arkit.txt

2024-08-25 04:43:37,932 - mmdet - INFO - Environment info:
------------------------------------------------------------
sys.platform: linux
Python: 3.8.19 (default, Mar 20 2024, 19:58:24) [GCC 11.2.0]
CUDA available: True
GPU 0: NVIDIA GeForce RTX 3090
CUDA_HOME: /usr/local/cuda-11.7
NVCC: Build cuda_11.7.r11.7/compiler.31294372_0
GCC: gcc (Ubuntu 10.5.0-1ubuntu1~22.04) 10.5.0
PyTorch: 1.7.1+cu110
PyTorch compiling details: PyTorch built with:
  - GCC 7.3
  - C++ Version: 201402
  - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications
  - Intel(R) MKL-DNN v1.6.0 (Git Hash 5ef631a030a6f73131c77892041042805a06064f)
  - OpenMP 201511 (a.k.a. OpenMP 4.5)
  - NNPACK is enabled
  - CPU capability usage: AVX2
  - CUDA Runtime 11.0
  - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-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
  - CuDNN 8.0.5
  - Magma 2.5.2
  - Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_VULKAN_WRAPPER -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, 

TorchVision: 0.8.2+cu110
OpenCV: 4.10.0
MMCV: 1.2.7
MMCV Compiler: GCC 7.3
MMCV CUDA Compiler: 11.0
MMDetection: 2.10.0
MMDetection3D: 0.8.0+a5dfdf3
------------------------------------------------------------

2024-08-25 04:43:37,933 - mmdet - INFO - Distributed training: False
2024-08-25 04:43:38,221 - mmdet - INFO - Config:
model = dict(
    type='ImGeoNet',
    pretrained='torchvision://resnet50',
    backbone=dict(
        type='ResNet',
        depth=50,
        num_stages=4,
        out_indices=(0, 1, 2, 3),
        frozen_stages=1,
        norm_cfg=dict(type='BN', requires_grad=False),
        norm_eval=True,
        style='pytorch'),
    neck=dict(
        type='FPN',
        in_channels=[256, 512, 1024, 2048],
        out_channels=256,
        num_outs=4),
    neck_3d=dict(
        type='FastIndoorImVoxelNeck',
        in_channels=256,
        out_channels=128,
        n_blocks=[1, 1, 1]),
    bbox_head=dict(
        type='SunRgbdImVoxelHeadV2',
        n_classes=17,
        n_channels=128,
        n_reg_outs=7,
        n_scales=3,
        limit=27,
        centerness_topk=18),
    occ_head=dict(
        type='OccupancyHead',
        in_channels=512,
        hidden_channels=128,
        n_blocks=[1, 1, 1],
        loss=dict(
            type='FocalLoss',
            use_sigmoid=True,
            gamma=2.0,
            alpha=0.25,
            loss_weight=10.0)),
    voxel_size=(0.16, 0.16, 0.16),
    n_voxels=(40, 40, 16),
    depth_cast_margin=4)
train_cfg = dict()
test_cfg = dict(nms_pre=1000, nms_thr=0.15, use_rotate_nms=True, score_thr=0.0)
img_norm_cfg = dict(
    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
dataset_type = 'ARKitDataset'
data_root = '../data/arkit/'
class_names = ('cabinet', 'refrigerator', 'shelf', 'stove', 'bed', 'sink',
               'washer', 'toilet', 'bathtub', 'oven', 'dishwasher',
               'fireplace', 'stool', 'chair', 'table', 'tv_monitor', 'sofa')
train_pipeline = [
    dict(type='LoadAnnotations3D'),
    dict(
        type='MultiViewPipeline',
        n_images=20,
        transforms=[
            dict(type='LoadImageFromFile'),
            dict(
                type='Normalize',
                mean=[123.675, 116.28, 103.53],
                std=[58.395, 57.12, 57.375],
                to_rgb=True)
        ]),
    dict(type='LoadDepthMap', depth_shift=1000.0),
    dict(type='RandomShiftOrigin', std=(0.7, 0.7, 0.0)),
    dict(
        type='DefaultFormatBundle3D',
        class_names=('cabinet', 'refrigerator', 'shelf', 'stove', 'bed',
                     'sink', 'washer', 'toilet', 'bathtub', 'oven',
                     'dishwasher', 'fireplace', 'stool', 'chair', 'table',
                     'tv_monitor', 'sofa')),
    dict(
        type='Collect3D',
        keys=[
            'img', 'depth_maps', 'depth_masks', 'gt_bboxes_3d', 'gt_labels_3d'
        ])
]
test_pipeline = [
    dict(
        type='MultiViewPipeline',
        n_images=50,
        sample_method='linear',
        transforms=[
            dict(type='LoadImageFromFile'),
            dict(
                type='Normalize',
                mean=[123.675, 116.28, 103.53],
                std=[58.395, 57.12, 57.375],
                to_rgb=True)
        ]),
    dict(
        type='DefaultFormatBundle3D',
        class_names=('cabinet', 'refrigerator', 'shelf', 'stove', 'bed',
                     'sink', 'washer', 'toilet', 'bathtub', 'oven',
                     'dishwasher', 'fireplace', 'stool', 'chair', 'table',
                     'tv_monitor', 'sofa'),
        with_label=False),
    dict(type='Collect3D', keys=['img'])
]
data = dict(
    samples_per_gpu=8,
    workers_per_gpu=8,
    train=dict(
        type='RepeatDataset',
        times=3,
        dataset=dict(
            type='ARKitDataset',
            data_root='../data/arkit/',
            ann_file='../data/arkit/arkit_infos_train.pkl',
            pipeline=[
                dict(type='LoadAnnotations3D'),
                dict(
                    type='MultiViewPipeline',
