 15:50:12 - mmengine - INFO - Epoch(train) [3][1050/1099] lr: 1.0000e-03 eta: 8:46:03 time: 3.2035 data_time: 0.1223 memory: 31434 grad_norm: 9.6703 loss: 0.7159 bbox_loss: 0.3214 cls_loss: 0.1465 layout_loss: 0.2235 cls_layout_loss: 0.0244 | |
| 2025/09/13 15:52:47 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 15:52:47 - mmengine - INFO - Saving checkpoint at 3 epochs | |
| 2025/09/13 15:53:30 - mmengine - INFO - Epoch(val) [3][ 50/241] eta: 0:02:38 time: 0.8314 data_time: 0.0641 memory: 26593 | |
| 2025/09/13 15:54:03 - mmengine - INFO - Epoch(val) [3][100/241] eta: 0:01:45 time: 0.6714 data_time: 0.0290 memory: 1369 | |
| 2025/09/13 15:54:43 - mmengine - INFO - Epoch(val) [3][150/241] eta: 0:01:09 time: 0.7897 data_time: 0.0406 memory: 1230 | |
| 2025/09/13 15:55:20 - mmengine - INFO - Epoch(val) [3][200/241] eta: 0:00:31 time: 0.7424 data_time: 0.0663 memory: 1081 | |
| 2025/09/13 15:56:54 - mmengine - INFO - | |
| +---------+-------------+-------------+ | |
| | Layouts | F1 @.25 IoU | F1 @.50 IoU | | |
| +---------+-------------+-------------+ | |
| | wall | 0.8370 | 0.8085 | | |
| | door | 0.9082 | 0.9032 | | |
| | window | 0.8277 | 0.8134 | | |
| +---------+-------------+-------------+ | |
| | Overall | 0.8577 | 0.8417 | | |
| +---------+-------------+-------------+ | |
| 2025/09/13 15:56:54 - mmengine - INFO - Epoch(val) [3][241/241] structured3d: {'layout': {'wall_f1_25': 0.8370050194970318, 'wall_f1_50': 0.8370050194970318, 'door_f1_25': 0.9082381395668033, 'door_f1_50': 0.9082381395668033, 'window_f1_25': 0.8277157733439822, 'window_f1_50': 0.8277157733439822, 'f1_25': 0.8576529774692725, 'f1_50': 0.8416883973680691}} data_time: 0.0543 time: 0.7698 | |
| 2025/09/13 15:59:31 - mmengine - INFO - Epoch(train) [4][ 50/1099] lr: 1.0000e-03 eta: 8:40:40 time: 3.1362 data_time: 0.2099 memory: 29074 grad_norm: 9.3336 loss: 0.6909 bbox_loss: 0.3163 cls_loss: 0.1391 layout_loss: 0.2115 cls_layout_loss: 0.0240 | |
| 2025/09/13 16:02:15 - mmengine - INFO - Epoch(train) [4][ 100/1099] lr: 1.0000e-03 eta: 8:38:15 time: 3.2748 data_time: 0.1616 memory: 26766 grad_norm: 9.9993 loss: 0.7084 bbox_loss: 0.3174 cls_loss: 0.1413 layout_loss: 0.2259 cls_layout_loss: 0.0238 | |
| 2025/09/13 16:04:54 - mmengine - INFO - Epoch(train) [4][ 150/1099] lr: 1.0000e-03 eta: 8:35:36 time: 3.1735 data_time: 0.1549 memory: 27890 grad_norm: 10.1389 loss: 0.7295 bbox_loss: 0.3207 cls_loss: 0.1490 layout_loss: 0.2355 cls_layout_loss: 0.0243 | |
| 2025/09/13 16:07:35 - mmengine - INFO - Epoch(train) [4][ 200/1099] lr: 1.0000e-03 eta: 8:33:04 time: 3.2268 data_time: 0.1609 memory: 32135 grad_norm: 9.1830 loss: 0.7270 bbox_loss: 0.3197 cls_loss: 0.1489 layout_loss: 0.2338 cls_layout_loss: 0.0245 | |
| 2025/09/13 16:10:16 - mmengine - INFO - Epoch(train) [4][ 250/1099] lr: 1.0000e-03 eta: 8:30:31 time: 3.2171 data_time: 0.1554 memory: 29855 grad_norm: 10.5340 loss: 0.6820 bbox_loss: 0.3151 cls_loss: 0.1387 layout_loss: 0.2046 cls_layout_loss: 0.0237 | |
| 2025/09/13 16:12:55 - mmengine - INFO - Epoch(train) [4][ 300/1099] lr: 1.0000e-03 eta: 8:27:53 time: 3.1812 data_time: 0.1656 memory: 30636 grad_norm: 9.8181 loss: 0.7085 bbox_loss: 0.3171 cls_loss: 0.1413 layout_loss: 0.2266 cls_layout_loss: 0.0234 | |
| 2025/09/13 16:15:37 - mmengine - INFO - Epoch(train) [4][ 350/1099] lr: 1.0000e-03 eta: 8:25:21 time: 3.2327 data_time: 0.1937 memory: 33110 grad_norm: 7.7999 loss: 0.6953 bbox_loss: 0.3126 cls_loss: 0.1402 layout_loss: 0.2193 cls_layout_loss: 0.0232 | |
| 2025/09/13 16:18:21 - mmengine - INFO - Epoch(train) [4][ 400/1099] lr: 1.0000e-03 eta: 8:22:56 time: 3.2832 data_time: 0.1922 memory: 30274 grad_norm: 9.0177 loss: 0.7247 bbox_loss: 0.3146 cls_loss: 0.1490 layout_loss: 0.2364 cls_layout_loss: 0.0246 | |
| 2025/09/13 16:21:00 - mmengine - INFO - Epoch(train) [4][ 450/1099] lr: 1.0000e-03 eta: 8:20:17 time: 3.1855 data_time: 0.1525 memory: 27957 grad_norm: 9.4082 loss: 0.6876 bbox_loss: 0.3121 cls_loss: 0.1373 layout_loss: 0.2145 cls_layout_loss: 0.0237 | |
| 2025/09/13 16:23:43 - mmengine - INFO - Epoch(train) [4][ 500/1099] lr: 1.0000e-03 eta: 8:17:49 time: 3.2632 data_time: 0.2048 memory: 26878 grad_norm: 8.7611 loss: 0.6969 bbox_loss: 0.3157 cls_loss: 0.1419 layout_loss: 0.2162 cls_layout_loss: 0.0230 | |
| 2025/09/13 16:26:22 - mmengine - INFO - Epoch(train) [4][ 550/1099] lr: 1.0000e-03 eta: 8:15:09 time: 3.1764 data_time: 0.1483 memory: 27969 grad_norm: 9.8938 loss: 0.6919 bbox_loss: 0.3155 cls_loss: 0.1370 layout_loss: 0.2163 cls_layout_loss: 0.0232 | |
| 2025/09/13 16:29:02 - mmengine - INFO - Epoch(train) [4][ 600/1099] lr: 1.0000e-03 eta: 8:12:33 time: 3.2016 data_time: 0.1669 memory: 28888 grad_norm: 8.2858 loss: 0.6939 bbox_loss: 0.3153 cls_loss: 0.1432 layout_loss: 0.2118 cls_layout_loss: 0.0236 | |
| 2025/09/13 16:31:41 - mmengine - INFO - Epoch(train) [4][ 650/1099] lr: 1.0000e-03 eta: 8:09:53 time: 3.1721 data_time: 0.1879 memory: 28203 grad_norm: 7.6550 loss: 0.7096 bbox_loss: 0.3141 cls_loss: 0.1416 layout_loss: 0.2302 cls_layout_loss: 0.0237 | |
| 2025/09/13 16:34:24 - mmengine - INFO - Epoch(train) [4][ 700/1099] lr: 1.0000e-03 eta: 8:07:23 time: 3.2646 data_time: 0.1651 memory: 31374 grad_norm: 8.7400 loss: 0.7197 bbox_loss: 0.3161 cls_loss: 0.1491 layout_loss: 0.2309 cls_layout_loss: 0.0236 | |
| 2025/09/13 16:34:34 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 16:37:02 - mmengine - INFO - Epoch(train) [4][ 750/1099] lr: 1.0000e-03 eta: 8:04:42 time: 3.1650 data_time: 0.1357 memory: 29845 grad_norm: 9.3675 loss: 0.6859 bbox_loss: 0.3109 cls_loss: 0.1402 layout_loss: 0.2115 cls_layout_loss: 0.0232 | |
| 2025/09/13 16:39:45 - mmengine - INFO - Epoch(train) [4][ 800/1099] lr: 1.0000e-03 eta: 8:02:11 time: 3.2529 data_time: 0.1659 memory: 28980 grad_norm: 8.5838 loss: 0.6686 bbox_loss: 0.3108 cls_loss: 0.1352 layout_loss: 0.2000 cls_layout_loss: 0.0226 | |
| 2025/09/13 16:42:20 - mmengine - INFO - Epoch(train) [4][ 850/1099] lr: 1.0000e-03 eta: 7:59:23 time: 3.1025 data_time: 0.1543 memory: 30674 grad_norm: 10.7037 loss: 0.7034 bbox_loss: 0.3157 cls_loss: 0.1449 layout_loss: 0.2192 cls_layout_loss: 0.0235 | |
| 2025/09/13 16:45:00 - mmengine - INFO - Epoch(train) [4][ 900/1099] lr: 1.0000e-03 eta: 7:56:46 time: 3.2009 data_time: 0.1726 memory: 27565 grad_norm: 8.5167 loss: 0.6827 bbox_loss: 0.3090 cls_loss: 0.1365 layout_loss: 0.2147 cls_layout_loss: 0.0225 | |
| 2025/09/13 16:47:41 - mmengine - INFO - Epoch(train) [4][ 950/1099] lr: 1.0000e-03 eta: 7:54:11 time: 3.2138 data_time: 0.1724 memory: 31564 grad_norm: 7.8274 loss: 0.6706 bbox_loss: 0.3102 cls_loss: 0.1360 layout_loss: 0.2016 cls_layout_loss: 0.0227 | |
| 2025/09/13 16:50:20 - mmengine - INFO - Epoch(train) [4][1000/1099] lr: 1.0000e-03 eta: 7:51:33 time: 3.1943 data_time: 0.1585 memory: 30819 grad_norm: 9.2864 loss: 0.6723 bbox_loss: 0.3080 cls_loss: 0.1342 layout_loss: 0.2074 cls_layout_loss: 0.0227 | |
| 2025/09/13 16:53:02 - mmengine - INFO - Epoch(train) [4][1050/1099] lr: 1.0000e-03 eta: 7:48:58 time: 3.2294 data_time: 0.1451 memory: 27379 grad_norm: 7.5440 loss: 0.6779 bbox_loss: 0.3095 cls_loss: 0.1398 layout_loss: 0.2060 cls_layout_loss: 0.0226 | |
| 2025/09/13 16:55:30 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 16:55:30 - mmengine - INFO - Saving checkpoint at 4 epochs | |
| 2025/09/13 16:56:12 - mmengine - INFO - Epoch(val) [4][ 50/241] eta: 0:02:36 time: 0.8195 data_time: 0.0591 memory: 28143 | |
| 2025/09/13 16:56:45 - mmengine - INFO - Epoch(val) [4][100/241] eta: 0:01:43 time: 0.6487 data_time: 0.0666 memory: 1369 | |
| 2025/09/13 16:57:23 - mmengine - INFO - Epoch(val) [4][150/241] eta: 0:01:07 time: 0.7617 data_time: 0.0559 memory: 1230 | |
| 2025/09/13 16:57:58 - mmengine - INFO - Epoch(val) [4][200/241] eta: 0:00:30 time: 0.7127 data_time: 0.0815 memory: 1081 | |
| 2025/09/13 16:59:34 - mmengine - INFO - | |
| +---------+-------------+-------------+ | |
| | Layouts | F1 @.25 IoU | F1 @.50 IoU | | |
| +---------+-------------+-------------+ | |
| | wall | 0.8520 | 0.8316 | | |