                    n_images=20,
                    transforms=[
                        dict(type='LoadImageFromFile'),
                        dict(
                            type='Normalize',
                            mean=[123.675, 116.28, 103.53],
                            std=[58.395, 57.12, 57.375],
                            to_rgb=True)
                    ]),
                dict(type='LoadDepthMap', depth_shift=1000.0),
                dict(type='RandomShiftOrigin', std=(0.7, 0.7, 0.0)),
                dict(
                    type='DefaultFormatBundle3D',
                    class_names=('cabinet', 'refrigerator', 'shelf', 'stove',
                                 'bed', 'sink', 'washer', 'toilet', 'bathtub',
                                 'oven', 'dishwasher', 'fireplace', 'stool',
                                 'chair', 'table', 'tv_monitor', 'sofa')),
                dict(
                    type='Collect3D',
                    keys=[
                        'img', 'depth_maps', 'depth_masks', 'gt_bboxes_3d',
                        'gt_labels_3d'
                    ])
            ],
            classes=('cabinet', 'refrigerator', 'shelf', 'stove', 'bed',
                     'sink', 'washer', 'toilet', 'bathtub', 'oven',
                     'dishwasher', 'fireplace', 'stool', 'chair', 'table',
                     'tv_monitor', 'sofa'),
            filter_empty_gt=True,
            box_type_3d='Depth')),
    val=dict(
        type='ARKitDataset',
        data_root='../data/arkit/',
        ann_file='../data/arkit/arkit_infos_val.pkl',
        pipeline=[
            dict(
                type='MultiViewPipeline',
                n_images=50,
                sample_method='linear',
                transforms=[
                    dict(type='LoadImageFromFile'),
                    dict(
                        type='Normalize',
                        mean=[123.675, 116.28, 103.53],
                        std=[58.395, 57.12, 57.375],
                        to_rgb=True)
                ]),
            dict(
                type='DefaultFormatBundle3D',
                class_names=('cabinet', 'refrigerator', 'shelf', 'stove',
                             'bed', 'sink', 'washer', 'toilet', 'bathtub',
                             'oven', 'dishwasher', 'fireplace', 'stool',
                             'chair', 'table', 'tv_monitor', 'sofa'),
                with_label=False),
            dict(type='Collect3D', keys=['img'])
        ],
        classes=('cabinet', 'refrigerator', 'shelf', 'stove', 'bed', 'sink',
                 'washer', 'toilet', 'bathtub', 'oven', 'dishwasher',
                 'fireplace', 'stool', 'chair', 'table', 'tv_monitor', 'sofa'),
        test_mode=True,
        box_type_3d='Depth'),
    test=dict(
        type='ARKitDataset',
        data_root='../data/arkit/',
        ann_file='../data/arkit/arkit_infos_val.pkl',
        pipeline=[
            dict(
                type='MultiViewPipeline',
                n_images=50,
                sample_method='linear',
                transforms=[
                    dict(type='LoadImageFromFile'),
                    dict(
                        type='Normalize',
                        mean=[123.675, 116.28, 103.53],
                        std=[58.395, 57.12, 57.375],
                        to_rgb=True)
                ]),
            dict(
                type='DefaultFormatBundle3D',
                class_names=('cabinet', 'refrigerator', 'shelf', 'stove',
                             'bed', 'sink', 'washer', 'toilet', 'bathtub',
                             'oven', 'dishwasher', 'fireplace', 'stool',
                             'chair', 'table', 'tv_monitor', 'sofa'),
                with_label=False),
            dict(type='Collect3D', keys=['img'])
        ],
        classes=('cabinet', 'refrigerator', 'shelf', 'stove', 'bed', 'sink',
                 'washer', 'toilet', 'bathtub', 'oven', 'dishwasher',
                 'fireplace', 'stool', 'chair', 'table', 'tv_monitor', 'sofa'),
        test_mode=True,
        box_type_3d='Depth'))
optimizer = dict(
    type='AdamW',
    lr=0.0001,
    weight_decay=0.0001,
    paramwise_cfg=dict(
        custom_keys=dict(backbone=dict(lr_mult=0.1, decay_mult=1.0))))
optimizer_config = dict(grad_clip=dict(max_norm=35.0, norm_type=2))
total_epochs = 12
lr_config = dict(policy='step', step=[8, 11])
checkpoint_config = dict(interval=1, max_keep_ckpts=12)
log_config = dict(
    interval=50,
    hooks=[dict(type='TextLoggerHook'),
           dict(type='TensorboardLoggerHook')])
evaluation = dict(interval=1)
dist_params = dict(backend='nccl')
find_unused_parameters = True
log_level = 'INFO'
load_from = None
resume_from = None
workflow = [('train', 1)]
work_dir = 'work_dir/imgeonet_arkit'
gpu_ids = range(0, 1)

2024-08-25 04:43:38,221 - mmdet - INFO - Set random seed to 0, deterministic: False
2024-08-25 04:43:38,622 - mmdet - INFO - load model from: torchvision://resnet50
2024-08-25 04:43:38,622 - mmdet - INFO - Use load_from_torchvision loader
2024-08-25 04:43:39,060 - mmdet - WARNING - The model and loaded state dict do not match exactly

unexpected key in source state_dict: fc.weight, fc.bias

2024-08-25 04:43:39,079 - mmdet - INFO - Model:
ImGeoNet(
  (backbone): ResNet(
    (conv1): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)
    (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (relu): ReLU(inplace=True)
    (maxpool): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)
    (layer1): ResLayer(
      (0): Bottleneck(
        (conv1): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
        (downsample): Sequential(
          (0): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        )
      )
      (1): Bottleneck(
        (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
      )
      (2): Bottleneck(
        (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
      )
    )
    (layer2): ResLayer(
      (0): Bottleneck(
        (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
        (downsample): Sequential(
          (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)
          (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        )
      )
      (1): Bottleneck(
        (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
      )
      (2): Bottleneck(
        (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
      )
      (3): Bottleneck(
        (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
      )
    )
    (layer3): ResLayer(
      (0): Bottleneck(
        (conv1): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
        (downsample): Sequential(
          (0): Conv2d(512, 1024, kernel_size=(1, 1), stride=(2, 2), bias=False)
          (1): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        )
      )
      (1): Bottleneck(
        (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
      )
      (2): Bottleneck(
        (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
      )
      (3): Bottleneck(
        (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
      )
      (4): Bottleneck(
        (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
      )
      (5): Bottleneck(
        (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
      )
    )
    (layer4): ResLayer(
      (0): Bottleneck(
        (conv1): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
        (downsample): Sequential(
          (0): Conv2d(1024, 2048, kernel_size=(1, 1), stride=(2, 2), bias=False)
          (1): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        )
      )
      (1): Bottleneck(
        (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
      )
      (2): Bottleneck(
        (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
      )
    )
  )
  (neck): FPN(
    (lateral_convs): ModuleList(
      (0): ConvModule(
        (conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))
      )
      (1): ConvModule(
        (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))
      )
      (2): ConvModule(
        (conv): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1))
      )
      (3): ConvModule(
        (conv): Conv2d(2048, 256, kernel_size=(1, 1), stride=(1, 1))
      )
    )
    (fpn_convs): ModuleList(
      (0): ConvModule(
        (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
      )
      (1): ConvModule(
        (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
      )
      (2): ConvModule(
        (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
      )
      (3): ConvModule(
        (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
      )
    )
  )
  (neck_3d): FastIndoorImVoxelNeck(
    (down_layer_0): Sequential(
      (0): BasicBlock3dV2(
        (conv1): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
        (norm1): BatchNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
        (conv2): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
        (norm2): BatchNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (out_block_0): Sequential(
      (0): Conv3d(256, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
      (1): BatchNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (2): ReLU(inplace=True)
    )
    (down_layer_1): Sequential(
      (0): BasicBlock3dV2(
        (conv1): Conv3d(256, 512, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1), bias=False)
        (norm1): BatchNorm3d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
        (conv2): Conv3d(512, 512, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
        (norm2): BatchNorm3d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (downsample): Sequential(
          (0): Conv3d(256, 512, kernel_size=(1, 1, 1), stride=(2, 2, 2), bias=False)
          (1): BatchNorm3d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        )
      )
    )
    (up_block_1): Sequential(
      (0): ConvTranspose3d(512, 256, kernel_size=(2, 2, 2), stride=(2, 2, 2), bias=False)