| | door | 0.9158 | 0.9113 | | |
| | window | 0.8513 | 0.8403 | | |
| +---------+-------------+-------------+ | |
| | Overall | 0.8731 | 0.8611 | | |
| +---------+-------------+-------------+ | |
| 2025/09/13 16:59:34 - mmengine - INFO - Epoch(val) [4][241/241] structured3d: {'layout': {'wall_f1_25': 0.8519955832524444, 'wall_f1_50': 0.8519955832524444, 'door_f1_25': 0.9158427468410787, 'door_f1_50': 0.9158427468410787, 'window_f1_25': 0.8513290629773265, 'window_f1_50': 0.8513290629773265, 'f1_25': 0.8730557976902832, 'f1_50': 0.8610649718667661}} data_time: 0.0661 time: 0.7538 | |
| 2025/09/13 17:02:21 - mmengine - INFO - Epoch(train) [5][ 50/1099] lr: 1.0000e-03 eta: 7:43:43 time: 3.3271 data_time: 0.2737 memory: 29676 grad_norm: 7.3469 loss: 0.6929 bbox_loss: 0.3072 cls_loss: 0.1426 layout_loss: 0.2205 cls_layout_loss: 0.0226 | |
| 2025/09/13 17:04:59 - mmengine - INFO - Epoch(train) [5][ 100/1099] lr: 1.0000e-03 eta: 7:41:03 time: 3.1789 data_time: 0.1746 memory: 27363 grad_norm: 8.1686 loss: 0.6643 bbox_loss: 0.3065 cls_loss: 0.1359 layout_loss: 0.1997 cls_layout_loss: 0.0222 | |
| 2025/09/13 17:07:42 - mmengine - INFO - Epoch(train) [5][ 150/1099] lr: 1.0000e-03 eta: 7:38:30 time: 3.2499 data_time: 0.1887 memory: 30927 grad_norm: 7.8508 loss: 0.6610 bbox_loss: 0.3041 cls_loss: 0.1314 layout_loss: 0.2032 cls_layout_loss: 0.0222 | |
| 2025/09/13 17:10:15 - mmengine - INFO - Epoch(train) [5][ 200/1099] lr: 1.0000e-03 eta: 7:35:40 time: 3.0687 data_time: 0.1590 memory: 23976 grad_norm: 8.3836 loss: 0.6539 bbox_loss: 0.3044 cls_loss: 0.1301 layout_loss: 0.1975 cls_layout_loss: 0.0219 | |
| 2025/09/13 17:12:51 - mmengine - INFO - Epoch(train) [5][ 250/1099] lr: 1.0000e-03 eta: 7:32:55 time: 3.1088 data_time: 0.1433 memory: 29848 grad_norm: 9.1917 loss: 0.6729 bbox_loss: 0.3115 cls_loss: 0.1362 layout_loss: 0.2026 cls_layout_loss: 0.0226 | |
| 2025/09/13 17:15:37 - mmengine - INFO - Epoch(train) [5][ 300/1099] lr: 1.0000e-03 eta: 7:30:30 time: 3.3378 data_time: 0.1744 memory: 26734 grad_norm: 7.3828 loss: 0.6577 bbox_loss: 0.3026 cls_loss: 0.1335 layout_loss: 0.1997 cls_layout_loss: 0.0219 | |
| 2025/09/13 17:18:13 - mmengine - INFO - Epoch(train) [5][ 350/1099] lr: 1.0000e-03 eta: 7:27:44 time: 3.1147 data_time: 0.1502 memory: 26392 grad_norm: 6.9180 loss: 0.6563 bbox_loss: 0.3018 cls_loss: 0.1335 layout_loss: 0.1989 cls_layout_loss: 0.0221 | |
| 2025/09/13 17:20:53 - mmengine - INFO - Epoch(train) [5][ 400/1099] lr: 1.0000e-03 eta: 7:25:06 time: 3.1940 data_time: 0.2013 memory: 29503 grad_norm: 8.7732 loss: 0.6650 bbox_loss: 0.3064 cls_loss: 0.1331 layout_loss: 0.2033 cls_layout_loss: 0.0221 | |
| 2025/09/13 17:23:36 - mmengine - INFO - Epoch(train) [5][ 450/1099] lr: 1.0000e-03 eta: 7:22:34 time: 3.2569 data_time: 0.1768 memory: 27665 grad_norm: 6.8143 loss: 0.6585 bbox_loss: 0.3026 cls_loss: 0.1346 layout_loss: 0.1988 cls_layout_loss: 0.0225 | |
| 2025/09/13 17:26:17 - mmengine - INFO - Epoch(train) [5][ 500/1099] lr: 1.0000e-03 eta: 7:19:58 time: 3.2300 data_time: 0.1867 memory: 30168 grad_norm: 7.8502 loss: 0.6783 bbox_loss: 0.3108 cls_loss: 0.1367 layout_loss: 0.2082 cls_layout_loss: 0.0226 | |
| 2025/09/13 17:29:00 - mmengine - INFO - Epoch(train) [5][ 550/1099] lr: 1.0000e-03 eta: 7:17:26 time: 3.2587 data_time: 0.1704 memory: 28526 grad_norm: 8.0814 loss: 0.6668 bbox_loss: 0.3012 cls_loss: 0.1360 layout_loss: 0.2075 cls_layout_loss: 0.0222 | |
| 2025/09/13 17:31:39 - mmengine - INFO - Epoch(train) [5][ 600/1099] lr: 1.0000e-03 eta: 7:14:45 time: 3.1679 data_time: 0.1683 memory: 27560 grad_norm: 8.2348 loss: 0.6531 bbox_loss: 0.3018 cls_loss: 0.1287 layout_loss: 0.2006 cls_layout_loss: 0.0220 | |
| 2025/09/13 17:31:51 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 17:34:20 - mmengine - INFO - Epoch(train) [5][ 650/1099] lr: 1.0000e-03 eta: 7:12:10 time: 3.2382 data_time: 0.1531 memory: 28162 grad_norm: 7.1332 loss: 0.6654 bbox_loss: 0.3038 cls_loss: 0.1336 layout_loss: 0.2058 cls_layout_loss: 0.0222 | |
| 2025/09/13 17:36:58 - mmengine - INFO - Epoch(train) [5][ 700/1099] lr: 1.0000e-03 eta: 7:09:28 time: 3.1538 data_time: 0.1663 memory: 33758 grad_norm: 8.2948 loss: 0.6556 bbox_loss: 0.3044 cls_loss: 0.1305 layout_loss: 0.1985 cls_layout_loss: 0.0223 | |
| 2025/09/13 17:39:40 - mmengine - INFO - Epoch(train) [5][ 750/1099] lr: 1.0000e-03 eta: 7:06:52 time: 3.2208 data_time: 0.1584 memory: 27618 grad_norm: 10.1578 loss: 0.6689 bbox_loss: 0.3094 cls_loss: 0.1324 layout_loss: 0.2046 cls_layout_loss: 0.0224 | |
| 2025/09/13 17:42:18 - mmengine - INFO - Epoch(train) [5][ 800/1099] lr: 1.0000e-03 eta: 7:04:12 time: 3.1761 data_time: 0.1560 memory: 26116 grad_norm: 8.3738 loss: 0.6292 bbox_loss: 0.2996 cls_loss: 0.1240 layout_loss: 0.1844 cls_layout_loss: 0.0211 | |
| 2025/09/13 17:44:58 - mmengine - INFO - Epoch(train) [5][ 850/1099] lr: 1.0000e-03 eta: 7:01:34 time: 3.1947 data_time: 0.1645 memory: 29065 grad_norm: 9.3925 loss: 0.6484 bbox_loss: 0.3024 cls_loss: 0.1278 layout_loss: 0.1965 cls_layout_loss: 0.0217 | |
| 2025/09/13 17:47:39 - mmengine - INFO - Epoch(train) [5][ 900/1099] lr: 1.0000e-03 eta: 6:58:57 time: 3.2257 data_time: 0.1710 memory: 28619 grad_norm: 7.6833 loss: 0.6609 bbox_loss: 0.3038 cls_loss: 0.1344 layout_loss: 0.2009 cls_layout_loss: 0.0218 | |
| 2025/09/13 17:50:17 - mmengine - INFO - Epoch(train) [5][ 950/1099] lr: 1.0000e-03 eta: 6:56:16 time: 3.1545 data_time: 0.1599 memory: 33319 grad_norm: 6.7463 loss: 0.6455 bbox_loss: 0.2985 cls_loss: 0.1297 layout_loss: 0.1959 cls_layout_loss: 0.0213 | |
| 2025/09/13 17:52:57 - mmengine - INFO - Epoch(train) [5][1000/1099] lr: 1.0000e-03 eta: 6:53:38 time: 3.2052 data_time: 0.1853 memory: 42833 grad_norm: 7.1353 loss: 0.6492 bbox_loss: 0.2990 cls_loss: 0.1297 layout_loss: 0.1985 cls_layout_loss: 0.0220 | |
| 2025/09/13 17:55:37 - mmengine - INFO - Epoch(train) [5][1050/1099] lr: 1.0000e-03 eta: 6:51:00 time: 3.1952 data_time: 0.1779 memory: 26245 grad_norm: 7.8461 loss: 0.6525 bbox_loss: 0.3032 cls_loss: 0.1317 layout_loss: 0.1962 cls_layout_loss: 0.0213 | |
| 2025/09/13 17:58:08 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 17:58:09 - mmengine - INFO - Saving checkpoint at 5 epochs | |
| 2025/09/13 17:58:50 - mmengine - INFO - Epoch(val) [5][ 50/241] eta: 0:02:34 time: 0.8095 data_time: 0.0789 memory: 28048 | |
| 2025/09/13 17:59:26 - mmengine - INFO - Epoch(val) [5][100/241] eta: 0:01:47 time: 0.7219 data_time: 0.0746 memory: 1369 | |
| 2025/09/13 18:00:04 - mmengine - INFO - Epoch(val) [5][150/241] eta: 0:01:09 time: 0.7668 data_time: 0.0692 memory: 1230 | |
| 2025/09/13 18:00:42 - mmengine - INFO - Epoch(val) [5][200/241] eta: 0:00:31 time: 0.7489 data_time: 0.0938 memory: 1081 | |
| 2025/09/13 18:02:18 - mmengine - INFO - | |
| +---------+-------------+-------------+ | |
| | Layouts | F1 @.25 IoU | F1 @.50 IoU | | |
| +---------+-------------+-------------+ | |
| | wall | 0.8557 | 0.8359 | | |
| | door | 0.9176 | 0.9093 | | |
| | window | 0.8523 | 0.8362 | | |
| +---------+-------------+-------------+ | |
| | Overall | 0.8752 | 0.8605 | | |
| +---------+-------------+-------------+ | |
| 2025/09/13 18:02:18 - mmengine - INFO - Epoch(val) [5][241/241] structured3d: {'layout': {'wall_f1_25': 0.8557155169996679, 'wall_f1_50': 0.8557155169996679, 'door_f1_25': 0.917635081256629, 'door_f1_50': 0.917635081256629, 'window_f1_25': 0.852285343163436, 'window_f1_50': 0.852285343163436, 'f1_25': 0.8752119804732442, 'f1_50': 0.8604501909411288}} data_time: 0.0762 time: 0.7751 | |
| 2025/09/13 18:04:57 - mmengine - INFO - Epoch(train) [6][ 50/1099] lr: 1.0000e-03 eta: 6:45:37 time: 3.1777 data_time: 0.2887 memory: 27621 grad_norm: 7.5313 loss: 0.6427 bbox_loss: 0.2990 cls_loss: 0.1283 layout_loss: 0.1938 cls_layout_loss: 0.0216 | |
| 2025/09/13 18:07:36 - mmengine - INFO - Epoch(train) [6][ 100/1099] lr: 1.0000e-03 eta: 6:42:58 time: 3.1824 data_time: 0.1936 memory: 29651 grad_norm: 8.1896 loss: 0.6483 bbox_loss: 0.3023 cls_loss: 0.1298 layout_loss: 0.1947 cls_layout_loss: 0.0215 | |