      (1): BatchNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (2): ReLU(inplace=True)
      (3): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
      (4): BatchNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (5): ReLU(inplace=True)
    )
    (out_block_1): Sequential(
      (0): Conv3d(512, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
      (1): BatchNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (2): ReLU(inplace=True)
    )
    (down_layer_2): Sequential(
      (0): BasicBlock3dV2(
        (conv1): Conv3d(512, 1024, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1), bias=False)
        (norm1): BatchNorm3d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace=True)
        (conv2): Conv3d(1024, 1024, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
        (norm2): BatchNorm3d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (downsample): Sequential(
          (0): Conv3d(512, 1024, kernel_size=(1, 1, 1), stride=(2, 2, 2), bias=False)
          (1): BatchNorm3d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        )
      )
    )
    (up_block_2): Sequential(
      (0): ConvTranspose3d(1024, 512, kernel_size=(2, 2, 2), stride=(2, 2, 2), bias=False)
      (1): BatchNorm3d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (2): ReLU(inplace=True)
      (3): Conv3d(512, 512, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
      (4): BatchNorm3d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (5): ReLU(inplace=True)
    )
    (out_block_2): Sequential(
      (0): Conv3d(1024, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
      (1): BatchNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (2): ReLU(inplace=True)
    )
  )
  (bbox_head): SunRgbdImVoxelHeadV2(
    (loss_centerness): CrossEntropyLoss()
    (loss_bbox): IoU3DLoss()
    (loss_cls): FocalLoss()
    (centerness_conv): Conv3d(128, 1, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
    (reg_conv): Conv3d(128, 7, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
    (cls_conv): Conv3d(128, 17, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))
    (scales): ModuleList(
      (0): Scale()
      (1): Scale()
      (2): Scale()
    )
  )
  (occ_head): OccupancyHead(
    (pre_proj): Sequential(
      (0): Conv3d(512, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))
      (1): LeakyReLU(negative_slope=0.01)
    )
    (net): OccupancyNet(
      (down_layer_0): Sequential(
        (0): BasicBlock3dV2(
          (conv1): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
          (norm1): BatchNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
          (relu): ReLU(inplace=True)
          (conv2): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
          (norm2): BatchNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        )
      )
      (out_block_0): Sequential(
        (0): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
        (1): BatchNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (2): ReLU(inplace=True)
      )
      (down_layer_1): Sequential(
        (0): BasicBlock3dV2(
          (conv1): Conv3d(128, 256, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1), bias=False)
          (norm1): BatchNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
          (relu): ReLU(inplace=True)
          (conv2): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
          (norm2): BatchNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
          (downsample): Sequential(
            (0): Conv3d(128, 256, kernel_size=(1, 1, 1), stride=(2, 2, 2), bias=False)
            (1): BatchNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
          )
        )
      )
      (up_block_1): Sequential(
        (0): ConvTranspose3d(256, 128, kernel_size=(2, 2, 2), stride=(2, 2, 2), bias=False)
        (1): BatchNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (2): ReLU(inplace=True)
        (3): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
        (4): BatchNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (5): ReLU(inplace=True)
      )
      (out_block_1): Sequential(
        (0): Conv3d(256, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
        (1): BatchNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (2): ReLU(inplace=True)
      )
      (down_layer_2): Sequential(
        (0): BasicBlock3dV2(
          (conv1): Conv3d(256, 512, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1), bias=False)
          (norm1): BatchNorm3d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
          (relu): ReLU(inplace=True)
          (conv2): Conv3d(512, 512, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
          (norm2): BatchNorm3d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
          (downsample): Sequential(
            (0): Conv3d(256, 512, kernel_size=(1, 1, 1), stride=(2, 2, 2), bias=False)
            (1): BatchNorm3d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
          )
        )
      )
      (up_block_2): Sequential(