| 2025/09/13 18:10:18 - mmengine - INFO - Epoch(train) [6][ 150/1099] lr: 1.0000e-03 eta: 6:40:22 time: 3.2319 data_time: 0.1343 memory: 31071 grad_norm: 8.7005 loss: 0.6570 bbox_loss: 0.3044 cls_loss: 0.1328 layout_loss: 0.1981 cls_layout_loss: 0.0217 | |
| 2025/09/13 18:12:52 - mmengine - INFO - Epoch(train) [6][ 200/1099] lr: 1.0000e-03 eta: 6:37:35 time: 3.0792 data_time: 0.1512 memory: 25821 grad_norm: 6.8937 loss: 0.6109 bbox_loss: 0.2933 cls_loss: 0.1227 layout_loss: 0.1746 cls_layout_loss: 0.0203 | |
| 2025/09/13 18:15:37 - mmengine - INFO - Epoch(train) [6][ 250/1099] lr: 1.0000e-03 eta: 6:35:03 time: 3.2951 data_time: 0.1850 memory: 36986 grad_norm: 6.7653 loss: 0.6556 bbox_loss: 0.2985 cls_loss: 0.1279 layout_loss: 0.2076 cls_layout_loss: 0.0216 | |
| 2025/09/13 18:18:14 - mmengine - INFO - Epoch(train) [6][ 300/1099] lr: 1.0000e-03 eta: 6:32:22 time: 3.1567 data_time: 0.1700 memory: 26462 grad_norm: 8.4172 loss: 0.6366 bbox_loss: 0.3002 cls_loss: 0.1257 layout_loss: 0.1896 cls_layout_loss: 0.0211 | |
| 2025/09/13 18:20:53 - mmengine - INFO - Epoch(train) [6][ 350/1099] lr: 1.0000e-03 eta: 6:29:42 time: 3.1725 data_time: 0.1517 memory: 30735 grad_norm: 6.9265 loss: 0.6481 bbox_loss: 0.2998 cls_loss: 0.1312 layout_loss: 0.1956 cls_layout_loss: 0.0214 | |
| 2025/09/13 18:23:34 - mmengine - INFO - Epoch(train) [6][ 400/1099] lr: 1.0000e-03 eta: 6:27:05 time: 3.2165 data_time: 0.1531 memory: 31044 grad_norm: 7.0833 loss: 0.6555 bbox_loss: 0.3000 cls_loss: 0.1307 layout_loss: 0.2038 cls_layout_loss: 0.0211 | |
| 2025/09/13 18:26:13 - mmengine - INFO - Epoch(train) [6][ 450/1099] lr: 1.0000e-03 eta: 6:24:26 time: 3.1835 data_time: 0.1431 memory: 31062 grad_norm: 7.8782 loss: 0.6496 bbox_loss: 0.3011 cls_loss: 0.1265 layout_loss: 0.2002 cls_layout_loss: 0.0219 | |
| 2025/09/13 18:28:52 - mmengine - INFO - Epoch(train) [6][ 500/1099] lr: 1.0000e-03 eta: 6:21:46 time: 3.1743 data_time: 0.1394 memory: 27192 grad_norm: 6.2651 loss: 0.6265 bbox_loss: 0.2951 cls_loss: 0.1227 layout_loss: 0.1878 cls_layout_loss: 0.0209 | |
| 2025/09/13 18:29:08 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 18:31:28 - mmengine - INFO - Epoch(train) [6][ 550/1099] lr: 1.0000e-03 eta: 6:19:03 time: 3.1239 data_time: 0.2019 memory: 26171 grad_norm: 8.6159 loss: 0.6309 bbox_loss: 0.2969 cls_loss: 0.1268 layout_loss: 0.1862 cls_layout_loss: 0.0211 | |
| 2025/09/13 18:34:09 - mmengine - INFO - Epoch(train) [6][ 600/1099] lr: 1.0000e-03 eta: 6:16:26 time: 3.2228 data_time: 0.1394 memory: 29268 grad_norm: 6.7264 loss: 0.6387 bbox_loss: 0.2991 cls_loss: 0.1300 layout_loss: 0.1881 cls_layout_loss: 0.0215 | |
| 2025/09/13 18:36:48 - mmengine - INFO - Epoch(train) [6][ 650/1099] lr: 1.0000e-03 eta: 6:13:47 time: 3.1781 data_time: 0.1379 memory: 29006 grad_norm: 6.4940 loss: 0.6189 bbox_loss: 0.2937 cls_loss: 0.1249 layout_loss: 0.1794 cls_layout_loss: 0.0209 | |
| 2025/09/13 18:39:22 - mmengine - INFO - Epoch(train) [6][ 700/1099] lr: 1.0000e-03 eta: 6:11:02 time: 3.0922 data_time: 0.1547 memory: 29975 grad_norm: 6.3581 loss: 0.6232 bbox_loss: 0.2940 cls_loss: 0.1227 layout_loss: 0.1858 cls_layout_loss: 0.0207 | |
| 2025/09/13 18:41:58 - mmengine - INFO - Epoch(train) [6][ 750/1099] lr: 1.0000e-03 eta: 6:08:19 time: 3.1160 data_time: 0.1509 memory: 33724 grad_norm: 6.6837 loss: 0.6346 bbox_loss: 0.2943 cls_loss: 0.1242 layout_loss: 0.1951 cls_layout_loss: 0.0210 | |
| 2025/09/13 18:44:36 - mmengine - INFO - Epoch(train) [6][ 800/1099] lr: 1.0000e-03 eta: 6:05:39 time: 3.1532 data_time: 0.1739 memory: 26178 grad_norm: 7.5438 loss: 0.6240 bbox_loss: 0.2968 cls_loss: 0.1274 layout_loss: 0.1794 cls_layout_loss: 0.0205 | |
| 2025/09/13 18:47:10 - mmengine - INFO - Epoch(train) [6][ 850/1099] lr: 1.0000e-03 eta: 6:02:54 time: 3.0858 data_time: 0.1492 memory: 25479 grad_norm: 6.4790 loss: 0.6226 bbox_loss: 0.2934 cls_loss: 0.1264 layout_loss: 0.1820 cls_layout_loss: 0.0208 | |
| 2025/09/13 18:49:52 - mmengine - INFO - Epoch(train) [6][ 900/1099] lr: 1.0000e-03 eta: 6:00:18 time: 3.2446 data_time: 0.1995 memory: 28078 grad_norm: 7.1846 loss: 0.6280 bbox_loss: 0.2980 cls_loss: 0.1282 layout_loss: 0.1810 cls_layout_loss: 0.0208 | |
| 2025/09/13 18:52:33 - mmengine - INFO - Epoch(train) [6][ 950/1099] lr: 1.0000e-03 eta: 5:57:41 time: 3.2185 data_time: 0.1600 memory: 34057 grad_norm: 5.8847 loss: 0.6383 bbox_loss: 0.2970 cls_loss: 0.1271 layout_loss: 0.1927 cls_layout_loss: 0.0214 | |
| 2025/09/13 18:55:13 - mmengine - INFO - Epoch(train) [6][1000/1099] lr: 1.0000e-03 eta: 5:55:02 time: 3.1824 data_time: 0.1858 memory: 28759 grad_norm: 8.1307 loss: 0.6265 bbox_loss: 0.2968 cls_loss: 0.1236 layout_loss: 0.1849 cls_layout_loss: 0.0211 | |
| 2025/09/13 18:57:53 - mmengine - INFO - Epoch(train) [6][1050/1099] lr: 1.0000e-03 eta: 5:52:24 time: 3.2048 data_time: 0.1571 memory: 28997 grad_norm: 6.7060 loss: 0.6179 bbox_loss: 0.2930 cls_loss: 0.1237 layout_loss: 0.1810 cls_layout_loss: 0.0202 | |
| 2025/09/13 19:00:29 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 19:00:29 - mmengine - INFO - Saving checkpoint at 6 epochs | |
| 2025/09/13 19:01:09 - mmengine - INFO - Epoch(val) [6][ 50/241] eta: 0:02:26 time: 0.7673 data_time: 0.0825 memory: 29003 | |
| 2025/09/13 19:01:40 - mmengine - INFO - Epoch(val) [6][100/241] eta: 0:01:37 time: 0.6213 data_time: 0.0885 memory: 1369 | |
| 2025/09/13 19:02:15 - mmengine - INFO - Epoch(val) [6][150/241] eta: 0:01:03 time: 0.7099 data_time: 0.0712 memory: 1230 | |
| 2025/09/13 19:02:49 - mmengine - INFO - Epoch(val) [6][200/241] eta: 0:00:28 time: 0.6828 data_time: 0.0807 memory: 1081 | |
| 2025/09/13 19:04:24 - mmengine - INFO - | |
| +---------+-------------+-------------+ | |
| | Layouts | F1 @.25 IoU | F1 @.50 IoU | | |
| +---------+-------------+-------------+ | |
| | wall | 0.8606 | 0.8422 | | |
| | door | 0.9274 | 0.9232 | | |
| | window | 0.8722 | 0.8544 | | |
| +---------+-------------+-------------+ | |
| | Overall | 0.8867 | 0.8732 | | |
| +---------+-------------+-------------+ | |
| 2025/09/13 19:04:24 - mmengine - INFO - Epoch(val) [6][241/241] structured3d: {'layout': {'wall_f1_25': 0.8606251303168886, 'wall_f1_50': 0.8606251303168886, 'door_f1_25': 0.9273867099453994, 'door_f1_50': 0.9273867099453994, 'window_f1_25': 0.8721593995488645, 'window_f1_50': 0.8721593995488645, 'f1_25': 0.8867237466037174, 'f1_50': 0.8732411124598274}} data_time: 0.0764 time: 0.7138 | |
| 2025/09/13 19:07:10 - mmengine - INFO - Epoch(train) [7][ 50/1099] lr: 1.0000e-03 eta: 5:47:15 time: 3.3187 data_time: 0.2941 memory: 25199 grad_norm: 6.8318 loss: 0.6223 bbox_loss: 0.2933 cls_loss: 0.1224 layout_loss: 0.1860 cls_layout_loss: 0.0206 | |
| 2025/09/13 19:09:48 - mmengine - INFO - Epoch(train) [7][ 100/1099] lr: 1.0000e-03 eta: 5:44:35 time: 3.1486 data_time: 0.1328 memory: 29365 grad_norm: 7.8828 loss: 0.6243 bbox_loss: 0.2970 cls_loss: 0.1270 layout_loss: 0.1798 cls_layout_loss: 0.0205 | |
| 2025/09/13 19:12:25 - mmengine - INFO - Epoch(train) [7][ 150/1099] lr: 1.0000e-03 eta: 5:41:54 time: 3.1460 data_time: 0.1685 memory: 28273 grad_norm: 6.3674 loss: 0.6186 bbox_loss: 0.2906 cls_loss: 0.1215 layout_loss: 0.1860 cls_layout_loss: 0.0205 | |
| 2025/09/13 19:15:06 - mmengine - INFO - Epoch(train) [7][ 200/1099] lr: 1.0000e-03 eta: 5:39:16 time: 3.2270 data_time: 0.1796 memory: 25015 grad_norm: 6.2255 loss: 0.6257 bbox_loss: 0.2930 cls_loss: 0.1234 layout_loss: 0.1886 cls_layout_loss: 0.0208 | |
| 2025/09/13 19:17:45 - mmengine - INFO - Epoch(train) [7][ 250/1099] lr: 1.0000e-03 eta: 5:36:37 time: 3.1805 data_time: 0.1710 memory: 27452 grad_norm: 6.6723 loss: 0.6123 bbox_loss: 0.2926 cls_loss: 0.1204 layout_loss: 0.1787 cls_layout_loss: 0.0206 | |
| 2025/09/13 19:20:21 - mmengine - INFO - Epoch(train) [7][ 300/1099] lr: 1.0000e-03 eta: 5:33:55 time: 3.1220 data_time: 0.1585 memory: 27545 grad_norm: 6.5987 loss: 0.6248 bbox_loss: 0.2945 cls_loss: 0.1300 layout_loss: 0.1799 cls_layout_loss: 0.0205 | |
| 2025/09/13 19:22:59 - mmengine - INFO - Epoch(train) [7][ 350/1099] lr: 1.0000e-03 eta: 5:31:15 time: 3.1633 data_time: 0.1765 memory: 27564 grad_norm: 7.1988 loss: 0.6216 bbox_loss: 0.2942 cls_loss: 0.1239 layout_loss: 0.1830 cls_layout_loss: 0.0204 | |
| 2025/09/13 19:25:37 - mmengine - INFO - Epoch(train) [7][ 400/1099] lr: 1.0000e-03 eta: 5:28:35 time: 3.1552 data_time: 0.1597 memory: 26373 grad_norm: 6.6615 loss: 0.6212 bbox_loss: 0.2942 cls_loss: 0.1229 layout_loss: 0.1839 cls_layout_loss: 0.0202 | |
| 2025/09/13 19:25:56 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 19:28:09 - mmengine - INFO - Epoch(train) [7][ 450/1099] lr: 1.0000e-03 eta: 5:25:50 time: 3.0480 data_time: 0.1459 memory: 25504 grad_norm: 6.5436 loss: 0.5983 bbox_loss: 0.2897 cls_loss: 0.1163 layout_loss: 0.1719 cls_layout_loss: 0.0203 | |
| 2025/09/13 19:30:48 - mmengine - INFO - Epoch(train) [7][ 500/1099] lr: 1.0000e-03 eta: 5:23:10 time: 3.1612 data_time: 0.1554 memory: 30774 grad_norm: 7.8974 loss: 0.6168 bbox_loss: 0.2927 cls_loss: 0.1246 layout_loss: 0.1798 cls_layout_loss: 0.0197 | |
| 2025/09/13 19:33:20 - mmengine - INFO - Epoch(train) [7][ 550/1099] lr: 1.0000e-03 eta: 5:20:24 time: 3.0398 data_time: 0.1460 memory: 28247 grad_norm: 6.4011 loss: 0.6116 bbox_loss: 0.2898 cls_loss: 0.1217 layout_loss: 0.1800 cls_layout_loss: 0.0200 | |
| 2025/09/13 19:35:58 - mmengine - INFO - Epoch(train) [7][ 600/1099] lr: 1.0000e-03 eta: 5:17:45 time: 3.1782 data_time: 0.1598 memory: 29232 grad_norm: 6.3764 loss: 0.6375 bbox_loss: 0.2966 cls_loss: 0.1284 layout_loss: 0.1919 cls_layout_loss: 0.0206 | |
| 2025/09/13 19:38:39 - mmengine - INFO - Epoch(train) [7][ 650/1099] lr: 1.0000e-03 eta: 5:15:07 time: 3.2056 data_time: 0.1563 memory: 32673 grad_norm: 6.1819 loss: 0.6085 bbox_loss: 0.2893 cls_loss: 0.1188 layout_loss: 0.1801 cls_layout_loss: 0.0203 | |
| 2025/09/13 19:41:17 - mmengine - INFO - Epoch(train) [7][ 700/1099] lr: 1.0000e-03 eta: 5:12:28 time: 3.1702 data_time: 0.1562 memory: 26304 grad_norm: 6.4609 loss: 0.6127 bbox_loss: 0.2909 cls_loss: 0.1221 layout_loss: 0.1791 cls_layout_loss: 0.0205 | |
| 2025/09/13 19:43:54 - mmengine - INFO - Epoch(train) [7][ 750/1099] lr: 1.0000e-03 eta: 5:09:47 time: 3.1328 data_time: 0.1696 memory: 27958 grad_norm: 5.7427 loss: 0.6117 bbox_loss: 0.2895 cls_loss: 0.1216 layout_loss: 0.1805 cls_layout_loss: 0.0202 | |
| 2025/09/13 19:46:28 - mmengine - INFO - Epoch(train) [7][ 800/1099] lr: 1.0000e-03 eta: 5:07:04 time: 3.0856 data_time: 0.1657 memory: 29163 grad_norm: 6.6596 loss: 0.6076 bbox_loss: 0.2920 cls_loss: 0.1177 layout_loss: 0.1775 cls_layout_loss: 0.0204 | |
| 2025/09/13 19:49:08 - mmengine - INFO - Epoch(train) [7][ 850/1099] lr: 1.0000e-03 eta: 5:04:26 time: 3.1979 data_time: 0.1797 memory: 27236 grad_norm: 7.2534 loss: 0.6111 bbox_loss: 0.2915 cls_loss: 0.1234 layout_loss: 0.1761 cls_layout_loss: 0.0202 | |
| 2025/09/13 19:51:45 - mmengine - INFO - Epoch(train) [7][ 900/1099] lr: 1.0000e-03 eta: 5:01:45 time: 3.1348 data_time: 0.1513 memory: 30234 grad_norm: 6.3193 loss: 0.6173 bbox_loss: 0.2922 cls_loss: 0.1202 layout_loss: 0.1846 cls_layout_loss: 0.0204 | |
| 2025/09/13 19:54:22 - mmengine - INFO - Epoch(train) [7][ 950/1099] lr: 1.0000e-03 eta: 4:59:05 time: 3.1381 data_time: 0.1647 memory: 26501 grad_norm: 6.4649 loss: 0.5938 bbox_loss: 0.2882 cls_loss: 0.1163 layout_loss: 0.1699 cls_layout_loss: 0.0194 | |
| 2025/09/13 19:57:03 - mmengine - INFO - Epoch(train) [7][1000/1099] lr: 1.0000e-03 eta: 4:56:27 time: 3.2288 data_time: 0.1932 memory: 33740 grad_norm: 6.1691 loss: 0.6011 bbox_loss: 0.2857 cls_loss: 0.1136 layout_loss: 0.1816 cls_layout_loss: 0.0202 | |
| 2025/09/13 19:59:39 - mmengine - INFO - Epoch(train) [7][1050/1099] lr: 1.0000e-03 eta: 4:53:46 time: 3.1152 data_time: 0.1444 memory: 30791 grad_norm: 6.1823 loss: 0.6142 bbox_loss: 0.2905 cls_loss: 0.1239 layout_loss: 0.1797 cls_layout_loss: 0.0200 | |
| 2025/09/13 20:02:14 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 20:02:15 - mmengine - INFO - Saving checkpoint at 7 epochs | |
| 2025/09/13 20:02:50 - mmengine - INFO - Epoch(val) [7][ 50/241] eta: 0:02:13 time: 0.7011 data_time: 0.0807 memory: 28842 | |
| 2025/09/13 20:03:23 - mmengine - INFO - Epoch(val) [7][100/241] eta: 0:01:35 time: 0.6509 data_time: 0.0563 memory: 1369 | |
| 2025/09/13 20:03:55 - mmengine - INFO - Epoch(val) [7][150/241] eta: 0:01:00 time: 0.6476 data_time: 0.0675 memory: 1230 | |
| 2025/09/13 20:04:29 - mmengine - INFO - Epoch(val) [7][200/241] eta: 0:00:27 time: 0.6770 data_time: 0.0651 memory: 1081 | |
| 2025/09/13 20:06:00 - mmengine - INFO - | |
| +---------+-------------+-------------+ | |
| | Layouts | F1 @.25 IoU | F1 @.50 IoU | | |
| +---------+-------------+-------------+ | |
| | wall | 0.8614 | 0.8476 | | |
| | door | 0.9270 | 0.9221 | | |
| | window | 0.8696 | 0.8486 | | |
| +---------+-------------+-------------+ | |
| | Overall | 0.8860 | 0.8728 | | |
| +---------+-------------+-------------+ | |
| 2025/09/13 20:06:00 - mmengine - INFO - Epoch(val) [7][241/241] structured3d: {'layout': {'wall_f1_25': 0.8613869912848221, 'wall_f1_50': 0.8613869912848221, 'door_f1_25': 0.927018507340305, 'door_f1_50': 0.927018507340305, 'window_f1_25': 0.8695505509586754, 'window_f1_50': 0.8695505509586754, 'f1_25': 0.8859853498612674, 'f1_50': 0.8727628776779014}} data_time: 0.0686 time: 0.6839 | |
| 2025/09/13 20:08:45 - mmengine - INFO - Epoch(train) [8][ 50/1099] lr: 1.0000e-03 eta: 4:48:35 time: 3.3096 data_time: 0.2481 memory: 28440 grad_norm: 6.1856 loss: 0.6102 bbox_loss: 0.2922 cls_loss: 0.1217 layout_loss: 0.1762 cls_layout_loss: 0.0201 | |
| 2025/09/13 20:11:25 - mmengine - INFO - Epoch(train) [8][ 100/1099] lr: 1.0000e-03 eta: 4:45:57 time: 3.1899 data_time: 0.1569 memory: 28992 grad_norm: 5.7781 loss: 0.6144 bbox_loss: 0.2925 cls_loss: 0.1211 layout_loss: 0.1807 cls_layout_loss: 0.0201 | |
| 2025/09/13 20:14:04 - mmengine - INFO - Epoch(train) [8][ 150/1099] lr: 1.0000e-03 eta: 4:43:17 time: 3.1789 data_time: 0.1572 memory: 27743 grad_norm: 6.9183 loss: 0.5936 bbox_loss: 0.2869 cls_loss: 0.1158 layout_loss: 0.1709 cls_layout_loss: 0.0200 | |
| 2025/09/13 20:16:39 - mmengine - INFO - Epoch(train) [8][ 200/1099] lr: 1.0000e-03 eta: 4:40:36 time: 3.0966 data_time: 0.1794 memory: 29725 grad_norm: 5.6513 loss: 0.5977 bbox_loss: 0.2838 cls_loss: 0.1189 layout_loss: 0.1752 cls_layout_loss: 0.0198 | |
| 2025/09/13 20:19:19 - mmengine - INFO - Epoch(train) [8][ 250/1099] lr: 1.0000e-03 eta: 4:37:58 time: 3.2090 data_time: 0.1694 memory: 27959 grad_norm: 5.3682 loss: 0.6077 bbox_loss: 0.2900 cls_loss: 0.1225 layout_loss: 0.1751 cls_layout_loss: 0.0201 | |
| 2025/09/13 20:22:02 - mmengine - INFO - Epoch(train) [8][ 300/1099] lr: 1.0000e-03 eta: 4:35:21 time: 3.2610 data_time: 0.1800 memory: 25575 grad_norm: 6.4331 loss: 0.6027 bbox_loss: 0.2895 cls_loss: 0.1226 layout_loss: 0.1710 cls_layout_loss: 0.0197 | |
| 2025/09/13 20:22:23 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 20:24:42 - mmengine - INFO - Epoch(train) [8][ 350/1099] lr: 1.0000e-03 eta: 4:32:43 time: 3.1999 data_time: 0.1463 memory: 25639 grad_norm: 5.7575 loss: 0.6059 bbox_loss: 0.2871 cls_loss: 0.1188 layout_loss: 0.1799 cls_layout_loss: 0.0200 | |
| 2025/09/13 20:27:22 - mmengine - INFO - Epoch(train) [8][ 400/1099] lr: 1.0000e-03 eta: 4:30:04 time: 3.1991 data_time: 0.1889 memory: 27725 grad_norm: 6.5223 loss: 0.6057 bbox_loss: 0.2908 cls_loss: 0.1163 layout_loss: 0.1789 cls_layout_loss: 0.0198 | |
| 2025/09/13 20:30:02 - mmengine - INFO - Epoch(train) [8][ 450/1099] lr: 1.0000e-03 eta: 4:27:26 time: 3.2064 data_time: 0.1365 memory: 32109 grad_norm: 7.4987 loss: 0.5934 bbox_loss: 0.2879 cls_loss: 0.1148 layout_loss: 0.1713 cls_layout_loss: 0.0194 | |
| 2025/09/13 20:32:42 - mmengine - INFO - Epoch(train) [8][ 500/1099] lr: 1.0000e-03 eta: 4:24:47 time: 3.1896 data_time: 0.1619 memory: 29044 grad_norm: 5.7442 loss: 0.5970 bbox_loss: 0.2848 cls_loss: 0.1186 layout_loss: 0.1739 cls_layout_loss: 0.0198 | |