        (0): ConvTranspose3d(512, 256, kernel_size=(2, 2, 2), stride=(2, 2, 2), bias=False)
        (1): BatchNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (2): ReLU(inplace=True)
        (3): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
        (4): BatchNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (5): ReLU(inplace=True)
      )
      (out_block_2): Sequential(
        (0): Conv3d(512, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
        (1): BatchNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (2): ReLU(inplace=True)
      )
    )
    (post_proj): Conv3d(128, 1, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), bias=False)
    (loss): FocalLoss()
  )
)
2024-08-25 04:43:45,277 - mmdet - INFO - Start running, host: ttao@mercury, work_dir: /home/ttao/Repository/imgeonet2/mmdetection3d/work_dir/imgeonet_arkit
2024-08-25 04:43:45,277 - mmdet - INFO - workflow: [('train', 1)], max: 12 epochs
2024-08-25 04:46:00,383 - mmdet - INFO - Epoch [1][50/1685]	lr: 1.000e-04, eta: 15:07:55, time: 2.701, data_time: 0.136, memory: 19396, loss_occ: 0.7530, acc_occ: 0.7815, loss_centerness: 0.6479, loss_bbox: 0.7035, loss_cls: 0.7751, loss: 2.8795, grad_norm: 7.1633
2024-08-25 04:48:10,042 - mmdet - INFO - Epoch [1][100/1685]	lr: 1.000e-04, eta: 14:47:37, time: 2.593, data_time: 0.013, memory: 19399, loss_occ: 0.6882, acc_occ: 0.7968, loss_centerness: 0.6397, loss_bbox: 0.6642, loss_cls: 0.6782, loss: 2.6703, grad_norm: 4.9641
2024-08-25 04:50:22,900 - mmdet - INFO - Epoch [1][150/1685]	lr: 1.000e-04, eta: 14:46:33, time: 2.657, data_time: 0.013, memory: 19399, loss_occ: 0.6781, acc_occ: 0.7934, loss_centerness: 0.6397, loss_bbox: 0.6559, loss_cls: 0.6401, loss: 2.6137, grad_norm: 4.8845
2024-08-25 04:52:38,035 - mmdet - INFO - Epoch [1][200/1685]	lr: 1.000e-04, eta: 14:48:42, time: 2.703, data_time: 0.010, memory: 19399, loss_occ: 0.6737, acc_occ: 0.7967, loss_centerness: 0.6405, loss_bbox: 0.6408, loss_cls: 0.6117, loss: 2.5667, grad_norm: 4.9208
2024-08-25 04:54:53,162 - mmdet - INFO - Epoch [1][250/1685]	lr: 1.000e-04, eta: 14:49:05, time: 2.703, data_time: 0.010, memory: 19399, loss_occ: 0.6717, acc_occ: 0.7984, loss_centerness: 0.6351, loss_bbox: 0.6316, loss_cls: 0.5911, loss: 2.5296, grad_norm: 4.3724
2024-08-25 04:57:08,680 - mmdet - INFO - Epoch [1][300/1685]	lr: 1.000e-04, eta: 14:49:01, time: 2.710, data_time: 0.010, memory: 19410, loss_occ: 0.6472, acc_occ: 0.8050, loss_centerness: 0.6374, loss_bbox: 0.6222, loss_cls: 0.5376, loss: 2.4445, grad_norm: 4.0634
2024-08-25 04:59:24,177 - mmdet - INFO - Epoch [1][350/1685]	lr: 1.000e-04, eta: 14:48:18, time: 2.710, data_time: 0.009, memory: 19410, loss_occ: 0.6530, acc_occ: 0.8051, loss_centerness: 0.6366, loss_bbox: 0.6241, loss_cls: 0.5426, loss: 2.4563, grad_norm: 4.6100
2024-08-25 05:01:39,493 - mmdet - INFO - Epoch [1][400/1685]	lr: 1.000e-04, eta: 14:47:04, time: 2.706, data_time: 0.010, memory: 19410, loss_occ: 0.6674, acc_occ: 0.7959, loss_centerness: 0.6349, loss_bbox: 0.6172, loss_cls: 0.5310, loss: 2.4504, grad_norm: 4.0903
2024-08-25 05:04:00,242 - mmdet - INFO - Epoch [1][450/1685]	lr: 1.000e-04, eta: 14:49:34, time: 2.815, data_time: 0.010, memory: 19410, loss_occ: 0.6484, acc_occ: 0.8020, loss_centerness: 0.6367, loss_bbox: 0.6199, loss_cls: 0.5880, loss: 2.4930, grad_norm: 4.6299
2024-08-25 05:06:23,133 - mmdet - INFO - Epoch [1][500/1685]	lr: 1.000e-04, eta: 14:52:31, time: 2.858, data_time: 0.011, memory: 19410, loss_occ: 0.6365, acc_occ: 0.8041, loss_centerness: 0.6372, loss_bbox: 0.6081, loss_cls: 0.5163, loss: 2.3981, grad_norm: 4.3552
2024-08-25 05:08:49,061 - mmdet - INFO - Epoch [1][550/1685]	lr: 1.000e-04, eta: 14:56:18, time: 2.919, data_time: 0.010, memory: 19410, loss_occ: 0.6385, acc_occ: 0.8088, loss_centerness: 0.6307, loss_bbox: 0.6062, loss_cls: 0.4931, loss: 2.3685, grad_norm: 4.4042
2024-08-25 05:11:14,906 - mmdet - INFO - Epoch [1][600/1685]	lr: 1.000e-04, eta: 14:59:00, time: 2.917, data_time: 0.010, memory: 19410, loss_occ: 0.6297, acc_occ: 0.8057, loss_centerness: 0.6342, loss_bbox: 0.6068, loss_cls: 0.4947, loss: 2.3653, grad_norm: 4.0112
2024-08-25 05:13:38,232 - mmdet - INFO - Epoch [1][650/1685]	lr: 1.000e-04, eta: 14:59:39, time: 2.867, data_time: 0.010, memory: 19412, loss_occ: 0.6311, acc_occ: 0.8086, loss_centerness: 0.6351, loss_bbox: 0.5973, loss_cls: 0.4791, loss: 2.3426, grad_norm: 3.9083
2024-08-25 05:16:01,247 - mmdet - INFO - Epoch [1][700/1685]	lr: 1.000e-04, eta: 14:59:44, time: 2.860, data_time: 0.011, memory: 19412, loss_occ: 0.6197, acc_occ: 0.8054, loss_centerness: 0.6316, loss_bbox: 0.5964, loss_cls: 0.4686, loss: 2.3163, grad_norm: 4.1393
2024-08-25 05:18:23,790 - mmdet - INFO - Epoch [1][750/1685]	lr: 1.000e-04, eta: 14:59:16, time: 2.851, data_time: 0.011, memory: 19412, loss_occ: 0.6317, acc_occ: 0.8037, loss_centerness: 0.6326, loss_bbox: 0.5978, loss_cls: 0.5048, loss: 2.3669, grad_norm: 4.6149