| 2025/09/13 20:35:22 - mmengine - INFO - Epoch(train) [8][ 550/1099] lr: 1.0000e-03 eta: 4:22:09 time: 3.2100 data_time: 0.1645 memory: 33111 grad_norm: 6.0075 loss: 0.6098 bbox_loss: 0.2885 cls_loss: 0.1207 layout_loss: 0.1806 cls_layout_loss: 0.0200 | |
| 2025/09/13 20:38:02 - mmengine - INFO - Epoch(train) [8][ 600/1099] lr: 1.0000e-03 eta: 4:19:30 time: 3.1860 data_time: 0.1816 memory: 28677 grad_norm: 5.7074 loss: 0.5836 bbox_loss: 0.2833 cls_loss: 0.1169 layout_loss: 0.1643 cls_layout_loss: 0.0191 | |
| 2025/09/13 20:40:44 - mmengine - INFO - Epoch(train) [8][ 650/1099] lr: 1.0000e-03 eta: 4:16:53 time: 3.2426 data_time: 0.1524 memory: 31735 grad_norm: 5.4369 loss: 0.5965 bbox_loss: 0.2843 cls_loss: 0.1181 layout_loss: 0.1745 cls_layout_loss: 0.0196 | |
| 2025/09/13 20:43:23 - mmengine - INFO - Epoch(train) [8][ 700/1099] lr: 1.0000e-03 eta: 4:14:14 time: 3.1860 data_time: 0.1683 memory: 25671 grad_norm: 6.5646 loss: 0.6034 bbox_loss: 0.2894 cls_loss: 0.1199 layout_loss: 0.1742 cls_layout_loss: 0.0199 | |
| 2025/09/13 20:46:05 - mmengine - INFO - Epoch(train) [8][ 750/1099] lr: 1.0000e-03 eta: 4:11:37 time: 3.2312 data_time: 0.1647 memory: 30446 grad_norm: 5.8300 loss: 0.6020 bbox_loss: 0.2892 cls_loss: 0.1205 layout_loss: 0.1728 cls_layout_loss: 0.0195 | |
| 2025/09/13 20:48:39 - mmengine - INFO - Epoch(train) [8][ 800/1099] lr: 1.0000e-03 eta: 4:08:55 time: 3.0929 data_time: 0.1555 memory: 25750 grad_norm: 7.0731 loss: 0.5753 bbox_loss: 0.2876 cls_loss: 0.1088 layout_loss: 0.1598 cls_layout_loss: 0.0192 | |
| 2025/09/13 20:51:16 - mmengine - INFO - Epoch(train) [8][ 850/1099] lr: 1.0000e-03 eta: 4:06:15 time: 3.1404 data_time: 0.1697 memory: 30071 grad_norm: 5.6928 loss: 0.5890 bbox_loss: 0.2881 cls_loss: 0.1141 layout_loss: 0.1674 cls_layout_loss: 0.0193 | |
| 2025/09/13 20:53:53 - mmengine - INFO - Epoch(train) [8][ 900/1099] lr: 1.0000e-03 eta: 4:03:35 time: 3.1378 data_time: 0.1511 memory: 27659 grad_norm: 5.8219 loss: 0.5850 bbox_loss: 0.2865 cls_loss: 0.1125 layout_loss: 0.1670 cls_layout_loss: 0.0189 | |
| 2025/09/13 20:56:35 - mmengine - INFO - Epoch(train) [8][ 950/1099] lr: 1.0000e-03 eta: 4:00:57 time: 3.2307 data_time: 0.1673 memory: 32695 grad_norm: 6.2038 loss: 0.5989 bbox_loss: 0.2868 cls_loss: 0.1168 layout_loss: 0.1759 cls_layout_loss: 0.0193 | |
| 2025/09/13 20:59:13 - mmengine - INFO - Epoch(train) [8][1000/1099] lr: 1.0000e-03 eta: 3:58:18 time: 3.1661 data_time: 0.1566 memory: 26740 grad_norm: 6.1501 loss: 0.5868 bbox_loss: 0.2841 cls_loss: 0.1125 layout_loss: 0.1704 cls_layout_loss: 0.0198 | |
| 2025/09/13 21:01:54 - mmengine - INFO - Epoch(train) [8][1050/1099] lr: 1.0000e-03 eta: 3:55:40 time: 3.2283 data_time: 0.1751 memory: 28241 grad_norm: 6.1625 loss: 0.5766 bbox_loss: 0.2850 cls_loss: 0.1105 layout_loss: 0.1622 cls_layout_loss: 0.0189 | |
| 2025/09/13 21:04:26 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 21:04:27 - mmengine - INFO - Saving checkpoint at 8 epochs | |
| 2025/09/13 21:05:06 - mmengine - INFO - Epoch(val) [8][ 50/241] eta: 0:02:26 time: 0.7665 data_time: 0.0586 memory: 24688 | |
| 2025/09/13 21:05:39 - mmengine - INFO - Epoch(val) [8][100/241] eta: 0:01:39 time: 0.6416 data_time: 0.0556 memory: 1369 | |
| 2025/09/13 21:06:11 - mmengine - INFO - Epoch(val) [8][150/241] eta: 0:01:02 time: 0.6490 data_time: 0.0456 memory: 1230 | |
| 2025/09/13 21:06:44 - mmengine - INFO - Epoch(val) [8][200/241] eta: 0:00:27 time: 0.6556 data_time: 0.0809 memory: 1081 | |
| 2025/09/13 21:08:13 - mmengine - INFO - | |
| +---------+-------------+-------------+ | |
| | Layouts | F1 @.25 IoU | F1 @.50 IoU | | |
| +---------+-------------+-------------+ | |
| | wall | 0.8702 | 0.8582 | | |
| | door | 0.9326 | 0.9306 | | |
| | window | 0.8831 | 0.8712 | | |
| +---------+-------------+-------------+ | |
| | Overall | 0.8953 | 0.8867 | | |
| +---------+-------------+-------------+ | |
| 2025/09/13 21:08:13 - mmengine - INFO - Epoch(val) [8][241/241] structured3d: {'layout': {'wall_f1_25': 0.8701736125015925, 'wall_f1_50': 0.8701736125015925, 'door_f1_25': 0.9326243153350507, 'door_f1_50': 0.9326243153350507, 'window_f1_25': 0.8830856147632826, 'window_f1_50': 0.8830856147632826, 'f1_25': 0.8952945141999753, 'f1_50': 0.8866601100554897}} data_time: 0.0592 time: 0.6866 | |
| 2025/09/13 21:11:00 - mmengine - INFO - Epoch(train) [9][ 50/1099] lr: 1.0000e-04 eta: 3:50:27 time: 3.3391 data_time: 0.2609 memory: 26291 grad_norm: 4.3532 loss: 0.5704 bbox_loss: 0.2757 cls_loss: 0.1144 layout_loss: 0.1614 cls_layout_loss: 0.0188 | |
| 2025/09/13 21:13:38 - mmengine - INFO - Epoch(train) [9][ 100/1099] lr: 1.0000e-04 eta: 3:47:47 time: 3.1632 data_time: 0.1619 memory: 35112 grad_norm: 4.1512 loss: 0.5719 bbox_loss: 0.2761 cls_loss: 0.1124 layout_loss: 0.1640 cls_layout_loss: 0.0194 | |
| 2025/09/13 21:16:17 - mmengine - INFO - Epoch(train) [9][ 150/1099] lr: 1.0000e-04 eta: 3:45:08 time: 3.1861 data_time: 0.1735 memory: 27487 grad_norm: 4.8169 loss: 0.5507 bbox_loss: 0.2725 cls_loss: 0.1099 layout_loss: 0.1499 cls_layout_loss: 0.0184 | |
| 2025/09/13 21:18:59 - mmengine - INFO - Epoch(train) [9][ 200/1099] lr: 1.0000e-04 eta: 3:42:30 time: 3.2354 data_time: 0.1324 memory: 28128 grad_norm: 4.3515 loss: 0.5519 bbox_loss: 0.2734 cls_loss: 0.1094 layout_loss: 0.1508 cls_layout_loss: 0.0183 | |
| 2025/09/13 21:19:25 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 21:21:37 - mmengine - INFO - Epoch(train) [9][ 250/1099] lr: 1.0000e-04 eta: 3:39:51 time: 3.1664 data_time: 0.1812 memory: 27299 grad_norm: 4.0580 loss: 0.5436 bbox_loss: 0.2715 cls_loss: 0.1075 layout_loss: 0.1460 cls_layout_loss: 0.0186 | |
| 2025/09/13 21:24:15 - mmengine - INFO - Epoch(train) [9][ 300/1099] lr: 1.0000e-04 eta: 3:37:11 time: 3.1506 data_time: 0.1583 memory: 30055 grad_norm: 4.4423 loss: 0.5539 bbox_loss: 0.2739 cls_loss: 0.1126 layout_loss: 0.1491 cls_layout_loss: 0.0183 | |
| 2025/09/13 21:26:51 - mmengine - INFO - Epoch(train) [9][ 350/1099] lr: 1.0000e-04 eta: 3:34:31 time: 3.1313 data_time: 0.1717 memory: 26104 grad_norm: 4.0762 loss: 0.5348 bbox_loss: 0.2680 cls_loss: 0.1076 layout_loss: 0.1407 cls_layout_loss: 0.0186 | |
| 2025/09/13 21:29:29 - mmengine - INFO - Epoch(train) [9][ 400/1099] lr: 1.0000e-04 eta: 3:31:51 time: 3.1496 data_time: 0.1551 memory: 26193 grad_norm: 3.9925 loss: 0.5333 bbox_loss: 0.2687 cls_loss: 0.1061 layout_loss: 0.1399 cls_layout_loss: 0.0186 | |
| 2025/09/13 21:32:06 - mmengine - INFO - Epoch(train) [9][ 450/1099] lr: 1.0000e-04 eta: 3:29:11 time: 3.1323 data_time: 0.1400 memory: 35424 grad_norm: 4.0377 loss: 0.5365 bbox_loss: 0.2662 cls_loss: 0.1046 layout_loss: 0.1476 cls_layout_loss: 0.0182 | |
| 2025/09/13 21:34:42 - mmengine - INFO - Epoch(train) [9][ 500/1099] lr: 1.0000e-04 eta: 3:26:31 time: 3.1154 data_time: 0.1431 memory: 31733 grad_norm: 4.4425 loss: 0.5488 bbox_loss: 0.2689 cls_loss: 0.1081 layout_loss: 0.1533 cls_layout_loss: 0.0185 | |
| 2025/09/13 21:37:21 - mmengine - INFO - Epoch(train) [9][ 550/1099] lr: 1.0000e-04 eta: 3:23:52 time: 3.1852 data_time: 0.1539 memory: 26202 grad_norm: 3.6083 loss: 0.5242 bbox_loss: 0.2664 cls_loss: 0.1034 layout_loss: 0.1365 cls_layout_loss: 0.0179 | |
| 2025/09/13 21:40:02 - mmengine - INFO - Epoch(train) [9][ 600/1099] lr: 1.0000e-04 eta: 3:21:14 time: 3.2236 data_time: 0.1662 memory: 29507 grad_norm: 4.1237 loss: 0.5274 bbox_loss: 0.2661 cls_loss: 0.1058 layout_loss: 0.1377 cls_layout_loss: 0.0179 | |
| 2025/09/13 21:42:40 - mmengine - INFO - Epoch(train) [9][ 650/1099] lr: 1.0000e-04 eta: 3:18:34 time: 3.1726 data_time: 0.1549 memory: 28074 grad_norm: 3.9647 loss: 0.5499 bbox_loss: 0.2698 cls_loss: 0.1098 layout_loss: 0.1521 cls_layout_loss: 0.0182 | |
| 2025/09/13 21:45:20 - mmengine - INFO - Epoch(train) [9][ 700/1099] lr: 1.0000e-04 eta: 3:15:55 time: 3.1842 data_time: 0.1553 memory: 31795 grad_norm: 4.1700 loss: 0.5427 bbox_loss: 0.2662 cls_loss: 0.1046 layout_loss: 0.1538 cls_layout_loss: 0.0181 | |
| 2025/09/13 21:47:57 - mmengine - INFO - Epoch(train) [9][ 750/1099] lr: 1.0000e-04 eta: 3:13:16 time: 3.1467 data_time: 0.1789 memory: 25173 grad_norm: 4.2684 loss: 0.5261 bbox_loss: 0.2663 cls_loss: 0.1059 layout_loss: 0.1361 cls_layout_loss: 0.0178 | |
| 2025/09/13 21:50:39 - mmengine - INFO - Epoch(train) [9][ 800/1099] lr: 1.0000e-04 eta: 3:10:38 time: 3.2335 data_time: 0.2008 memory: 26242 grad_norm: 4.4069 loss: 0.5329 bbox_loss: 0.2680 cls_loss: 0.1047 layout_loss: 0.1421 cls_layout_loss: 0.0181 | |
| 2025/09/13 21:53:18 - mmengine - INFO - Epoch(train) [9][ 850/1099] lr: 1.0000e-04 eta: 3:07:59 time: 3.1938 data_time: 0.1733 memory: 27726 grad_norm: 4.0786 loss: 0.5285 bbox_loss: 0.2641 cls_loss: 0.1045 layout_loss: 0.1423 cls_layout_loss: 0.0176 | |
| 2025/09/13 21:55:52 - mmengine - INFO - Epoch(train) [9][ 900/1099] lr: 1.0000e-04 eta: 3:05:18 time: 3.0696 data_time: 0.1742 memory: 26221 grad_norm: 4.5411 loss: 0.5388 bbox_loss: 0.2700 cls_loss: 0.1079 layout_loss: 0.1423 cls_layout_loss: 0.0186 | |
| 2025/09/13 21:58:25 - mmengine - INFO - Epoch(train) [9][ 950/1099] lr: 1.0000e-04 eta: 3:02:37 time: 3.0616 data_time: 0.1310 memory: 27491 grad_norm: 3.9199 loss: 0.5315 bbox_loss: 0.2672 cls_loss: 0.1067 layout_loss: 0.1398 cls_layout_loss: 0.0178 | |
| 2025/09/13 22:01:00 - mmengine - INFO - Epoch(train) [9][1000/1099] lr: 1.0000e-04 eta: 2:59:56 time: 3.0959 data_time: 0.1774 memory: 32149 grad_norm: 4.1351 loss: 0.5355 bbox_loss: 0.2670 cls_loss: 0.1054 layout_loss: 0.1451 cls_layout_loss: 0.0180 | |
| 2025/09/13 22:03:37 - mmengine - INFO - Epoch(train) [9][1050/1099] lr: 1.0000e-04 eta: 2:57:17 time: 3.1354 data_time: 0.1694 memory: 35163 grad_norm: 3.8675 loss: 0.5165 bbox_loss: 0.2621 cls_loss: 0.0998 layout_loss: 0.1373 cls_layout_loss: 0.0173 | |
| 2025/09/13 22:06:09 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 22:06:09 - mmengine - INFO - Saving checkpoint at 9 epochs | |
| 2025/09/13 22:06:47 - mmengine - INFO - Epoch(val) [9][ 50/241] eta: 0:02:20 time: 0.7335 data_time: 0.0479 memory: 30089 | |
| 2025/09/13 22:07:21 - mmengine - INFO - Epoch(val) [9][100/241] eta: 0:01:39 time: 0.6791 data_time: 0.0645 memory: 1369 | |
| 2025/09/13 22:07:56 - mmengine - INFO - Epoch(val) [9][150/241] eta: 0:01:03 time: 0.6941 data_time: 0.0855 memory: 1230 | |
| 2025/09/13 22:08:29 - mmengine - INFO - Epoch(val) [9][200/241] eta: 0:00:28 time: 0.6656 data_time: 0.0568 memory: 1081 | |
| 2025/09/13 22:10:02 - mmengine - INFO - | |
| +---------+-------------+-------------+ | |
| | Layouts | F1 @.25 IoU | F1 @.50 IoU | | |
| +---------+-------------+-------------+ | |
| | wall | 0.8790 | 0.8657 | | |
| | door | 0.9362 | 0.9336 | | |
| | window | 0.8967 | 0.8833 | | |
| +---------+-------------+-------------+ | |
| | Overall | 0.9039 | 0.8942 | | |
| +---------+-------------+-------------+ | |
| 2025/09/13 22:10:02 - mmengine - INFO - Epoch(val) [9][241/241] structured3d: {'layout': {'wall_f1_25': 0.8789501644206176, 'wall_f1_50': 0.8789501644206176, 'door_f1_25': 0.9361946663292635, 'door_f1_50': 0.9361946663292635, 'window_f1_25': 0.8966795289205506, 'window_f1_50': 0.8966795289205506, 'f1_25': 0.9039414532234772, 'f1_50': 0.8941689079561351}} data_time: 0.0631 time: 0.6979 | |
| 2025/09/13 22:12:54 - mmengine - INFO - Epoch(train) [10][ 50/1099] lr: 1.0000e-04 eta: 2:52:05 time: 3.4321 data_time: 0.3218 memory: 35991 grad_norm: 4.8028 loss: 0.5323 bbox_loss: 0.2663 cls_loss: 0.1043 layout_loss: 0.1439 cls_layout_loss: 0.0179 | |
| 2025/09/13 22:15:28 - mmengine - INFO - Epoch(train) [10][ 100/1099] lr: 1.0000e-04 eta: 2:49:24 time: 3.0916 data_time: 0.1789 memory: 31724 grad_norm: 3.9967 loss: 0.5258 bbox_loss: 0.2639 cls_loss: 0.1027 layout_loss: 0.1413 cls_layout_loss: 0.0179 | |
| 2025/09/13 22:15:59 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 22:18:05 - mmengine - INFO - Epoch(train) [10][ 150/1099] lr: 1.0000e-04 eta: 2:46:45 time: 3.1291 data_time: 0.1582 memory: 26883 grad_norm: 3.8833 loss: 0.5284 bbox_loss: 0.2657 cls_loss: 0.1053 layout_loss: 0.1394 cls_layout_loss: 0.0180 | |
| 2025/09/13 22:20:44 - mmengine - INFO - Epoch(train) [10][ 200/1099] lr: 1.0000e-04 eta: 2:44:06 time: 3.1868 data_time: 0.1451 memory: 27716 grad_norm: 4.2531 loss: 0.5300 bbox_loss: 0.2654 cls_loss: 0.1048 layout_loss: 0.1419 cls_layout_loss: 0.0180 | |
| 2025/09/13 22:23:23 - mmengine - INFO - Epoch(train) [10][ 250/1099] lr: 1.0000e-04 eta: 2:41:27 time: 3.1676 data_time: 0.1685 memory: 27468 grad_norm: 4.0689 loss: 0.5296 bbox_loss: 0.2662 cls_loss: 0.1050 layout_loss: 0.1405 cls_layout_loss: 0.0179 | |
| 2025/09/13 22:25:57 - mmengine - INFO - Epoch(train) [10][ 300/1099] lr: 1.0000e-04 eta: 2:38:46 time: 3.0975 data_time: 0.1580 memory: 28414 grad_norm: 4.3693 loss: 0.5216 bbox_loss: 0.2660 cls_loss: 0.1026 layout_loss: 0.1354 cls_layout_loss: 0.0176 | |
| 2025/09/13 22:28:33 - mmengine - INFO - Epoch(train) [10][ 350/1099] lr: 1.0000e-04 eta: 2:36:06 time: 3.1055 data_time: 0.1653 memory: 27584 grad_norm: 3.9711 loss: 0.5324 bbox_loss: 0.2656 cls_loss: 0.1082 layout_loss: 0.1405 cls_layout_loss: 0.0181 | |
| 2025/09/13 22:31:15 - mmengine - INFO - Epoch(train) [10][ 400/1099] lr: 1.0000e-04 eta: 2:33:29 time: 3.2544 data_time: 0.1666 memory: 26478 grad_norm: 4.6938 loss: 0.5336 bbox_loss: 0.2674 cls_loss: 0.1092 layout_loss: 0.1389 cls_layout_loss: 0.0180 | |
| 2025/09/13 22:33:51 - mmengine - INFO - Epoch(train) [10][ 450/1099] lr: 1.0000e-04 eta: 2:30:49 time: 3.1031 data_time: 0.1320 memory: 30074 grad_norm: 4.4155 loss: 0.5176 bbox_loss: 0.2644 cls_loss: 0.1022 layout_loss: 0.1334 cls_layout_loss: 0.0176 | |
| 2025/09/13 22:36:29 - mmengine - INFO - Epoch(train) [10][ 500/1099] lr: 1.0000e-04 eta: 2:28:09 time: 3.1614 data_time: 0.1442 memory: 31207 grad_norm: 3.6790 loss: 0.5212 bbox_loss: 0.2637 cls_loss: 0.1040 layout_loss: 0.1361 cls_layout_loss: 0.0174 | |
| 2025/09/13 22:39:07 - mmengine - INFO - Epoch(train) [10][ 550/1099] lr: 1.0000e-04 eta: 2:25:30 time: 3.1598 data_time: 0.1412 memory: 30829 grad_norm: 4.0609 loss: 0.5236 bbox_loss: 0.2625 cls_loss: 0.1047 layout_loss: 0.1391 cls_layout_loss: 0.0172 | |
| 2025/09/13 22:41:48 - mmengine - INFO - Epoch(train) [10][ 600/1099] lr: 1.0000e-04 eta: 2:22:52 time: 3.2284 data_time: 0.1567 memory: 30694 grad_norm: 4.4562 loss: 0.5427 bbox_loss: 0.2683 cls_loss: 0.1078 layout_loss: 0.1484 cls_layout_loss: 0.0183 | |
| 2025/09/13 22:44:23 - mmengine - INFO - Epoch(train) [10][ 650/1099] lr: 1.0000e-04 eta: 2:20:12 time: 3.0985 data_time: 0.1494 memory: 31280 grad_norm: 4.2675 loss: 0.5260 bbox_loss: 0.2661 cls_loss: 0.1030 layout_loss: 0.1390 cls_layout_loss: 0.0179 | |
| 2025/09/13 22:47:00 - mmengine - INFO - Epoch(train) [10][ 700/1099] lr: 1.0000e-04 eta: 2:17:32 time: 3.1242 data_time: 0.1461 memory: 34370 grad_norm: 4.8503 loss: 0.5318 bbox_loss: 0.2654 cls_loss: 0.1047 layout_loss: 0.1435 cls_layout_loss: 0.0182 | |
| 2025/09/13 22:49:41 - mmengine - INFO - Epoch(train) [10][ 750/1099] lr: 1.0000e-04 eta: 2:14:54 time: 3.2250 data_time: 0.1688 memory: 26529 grad_norm: 4.4920 loss: 0.5271 bbox_loss: 0.2645 cls_loss: 0.1048 layout_loss: 0.1400 cls_layout_loss: 0.0178 | |
| 2025/09/13 22:52:19 - mmengine - INFO - Epoch(train) [10][ 800/1099] lr: 1.0000e-04 eta: 2:12:15 time: 3.1733 data_time: 0.1900 memory: 26465 grad_norm: 4.2188 loss: 0.5233 bbox_loss: 0.2657 cls_loss: 0.1014 layout_loss: 0.1386 cls_layout_loss: 0.0177 | |
| 2025/09/13 22:54:55 - mmengine - INFO - Epoch(train) [10][ 850/1099] lr: 1.0000e-04 eta: 2:09:36 time: 3.1177 data_time: 0.1507 memory: 27147 grad_norm: 3.9009 loss: 0.5240 bbox_loss: 0.2633 cls_loss: 0.1050 layout_loss: 0.1380 cls_layout_loss: 0.0177 | |
| 2025/09/13 22:57:34 - mmengine - INFO - Epoch(train) [10][ 900/1099] lr: 1.0000e-04 eta: 2:06:57 time: 3.1849 data_time: 0.1560 memory: 29676 grad_norm: 4.0135 loss: 0.5203 bbox_loss: 0.2650 cls_loss: 0.1030 layout_loss: 0.1347 cls_layout_loss: 0.0177 | |
| 2025/09/13 23:00:14 - mmengine - INFO - Epoch(train) [10][ 950/1099] lr: 1.0000e-04 eta: 2:04:18 time: 3.1842 data_time: 0.1721 memory: 27896 grad_norm: 4.1126 loss: 0.5278 bbox_loss: 0.2647 cls_loss: 0.1010 layout_loss: 0.1442 cls_layout_loss: 0.0179 | |