2024-08-25 05:20:50,908 - mmdet - INFO - Epoch [1][800/1685]	lr: 1.000e-04, eta: 15:00:25, time: 2.942, data_time: 0.013, memory: 19412, loss_occ: 0.6313, acc_occ: 0.8116, loss_centerness: 0.6292, loss_bbox: 0.5869, loss_cls: 0.4538, loss: 2.3013, grad_norm: 4.0275
2024-08-25 05:23:18,319 - mmdet - INFO - Epoch [1][850/1685]	lr: 1.000e-04, eta: 15:01:15, time: 2.948, data_time: 0.014, memory: 19412, loss_occ: 0.6193, acc_occ: 0.8110, loss_centerness: 0.6280, loss_bbox: 0.5833, loss_cls: 0.4493, loss: 2.2798, grad_norm: 3.9784
2024-08-25 05:25:47,568 - mmdet - INFO - Epoch [1][900/1685]	lr: 1.000e-04, eta: 15:02:23, time: 2.985, data_time: 0.014, memory: 19414, loss_occ: 0.6124, acc_occ: 0.8126, loss_centerness: 0.6281, loss_bbox: 0.5822, loss_cls: 0.4605, loss: 2.2832, grad_norm: 4.3195
2024-08-25 05:28:18,585 - mmdet - INFO - Epoch [1][950/1685]	lr: 1.000e-04, eta: 15:03:44, time: 3.020, data_time: 0.014, memory: 19414, loss_occ: 0.6076, acc_occ: 0.8155, loss_centerness: 0.6288, loss_bbox: 0.5760, loss_cls: 0.4424, loss: 2.2548, grad_norm: 3.9813
2024-08-25 05:30:48,797 - mmdet - INFO - Epoch [1][1000/1685]	lr: 1.000e-04, eta: 15:04:26, time: 3.004, data_time: 0.014, memory: 19414, loss_occ: 0.6200, acc_occ: 0.8182, loss_centerness: 0.6316, loss_bbox: 0.5779, loss_cls: 0.4405, loss: 2.2700, grad_norm: 3.8881
2024-08-25 05:33:19,347 - mmdet - INFO - Epoch [1][1050/1685]	lr: 1.000e-04, eta: 15:04:56, time: 3.011, data_time: 0.016, memory: 19414, loss_occ: 0.5942, acc_occ: 0.8155, loss_centerness: 0.6315, loss_bbox: 0.5750, loss_cls: 0.4317, loss: 2.2324, grad_norm: 3.9129
2024-08-25 05:35:49,927 - mmdet - INFO - Epoch [1][1100/1685]	lr: 1.000e-04, eta: 15:05:10, time: 3.012, data_time: 0.014, memory: 19414, loss_occ: 0.6179, acc_occ: 0.8145, loss_centerness: 0.6290, loss_bbox: 0.5760, loss_cls: 0.4315, loss: 2.2544, grad_norm: 4.4633
2024-08-25 05:38:16,964 - mmdet - INFO - Epoch [1][1150/1685]	lr: 1.000e-04, eta: 15:04:11, time: 2.941, data_time: 0.014, memory: 19414, loss_occ: 0.6089, acc_occ: 0.8205, loss_centerness: 0.6279, loss_bbox: 0.5778, loss_cls: 0.4379, loss: 2.2524, grad_norm: 4.0958
2024-08-25 05:40:44,532 - mmdet - INFO - Epoch [1][1200/1685]	lr: 1.000e-04, eta: 15:03:14, time: 2.951, data_time: 0.014, memory: 19414, loss_occ: 0.6237, acc_occ: 0.8206, loss_centerness: 0.6283, loss_bbox: 0.5693, loss_cls: 0.4194, loss: 2.2407, grad_norm: 3.9373
2024-08-25 05:43:15,003 - mmdet - INFO - Epoch [1][1250/1685]	lr: 1.000e-04, eta: 15:02:53, time: 3.009, data_time: 0.014, memory: 19414, loss_occ: 0.6039, acc_occ: 0.8246, loss_centerness: 0.6270, loss_bbox: 0.5668, loss_cls: 0.4328, loss: 2.2306, grad_norm: 4.4634
2024-08-25 05:45:43,830 - mmdet - INFO - Epoch [1][1300/1685]	lr: 1.000e-04, eta: 15:01:58, time: 2.977, data_time: 0.014, memory: 19414, loss_occ: 0.5973, acc_occ: 0.8245, loss_centerness: 0.6317, loss_bbox: 0.5623, loss_cls: 0.4226, loss: 2.2139, grad_norm: 4.2927
2024-08-25 05:48:09,260 - mmdet - INFO - Epoch [1][1350/1685]	lr: 1.000e-04, eta: 15:00:08, time: 2.909, data_time: 0.014, memory: 19414, loss_occ: 0.6181, acc_occ: 0.8210, loss_centerness: 0.6312, loss_bbox: 0.5625, loss_cls: 0.4107, loss: 2.2224, grad_norm: 4.0398
2024-08-25 05:50:33,620 - mmdet - INFO - Epoch [1][1400/1685]	lr: 1.000e-04, eta: 14:58:02, time: 2.887, data_time: 0.015, memory: 19414, loss_occ: 0.6022, acc_occ: 0.8289, loss_centerness: 0.6274, loss_bbox: 0.5576, loss_cls: 0.4067, loss: 2.1939, grad_norm: 4.2058
2024-08-25 05:53:05,379 - mmdet - INFO - Epoch [1][1450/1685]	lr: 1.000e-04, eta: 14:57:30, time: 3.035, data_time: 0.013, memory: 19414, loss_occ: 0.5976, acc_occ: 0.8232, loss_centerness: 0.6286, loss_bbox: 0.5562, loss_cls: 0.4098, loss: 2.1921, grad_norm: 3.8393
2024-08-25 05:55:31,726 - mmdet - INFO - Epoch [1][1500/1685]	lr: 1.000e-04, eta: 14:55:43, time: 2.927, data_time: 0.011, memory: 19414, loss_occ: 0.6092, acc_occ: 0.8226, loss_centerness: 0.6287, loss_bbox: 0.5548, loss_cls: 0.4126, loss: 2.2052, grad_norm: 4.1663
2024-08-25 05:57:58,446 - mmdet - INFO - Epoch [1][1550/1685]	lr: 1.000e-04, eta: 14:53:58, time: 2.934, data_time: 0.011, memory: 19414, loss_occ: 0.5949, acc_occ: 0.8251, loss_centerness: 0.6276, loss_bbox: 0.5533, loss_cls: 0.4069, loss: 2.1828, grad_norm: 3.9826
2024-08-25 06:00:26,042 - mmdet - INFO - Epoch [1][1600/1685]	lr: 1.000e-04, eta: 14:52:20, time: 2.952, data_time: 0.012, memory: 19414, loss_occ: 0.6056, acc_occ: 0.8284, loss_centerness: 0.6276, loss_bbox: 0.5457, loss_cls: 0.3955, loss: 2.1743, grad_norm: 4.3637
2024-08-25 06:02:52,519 - mmdet - INFO - Epoch [1][1650/1685]	lr: 1.000e-04, eta: 14:50:27, time: 2.930, data_time: 0.014, memory: 19414, loss_occ: 0.5962, acc_occ: 0.8171, loss_centerness: 0.6272, loss_bbox: 0.5638, loss_cls: 0.4812, loss: 2.2684, grad_norm: 5.0648
2024-08-25 06:04:33,130 - mmdet - INFO - Saving checkpoint at 1 epochs
2024-08-25 06:06:46,539 - mmdet - INFO - 
+--------------+---------+---------+---------+---------+
| classes      | AP_0.25 | AR_0.25 | AP_0.50 | AR_0.50 |
+--------------+---------+---------+---------+---------+
| sofa         | 0.6568  | 0.8215  | 0.1692  | 0.3491  |
| cabinet      | 0.3546  | 0.5831  | 0.0525  | 0.1517  |
| chair        | 0.4679  | 0.7388  | 0.1010  | 0.2362  |
| table        | 0.3309  | 0.7467  | 0.0388  | 0.1993  |
| toilet       | 0.8643  | 0.9174  | 0.5271  | 0.6281  |
| stool        | 0.0398  | 0.3763  | 0.0071  | 0.0376  |
| sink         | 0.2367  | 0.3217  | 0.0144  | 0.0669  |
| shelf        | 0.1658  | 0.4660  | 0.0035  | 0.0631  |
| refrigerator | 0.4170  | 0.9024  | 0.1919  | 0.4512  |
| tv_monitor   | 0.0000  | 0.0000  | 0.0000  | 0.0000  |
| washer       | 0.6672  | 0.8596  | 0.4499  | 0.5877  |
| oven         | 0.3184  | 0.5584  | 0.0881  | 0.2273  |
| bathtub      | 0.9206  | 0.9592  | 0.4246  | 0.5408  |
| bed          | 0.7916  | 0.9337  | 0.4325  | 0.5470  |
| fireplace    | 0.3206  | 0.6111  | 0.0226  | 0.1296  |
| dishwasher   | 0.0323  | 0.8400  | 0.0097  | 0.4000  |
| stove        | 0.0041  | 0.0510  | 0.0000  | 0.0000  |
+--------------+---------+---------+---------+---------+
| Overall      | 0.3876  | 0.6287  | 0.1490  | 0.2715  |
+--------------+---------+---------+---------+---------+
2024-08-25 06:06:47,081 - mmdet - INFO - Epoch(val) [1][1685]	sofa_AP_0.25: 0.6568, cabinet_AP_0.25: 0.3546, chair_AP_0.25: 0.4679, table_AP_0.25: 0.3309, toilet_AP_0.25: 0.8643, stool_AP_0.25: 0.0398, sink_AP_0.25: 0.2367, shelf_AP_0.25: 0.1658, refrigerator_AP_0.25: 0.4170, tv_monitor_AP_0.25: 0.0000, washer_AP_0.25: 0.6672, oven_AP_0.25: 0.3184, bathtub_AP_0.25: 0.9206, bed_AP_0.25: 0.7916, fireplace_AP_0.25: 0.3206, dishwasher_AP_0.25: 0.0323, stove_AP_0.25: 0.0041, mAP_0.25: 0.3876, sofa_rec_0.25: 0.8215, cabinet_rec_0.25: 0.5831, chair_rec_0.25: 0.7388, table_rec_0.25: 0.7467, toilet_rec_0.25: 0.9174, stool_rec_0.25: 0.3763, sink_rec_0.25: 0.3217, shelf_rec_0.25: 0.4660, refrigerator_rec_0.25: 0.9024, tv_monitor_rec_0.25: 0.0000, washer_rec_0.25: 0.8596, oven_rec_0.25: 0.5584, bathtub_rec_0.25: 0.9592, bed_rec_0.25: 0.9337, fireplace_rec_0.25: 0.6111, dishwasher_rec_0.25: 0.8400, stove_rec_0.25: 0.0510, mAR_0.25: 0.6287, sofa_AP_0.50: 0.1692, cabinet_AP_0.50: 0.0525, chair_AP_0.50: 0.1010, table_AP_0.50: 0.0388, toilet_AP_0.50: 0.5271, stool_AP_0.50: 0.0071, sink_AP_0.50: 0.0144, shelf_AP_0.50: 0.0035, refrigerator_AP_0.50: 0.1919, tv_monitor_AP_0.50: 0.0000, washer_AP_0.50: 0.4499, oven_AP_0.50: 0.0881, bathtub_AP_0.50: 0.4246, bed_AP_0.50: 0.4325, fireplace_AP_0.50: 0.0226, dishwasher_AP_0.50: 0.0097, stove_AP_0.50: 0.0000, mAP_0.50: 0.1490, sofa_rec_0.50: 0.3491, cabinet_rec_0.50: 0.1517, chair_rec_0.50: 0.2362, table_rec_0.50: 0.1993, toilet_rec_0.50: 0.6281, stool_rec_0.50: 0.0376, sink_rec_0.50: 0.0669, shelf_rec_0.50: 0.0631, refrigerator_rec_0.50: 0.4512, tv_monitor_rec_0.50: 0.0000, washer_rec_0.50: 0.5877, oven_rec_0.50: 0.2273, bathtub_rec_0.50: 0.5408, bed_rec_0.50: 0.5470, fireplace_rec_0.50: 0.1296, dishwasher_rec_0.50: 0.4000, stove_rec_0.50: 0.0000, mAR_0.50: 0.2715
2024-08-25 06:09:23,314 - mmdet - INFO - Epoch [2][50/1685]	lr: 1.000e-04, eta: 14:30:41, time: 3.124, data_time: 0.136, memory: 19414, loss_occ: 0.6057, acc_occ: 0.8204, loss_centerness: 0.6242, loss_bbox: 0.5524, loss_cls: 0.4331, loss: 2.2153, grad_norm: 4.3275
2024-08-25 06:11:50,115 - mmdet - INFO - Epoch [2][100/1685]	lr: 1.000e-04, eta: 14:29:16, time: 2.936, data_time: 0.011, memory: 19414, loss_occ: 0.5867, acc_occ: 0.8319, loss_centerness: 0.6308, loss_bbox: 0.5451, loss_cls: 0.3937, loss: 2.1563, grad_norm: 3.7693
2024-08-25 06:14:18,137 - mmdet - INFO - Epoch [2][150/1685]	lr: 1.000e-04, eta: 14:28:01, time: 2.960, data_time: 0.010, memory: 19414, loss_occ: 0.6112, acc_occ: 0.8295, loss_centerness: 0.6287, loss_bbox: 0.5443, loss_cls: 0.3968, loss: 2.1811, grad_norm: 3.8565
2024-08-25 06:16:45,754 - mmdet - INFO - Epoch [2][200/1685]	lr: 1.000e-04, eta: 14:26:37, time: 2.952, data_time: 0.011, memory: 19414, loss_occ: 0.5993, acc_occ: 0.8341, loss_centerness: 0.6259, loss_bbox: 0.5411, loss_cls: 0.3863, loss: 2.1526, grad_norm: 3.9392
2024-08-25 06:19:10,514 - mmdet - INFO - Epoch [2][250/1685]	lr: 1.000e-04, eta: 14:24:43, time: 2.895, data_time: 0.013, memory: 19414, loss_occ: 0.5868, acc_occ: 0.8419, loss_centerness: 0.6256, loss_bbox: 0.5384, loss_cls: 0.3769, loss: 2.1278, grad_norm: 3.8981
2024-08-25 06:21:35,948 - mmdet - INFO - Epoch [2][300/1685]	lr: 1.000e-04, eta: 14:22:54, time: 2.909, data_time: 0.015, memory: 19414, loss_occ: 0.5943, acc_occ: 0.8382, loss_centerness: 0.6245, loss_bbox: 0.5395, loss_cls: 0.3695, loss: 2.1277, grad_norm: 4.0979
2024-08-25 06:24:03,203 - mmdet - INFO - Epoch [2][350/1685]	lr: 1.000e-04, eta: 14:21:19, time: 2.945, data_time: 0.015, memory: 19414, loss_occ: 0.5810, acc_occ: 0.8370, loss_centerness: 0.6211, loss_bbox: 0.5425, loss_cls: 0.4049, loss: 2.1496, grad_norm: 4.1070
2024-08-25 06:26:29,571 - mmdet - INFO - Epoch [2][400/1685]	lr: 1.000e-04, eta: 14:19:34, time: 2.927, data_time: 0.014, memory: 19414, loss_occ: 0.5793, acc_occ: 0.8407, loss_centerness: 0.6285, loss_bbox: 0.5366, loss_cls: 0.3796, loss: 2.1240, grad_norm: 3.8638