| 2025/09/13 23:02:53 - mmengine - INFO - Epoch(train) [10][1000/1099] lr: 1.0000e-04 eta: 2:01:39 time: 3.1959 data_time: 0.1434 memory: 27804 grad_norm: 3.9994 loss: 0.5279 bbox_loss: 0.2661 cls_loss: 0.1040 layout_loss: 0.1397 cls_layout_loss: 0.0180 | |
| 2025/09/13 23:05:32 - mmengine - INFO - Epoch(train) [10][1050/1099] lr: 1.0000e-04 eta: 1:59:00 time: 3.1631 data_time: 0.1489 memory: 36464 grad_norm: 4.2432 loss: 0.5174 bbox_loss: 0.2639 cls_loss: 0.1006 layout_loss: 0.1356 cls_layout_loss: 0.0173 | |
| 2025/09/13 23:08:06 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 23:08:07 - mmengine - INFO - Saving checkpoint at 10 epochs | |
| 2025/09/13 23:08:45 - mmengine - INFO - Epoch(val) [10][ 50/241] eta: 0:02:22 time: 0.7448 data_time: 0.0866 memory: 28814 | |
| 2025/09/13 23:09:17 - mmengine - INFO - Epoch(val) [10][100/241] eta: 0:01:38 time: 0.6511 data_time: 0.0628 memory: 1369 | |
| 2025/09/13 23:09:49 - mmengine - INFO - Epoch(val) [10][150/241] eta: 0:01:01 time: 0.6454 data_time: 0.0582 memory: 1230 | |
| 2025/09/13 23:10:24 - mmengine - INFO - Epoch(val) [10][200/241] eta: 0:00:27 time: 0.6867 data_time: 0.0611 memory: 1081 | |
| 2025/09/13 23:11:56 - mmengine - INFO - | |
| +---------+-------------+-------------+ | |
| | Layouts | F1 @.25 IoU | F1 @.50 IoU | | |
| +---------+-------------+-------------+ | |
| | wall | 0.8799 | 0.8680 | | |
| | door | 0.9388 | 0.9378 | | |
| | window | 0.8980 | 0.8847 | | |
| +---------+-------------+-------------+ | |
| | Overall | 0.9056 | 0.8968 | | |
| +---------+-------------+-------------+ | |
| 2025/09/13 23:11:56 - mmengine - INFO - Epoch(val) [10][241/241] structured3d: {'layout': {'wall_f1_25': 0.8799432064620621, 'wall_f1_50': 0.8799432064620621, 'door_f1_25': 0.9388397554712523, 'door_f1_50': 0.9388397554712523, 'window_f1_25': 0.8980157565282779, 'window_f1_50': 0.8980157565282779, 'f1_25': 0.9055995728205307, 'f1_50': 0.8968283311816623}} data_time: 0.0665 time: 0.6891 | |
| 2025/09/13 23:12:32 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/13 23:14:41 - mmengine - INFO - Epoch(train) [11][ 50/1099] lr: 1.0000e-04 eta: 1:53:46 time: 3.2959 data_time: 0.2654 memory: 30974 grad_norm: 4.4031 loss: 0.5349 bbox_loss: 0.2668 cls_loss: 0.1059 layout_loss: 0.1443 cls_layout_loss: 0.0179 | |
| 2025/09/13 23:17:17 - mmengine - INFO - Epoch(train) [11][ 100/1099] lr: 1.0000e-04 eta: 1:51:07 time: 3.1142 data_time: 0.1805 memory: 31187 grad_norm: 4.0806 loss: 0.5284 bbox_loss: 0.2622 cls_loss: 0.0974 layout_loss: 0.1512 cls_layout_loss: 0.0176 | |
| 2025/09/13 23:19:55 - mmengine - INFO - Epoch(train) [11][ 150/1099] lr: 1.0000e-04 eta: 1:48:28 time: 3.1605 data_time: 0.1597 memory: 34765 grad_norm: 4.2669 loss: 0.5391 bbox_loss: 0.2637 cls_loss: 0.1064 layout_loss: 0.1510 cls_layout_loss: 0.0180 | |
| 2025/09/13 23:22:28 - mmengine - INFO - Epoch(train) [11][ 200/1099] lr: 1.0000e-04 eta: 1:45:48 time: 3.0658 data_time: 0.1251 memory: 27382 grad_norm: 4.3479 loss: 0.5119 bbox_loss: 0.2632 cls_loss: 0.1013 layout_loss: 0.1298 cls_layout_loss: 0.0177 | |
| 2025/09/13 23:25:04 - mmengine - INFO - Epoch(train) [11][ 250/1099] lr: 1.0000e-04 eta: 1:43:09 time: 3.1116 data_time: 0.1504 memory: 31062 grad_norm: 4.0474 loss: 0.5144 bbox_loss: 0.2643 cls_loss: 0.1005 layout_loss: 0.1320 cls_layout_loss: 0.0176 | |
| 2025/09/13 23:27:47 - mmengine - INFO - Epoch(train) [11][ 300/1099] lr: 1.0000e-04 eta: 1:40:30 time: 3.2637 data_time: 0.1572 memory: 32483 grad_norm: 4.0985 loss: 0.5207 bbox_loss: 0.2638 cls_loss: 0.0989 layout_loss: 0.1400 cls_layout_loss: 0.0180 | |
| 2025/09/13 23:30:25 - mmengine - INFO - Epoch(train) [11][ 350/1099] lr: 1.0000e-04 eta: 1:37:51 time: 3.1663 data_time: 0.1636 memory: 26464 grad_norm: 4.1367 loss: 0.5165 bbox_loss: 0.2625 cls_loss: 0.1023 layout_loss: 0.1340 cls_layout_loss: 0.0177 | |
| 2025/09/13 23:33:00 - mmengine - INFO - Epoch(train) [11][ 400/1099] lr: 1.0000e-04 eta: 1:35:12 time: 3.1002 data_time: 0.1281 memory: 29042 grad_norm: 4.1852 loss: 0.5408 bbox_loss: 0.2685 cls_loss: 0.1105 layout_loss: 0.1435 cls_layout_loss: 0.0184 | |
| 2025/09/13 23:35:38 - mmengine - INFO - Epoch(train) [11][ 450/1099] lr: 1.0000e-04 eta: 1:32:33 time: 3.1568 data_time: 0.1439 memory: 28157 grad_norm: 4.8580 loss: 0.5170 bbox_loss: 0.2622 cls_loss: 0.1045 layout_loss: 0.1327 cls_layout_loss: 0.0176 | |
| 2025/09/13 23:38:14 - mmengine - INFO - Epoch(train) [11][ 500/1099] lr: 1.0000e-04 eta: 1:29:54 time: 3.1072 data_time: 0.1544 memory: 31639 grad_norm: 4.6542 loss: 0.5255 bbox_loss: 0.2618 cls_loss: 0.1056 layout_loss: 0.1406 cls_layout_loss: 0.0175 | |
| 2025/09/13 23:40:49 - mmengine - INFO - Epoch(train) [11][ 550/1099] lr: 1.0000e-04 eta: 1:27:14 time: 3.1083 data_time: 0.1582 memory: 26991 grad_norm: 4.3425 loss: 0.5080 bbox_loss: 0.2627 cls_loss: 0.0996 layout_loss: 0.1287 cls_layout_loss: 0.0170 | |
| 2025/09/13 23:43:29 - mmengine - INFO - Epoch(train) [11][ 600/1099] lr: 1.0000e-04 eta: 1:24:36 time: 3.2057 data_time: 0.1368 memory: 26642 grad_norm: 4.6768 loss: 0.5126 bbox_loss: 0.2617 cls_loss: 0.1006 layout_loss: 0.1332 cls_layout_loss: 0.0171 | |
| 2025/09/13 23:46:07 - mmengine - INFO - Epoch(train) [11][ 650/1099] lr: 1.0000e-04 eta: 1:21:57 time: 3.1494 data_time: 0.1370 memory: 25260 grad_norm: 4.1259 loss: 0.5230 bbox_loss: 0.2650 cls_loss: 0.1058 layout_loss: 0.1345 cls_layout_loss: 0.0177 | |
| 2025/09/13 23:48:46 - mmengine - INFO - Epoch(train) [11][ 700/1099] lr: 1.0000e-04 eta: 1:19:18 time: 3.1792 data_time: 0.1751 memory: 27457 grad_norm: 3.9879 loss: 0.5312 bbox_loss: 0.2662 cls_loss: 0.1051 layout_loss: 0.1419 cls_layout_loss: 0.0179 | |
| 2025/09/13 23:51:24 - mmengine - INFO - Epoch(train) [11][ 750/1099] lr: 1.0000e-04 eta: 1:16:39 time: 3.1671 data_time: 0.1915 memory: 30775 grad_norm: 4.4231 loss: 0.5213 bbox_loss: 0.2625 cls_loss: 0.1046 layout_loss: 0.1364 cls_layout_loss: 0.0177 | |
| 2025/09/13 23:54:00 - mmengine - INFO - Epoch(train) [11][ 800/1099] lr: 1.0000e-04 eta: 1:14:00 time: 3.1084 data_time: 0.1613 memory: 27438 grad_norm: 4.0974 loss: 0.5176 bbox_loss: 0.2630 cls_loss: 0.1019 layout_loss: 0.1348 cls_layout_loss: 0.0178 | |
| 2025/09/13 23:56:36 - mmengine - INFO - Epoch(train) [11][ 850/1099] lr: 1.0000e-04 eta: 1:11:21 time: 3.1363 data_time: 0.1515 memory: 29269 grad_norm: 4.3977 loss: 0.5262 bbox_loss: 0.2669 cls_loss: 0.1062 layout_loss: 0.1358 cls_layout_loss: 0.0173 | |
| 2025/09/13 23:59:15 - mmengine - INFO - Epoch(train) [11][ 900/1099] lr: 1.0000e-04 eta: 1:08:42 time: 3.1686 data_time: 0.1432 memory: 29576 grad_norm: 3.8403 loss: 0.5086 bbox_loss: 0.2603 cls_loss: 0.0983 layout_loss: 0.1331 cls_layout_loss: 0.0170 | |
| 2025/09/14 00:01:54 - mmengine - INFO - Epoch(train) [11][ 950/1099] lr: 1.0000e-04 eta: 1:06:03 time: 3.1868 data_time: 0.1856 memory: 29191 grad_norm: 4.2565 loss: 0.5211 bbox_loss: 0.2631 cls_loss: 0.1039 layout_loss: 0.1369 cls_layout_loss: 0.0172 | |
| 2025/09/14 00:04:34 - mmengine - INFO - Epoch(train) [11][1000/1099] lr: 1.0000e-04 eta: 1:03:24 time: 3.1916 data_time: 0.2177 memory: 24668 grad_norm: 4.2230 loss: 0.5002 bbox_loss: 0.2585 cls_loss: 0.1000 layout_loss: 0.1244 cls_layout_loss: 0.0173 | |
| 2025/09/14 00:05:06 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/14 00:07:16 - mmengine - INFO - Epoch(train) [11][1050/1099] lr: 1.0000e-04 eta: 1:00:46 time: 3.2428 data_time: 0.1817 memory: 29108 grad_norm: 4.1869 loss: 0.5162 bbox_loss: 0.2619 cls_loss: 0.1028 layout_loss: 0.1344 cls_layout_loss: 0.0171 | |
| 2025/09/14 00:09:50 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/14 00:09:51 - mmengine - INFO - Saving checkpoint at 11 epochs | |
| 2025/09/14 00:10:29 - mmengine - INFO - Epoch(val) [11][ 50/241] eta: 0:02:20 time: 0.7333 data_time: 0.0618 memory: 28709 | |
| 2025/09/14 00:11:02 - mmengine - INFO - Epoch(val) [11][100/241] eta: 0:01:38 time: 0.6575 data_time: 0.0795 memory: 1369 | |
| 2025/09/14 00:11:35 - mmengine - INFO - Epoch(val) [11][150/241] eta: 0:01:02 time: 0.6642 data_time: 0.0563 memory: 1230 | |
| 2025/09/14 00:12:09 - mmengine - INFO - Epoch(val) [11][200/241] eta: 0:00:28 time: 0.6815 data_time: 0.0778 memory: 1081 | |
| 2025/09/14 00:13:41 - mmengine - INFO - | |
| +---------+-------------+-------------+ | |
| | Layouts | F1 @.25 IoU | F1 @.50 IoU | | |
| +---------+-------------+-------------+ | |
| | wall | 0.8817 | 0.8672 | | |
| | door | 0.9409 | 0.9387 | | |
| | window | 0.8938 | 0.8816 | | |
| +---------+-------------+-------------+ | |
| | Overall | 0.9055 | 0.8958 | | |
| +---------+-------------+-------------+ | |
| 2025/09/14 00:13:41 - mmengine - INFO - Epoch(val) [11][241/241] structured3d: {'layout': {'wall_f1_25': 0.8817000472540413, 'wall_f1_50': 0.8817000472540413, 'door_f1_25': 0.9408538614795029, 'door_f1_50': 0.9408538614795029, 'window_f1_25': 0.8938483506781523, 'window_f1_50': 0.8938483506781523, 'f1_25': 0.9054674198038987, 'f1_50': 0.8958324347292853}} data_time: 0.0684 time: 0.6894 | |
| 2025/09/14 00:16:24 - mmengine - INFO - Epoch(train) [12][ 50/1099] lr: 1.0000e-05 eta: 0:55:32 time: 3.2561 data_time: 0.2547 memory: 27287 grad_norm: 3.8779 loss: 0.5167 bbox_loss: 0.2609 cls_loss: 0.1028 layout_loss: 0.1355 cls_layout_loss: 0.0175 | |
| 2025/09/14 00:19:09 - mmengine - INFO - Epoch(train) [12][ 100/1099] lr: 1.0000e-05 eta: 0:52:53 time: 3.2942 data_time: 0.1935 memory: 30391 grad_norm: 3.5448 loss: 0.5037 bbox_loss: 0.2611 cls_loss: 0.0986 layout_loss: 0.1271 cls_layout_loss: 0.0169 | |
| 2025/09/14 00:21:42 - mmengine - INFO - Epoch(train) [12][ 150/1099] lr: 1.0000e-05 eta: 0:50:14 time: 3.0559 data_time: 0.1328 memory: 27860 grad_norm: 3.6955 loss: 0.5056 bbox_loss: 0.2586 cls_loss: 0.0991 layout_loss: 0.1305 cls_layout_loss: 0.0174 | |
| 2025/09/14 00:24:19 - mmengine - INFO - Epoch(train) [12][ 200/1099] lr: 1.0000e-05 eta: 0:47:35 time: 3.1594 data_time: 0.1415 memory: 29310 grad_norm: 3.9266 loss: 0.5268 bbox_loss: 0.2644 cls_loss: 0.1070 layout_loss: 0.1378 cls_layout_loss: 0.0176 | |
| 2025/09/14 00:27:01 - mmengine - INFO - Epoch(train) [12][ 250/1099] lr: 1.0000e-05 eta: 0:44:56 time: 3.2185 data_time: 0.1654 memory: 27101 grad_norm: 3.6185 loss: 0.5179 bbox_loss: 0.2630 cls_loss: 0.1049 layout_loss: 0.1325 cls_layout_loss: 0.0174 | |
| 2025/09/14 00:29:42 - mmengine - INFO - Epoch(train) [12][ 300/1099] lr: 1.0000e-05 eta: 0:42:18 time: 3.2284 data_time: 0.1851 memory: 30320 grad_norm: 4.1170 loss: 0.5137 bbox_loss: 0.2612 cls_loss: 0.1007 layout_loss: 0.1343 cls_layout_loss: 0.0176 | |
| 2025/09/14 00:32:19 - mmengine - INFO - Epoch(train) [12][ 350/1099] lr: 1.0000e-05 eta: 0:39:39 time: 3.1507 data_time: 0.1659 memory: 27364 grad_norm: 4.0937 loss: 0.5141 bbox_loss: 0.2610 cls_loss: 0.1001 layout_loss: 0.1355 cls_layout_loss: 0.0175 | |
| 2025/09/14 00:34:58 - mmengine - INFO - Epoch(train) [12][ 400/1099] lr: 1.0000e-05 eta: 0:37:00 time: 3.1811 data_time: 0.1634 memory: 26170 grad_norm: 3.4857 loss: 0.5126 bbox_loss: 0.2620 cls_loss: 0.1005 layout_loss: 0.1320 cls_layout_loss: 0.0181 | |
| 2025/09/14 00:37:31 - mmengine - INFO - Epoch(train) [12][ 450/1099] lr: 1.0000e-05 eta: 0:34:21 time: 3.0520 data_time: 0.1524 memory: 31143 grad_norm: 3.8839 loss: 0.5163 bbox_loss: 0.2579 cls_loss: 0.1012 layout_loss: 0.1397 cls_layout_loss: 0.0175 | |
| 2025/09/14 00:40:12 - mmengine - INFO - Epoch(train) [12][ 500/1099] lr: 1.0000e-05 eta: 0:31:42 time: 3.2279 data_time: 0.1601 memory: 29912 grad_norm: 3.9856 loss: 0.5130 bbox_loss: 0.2622 cls_loss: 0.1006 layout_loss: 0.1328 cls_layout_loss: 0.0175 | |
| 2025/09/14 00:42:51 - mmengine - INFO - Epoch(train) [12][ 550/1099] lr: 1.0000e-05 eta: 0:29:03 time: 3.1722 data_time: 0.1299 memory: 35418 grad_norm: 3.5797 loss: 0.5177 bbox_loss: 0.2591 cls_loss: 0.1032 layout_loss: 0.1381 cls_layout_loss: 0.0174 | |
| 2025/09/14 00:45:33 - mmengine - INFO - Epoch(train) [12][ 600/1099] lr: 1.0000e-05 eta: 0:26:25 time: 3.2439 data_time: 0.1699 memory: 30213 grad_norm: 3.7907 loss: 0.5182 bbox_loss: 0.2637 cls_loss: 0.1027 layout_loss: 0.1341 cls_layout_loss: 0.0178 | |
| 2025/09/14 00:48:12 - mmengine - INFO - Epoch(train) [12][ 650/1099] lr: 1.0000e-05 eta: 0:23:46 time: 3.1834 data_time: 0.1411 memory: 27237 grad_norm: 3.7748 loss: 0.5164 bbox_loss: 0.2621 cls_loss: 0.1028 layout_loss: 0.1341 cls_layout_loss: 0.0175 | |
| 2025/09/14 00:50:47 - mmengine - INFO - Epoch(train) [12][ 700/1099] lr: 1.0000e-05 eta: 0:21:07 time: 3.0888 data_time: 0.1263 memory: 26371 grad_norm: 3.8791 loss: 0.5028 bbox_loss: 0.2563 cls_loss: 0.1010 layout_loss: 0.1285 cls_layout_loss: 0.0170 | |
| 2025/09/14 00:53:23 - mmengine - INFO - Epoch(train) [12][ 750/1099] lr: 1.0000e-05 eta: 0:18:28 time: 3.1124 data_time: 0.1606 memory: 25702 grad_norm: 3.9926 loss: 0.4995 bbox_loss: 0.2584 cls_loss: 0.0984 layout_loss: 0.1253 cls_layout_loss: 0.0173 | |
| 2025/09/14 00:56:04 - mmengine - INFO - Epoch(train) [12][ 800/1099] lr: 1.0000e-05 eta: 0:15:49 time: 3.2354 data_time: 0.1767 memory: 34163 grad_norm: 3.9406 loss: 0.5222 bbox_loss: 0.2612 cls_loss: 0.1027 layout_loss: 0.1406 cls_layout_loss: 0.0177 | |
| 2025/09/14 00:58:42 - mmengine - INFO - Epoch(train) [12][ 850/1099] lr: 1.0000e-05 eta: 0:13:10 time: 3.1526 data_time: 0.1498 memory: 31730 grad_norm: 4.0290 loss: 0.5156 bbox_loss: 0.2591 cls_loss: 0.1009 layout_loss: 0.1385 cls_layout_loss: 0.0171 | |
| 2025/09/14 01:01:20 - mmengine - INFO - Epoch(train) [12][ 900/1099] lr: 1.0000e-05 eta: 0:10:32 time: 3.1663 data_time: 0.1558 memory: 28044 grad_norm: 3.8966 loss: 0.4952 bbox_loss: 0.2585 cls_loss: 0.0966 layout_loss: 0.1229 cls_layout_loss: 0.0172 | |
| 2025/09/14 01:01:56 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/14 01:03:54 - mmengine - INFO - Epoch(train) [12][ 950/1099] lr: 1.0000e-05 eta: 0:07:53 time: 3.0727 data_time: 0.1509 memory: 28430 grad_norm: 3.6550 loss: 0.5115 bbox_loss: 0.2593 cls_loss: 0.1023 layout_loss: 0.1323 cls_layout_loss: 0.0175 | |
| 2025/09/14 01:06:37 - mmengine - INFO - Epoch(train) [12][1000/1099] lr: 1.0000e-05 eta: 0:05:14 time: 3.2546 data_time: 0.1218 memory: 28344 grad_norm: 3.6517 loss: 0.5199 bbox_loss: 0.2624 cls_loss: 0.1022 layout_loss: 0.1377 cls_layout_loss: 0.0176 | |
| 2025/09/14 01:09:22 - mmengine - INFO - Epoch(train) [12][1050/1099] lr: 1.0000e-05 eta: 0:02:35 time: 3.2998 data_time: 0.1664 memory: 33331 grad_norm: 3.6780 loss: 0.5153 bbox_loss: 0.2628 cls_loss: 0.1046 layout_loss: 0.1306 cls_layout_loss: 0.0173 | |
| 2025/09/14 01:11:55 - mmengine - INFO - Exp name: tr3d_1xb16_structured3d_v51_20250913_124949 | |
| 2025/09/14 01:11:56 - mmengine - INFO - Saving checkpoint at 12 epochs | |
| 2025/09/14 01:12:36 - mmengine - INFO - Epoch(val) [12][ 50/241] eta: 0:02:29 time: 0.7825 data_time: 0.0855 memory: 36540 | |
| 2025/09/14 01:13:10 - mmengine - INFO - Epoch(val) [12][100/241] eta: 0:01:43 time: 0.6829 data_time: 0.0777 memory: 1369 | |
| 2025/09/14 01:13:44 - mmengine - INFO - Epoch(val) [12][150/241] eta: 0:01:05 time: 0.6947 data_time: 0.0928 memory: 1230 | |
| 2025/09/14 01:14:18 - mmengine - INFO - Epoch(val) [12][200/241] eta: 0:00:28 time: 0.6686 data_time: 0.0812 memory: 1081 | |
| 2025/09/14 01:15:50 - mmengine - INFO - | |
| +---------+-------------+-------------+ | |
| | Layouts | F1 @.25 IoU | F1 @.50 IoU | | |
| +---------+-------------+-------------+ | |
| | wall | 0.8815 | 0.8690 | | |
| | door | 0.9388 | 0.9366 | | |
| | window | 0.8955 | 0.8816 | | |
| +---------+-------------+-------------+ | |
| | Overall | 0.9053 | 0.8957 | | |
| +---------+-------------+-------------+ | |
| 2025/09/14 01:15:50 - mmengine - INFO - Epoch(val) [12][241/241] structured3d: {'layout': {'wall_f1_25': 0.8815168409881027, 'wall_f1_50': 0.8815168409881027, 'door_f1_25': 0.9387956729237671, 'door_f1_50': 0.9387956729237671, 'window_f1_25': 0.8955387510911067, 'window_f1_50': 0.8955387510911067, 'f1_25': 0.9052837550009922, 'f1_50': 0.8957268870155275}} data_time: 0.0814 time: 0.7114 | |