2024-08-25 06:28:54,388 - mmdet - INFO - Epoch [2][450/1685]	lr: 1.000e-04, eta: 14:17:34, time: 2.896, data_time: 0.013, memory: 19414, loss_occ: 0.5770, acc_occ: 0.8378, loss_centerness: 0.6227, loss_bbox: 0.5301, loss_cls: 0.3770, loss: 2.1068, grad_norm: 3.9299
2024-08-25 06:31:20,738 - mmdet - INFO - Epoch [2][500/1685]	lr: 1.000e-04, eta: 14:15:46, time: 2.927, data_time: 0.012, memory: 19414, loss_occ: 0.5901, acc_occ: 0.8364, loss_centerness: 0.6264, loss_bbox: 0.5348, loss_cls: 0.3726, loss: 2.1240, grad_norm: 3.9235
2024-08-25 06:33:44,454 - mmdet - INFO - Epoch [2][550/1685]	lr: 1.000e-04, eta: 14:13:35, time: 2.874, data_time: 0.012, memory: 19414, loss_occ: 0.5848, acc_occ: 0.8362, loss_centerness: 0.6233, loss_bbox: 0.5339, loss_cls: 0.3720, loss: 2.1141, grad_norm: 4.0677
2024-08-25 06:36:03,212 - mmdet - INFO - Epoch [2][600/1685]	lr: 1.000e-04, eta: 14:10:44, time: 2.775, data_time: 0.014, memory: 19414, loss_occ: 0.5835, acc_occ: 0.8391, loss_centerness: 0.6226, loss_bbox: 0.5367, loss_cls: 0.3807, loss: 2.1235, grad_norm: 3.8275
2024-08-25 06:38:20,951 - mmdet - INFO - Epoch [2][650/1685]	lr: 1.000e-04, eta: 14:07:46, time: 2.755, data_time: 0.010, memory: 19414, loss_occ: 0.5887, acc_occ: 0.8311, loss_centerness: 0.6220, loss_bbox: 0.5331, loss_cls: 0.4456, loss: 2.1894, grad_norm: 5.0562
2024-08-25 06:40:40,237 - mmdet - INFO - Epoch [2][700/1685]	lr: 1.000e-04, eta: 14:05:02, time: 2.786, data_time: 0.010, memory: 19414, loss_occ: 0.5986, acc_occ: 0.8325, loss_centerness: 0.6262, loss_bbox: 0.5417, loss_cls: 0.4084, loss: 2.1749, grad_norm: 3.7099
2024-08-25 06:43:01,110 - mmdet - INFO - Epoch [2][750/1685]	lr: 1.000e-04, eta: 14:02:31, time: 2.817, data_time: 0.010, memory: 19414, loss_occ: 0.5826, acc_occ: 0.8406, loss_centerness: 0.6266, loss_bbox: 0.5357, loss_cls: 0.3887, loss: 2.1336, grad_norm: 3.7907
2024-08-25 06:45:20,425 - mmdet - INFO - Epoch [2][800/1685]	lr: 1.000e-04, eta: 13:59:49, time: 2.786, data_time: 0.012, memory: 19414, loss_occ: 0.5969, acc_occ: 0.8378, loss_centerness: 0.6189, loss_bbox: 0.5315, loss_cls: 0.3712, loss: 2.1185, grad_norm: 3.8306
2024-08-25 06:47:38,483 - mmdet - INFO - Epoch [2][850/1685]	lr: 1.000e-04, eta: 13:56:59, time: 2.761, data_time: 0.014, memory: 19414, loss_occ: 0.5871, acc_occ: 0.8383, loss_centerness: 0.6220, loss_bbox: 0.5319, loss_cls: 0.3748, loss: 2.1159, grad_norm: 3.9907
2024-08-25 06:50:00,347 - mmdet - INFO - Epoch [2][900/1685]	lr: 1.000e-04, eta: 13:54:36, time: 2.837, data_time: 0.013, memory: 19414, loss_occ: 0.5880, acc_occ: 0.8432, loss_centerness: 0.6256, loss_bbox: 0.5327, loss_cls: 0.3778, loss: 2.1241, grad_norm: 4.2937
2024-08-25 06:52:27,270 - mmdet - INFO - Epoch [2][950/1685]	lr: 1.000e-04, eta: 13:52:47, time: 2.938, data_time: 0.015, memory: 19414, loss_occ: 0.5857, acc_occ: 0.8415, loss_centerness: 0.6249, loss_bbox: 0.5249, loss_cls: 0.3674, loss: 2.1030, grad_norm: 3.8771
2024-08-25 06:54:57,635 - mmdet - INFO - Epoch [2][1000/1685]	lr: 1.000e-04, eta: 13:51:19, time: 3.007, data_time: 0.015, memory: 19414, loss_occ: 0.5784, acc_occ: 0.8440, loss_centerness: 0.6232, loss_bbox: 0.5240, loss_cls: 0.3596, loss: 2.0852, grad_norm: 3.9778
2024-08-25 06:57:25,461 - mmdet - INFO - Epoch [2][1050/1685]	lr: 1.000e-04, eta: 13:49:33, time: 2.957, data_time: 0.013, memory: 19414, loss_occ: 0.5943, acc_occ: 0.8450, loss_centerness: 0.6250, loss_bbox: 0.5199, loss_cls: 0.3622, loss: 2.1014, grad_norm: 3.8302
2024-08-25 06:59:52,441 - mmdet - INFO - Epoch [2][1100/1685]	lr: 1.000e-04, eta: 13:47:39, time: 2.940, data_time: 0.011, memory: 19414, loss_occ: 0.5742, acc_occ: 0.8465, loss_centerness: 0.6236, loss_bbox: 0.5218, loss_cls: 0.3578, loss: 2.0774, grad_norm: 3.8936
2024-08-25 07:02:18,744 - mmdet - INFO - Epoch [2][1150/1685]	lr: 1.000e-04, eta: 13:45:41, time: 2.926, data_time: 0.011, memory: 19414, loss_occ: 0.5870, acc_occ: 0.8449, loss_centerness: 0.6263, loss_bbox: 0.5238, loss_cls: 0.3580, loss: 2.0951, grad_norm: 3.7640
2024-08-25 07:04:47,600 - mmdet - INFO - Epoch [2][1200/1685]	lr: 1.000e-04, eta: 13:43:57, time: 2.977, data_time: 0.011, memory: 19414, loss_occ: 0.5760, acc_occ: 0.8462, loss_centerness: 0.6242, loss_bbox: 0.5196, loss_cls: 0.3556, loss: 2.0755, grad_norm: 3.7800
2024-08-25 07:07:15,564 - mmdet - INFO - Epoch [2][1250/1685]	lr: 1.000e-04, eta: 13:42:06, time: 2.959, data_time: 0.010, memory: 19414, loss_occ: 0.5800, acc_occ: 0.8433, loss_centerness: 0.6219, loss_bbox: 0.5218, loss_cls: 0.3732, loss: 2.0969, grad_norm: 4.2597
2024-08-25 07:09:43,564 - mmdet - INFO - Epoch [2][1300/1685]	lr: 1.000e-04, eta: 13:40:14, time: 2.960, data_time: 0.010, memory: 19414, loss_occ: 0.5670, acc_occ: 0.8494, loss_centerness: 0.6251, loss_bbox: 0.5232, loss_cls: 0.3622, loss: 2.0776, grad_norm: 4.0014
2024-08-25 07:12:08,520 - mmdet - INFO - Epoch [2][1350/1685]	lr: 1.000e-04, eta: 13:38:03, time: 2.899, data_time: 0.011, memory: 19414, loss_occ: 0.5760, acc_occ: 0.8545, loss_centerness: 0.6228, loss_bbox: 0.5156, loss_cls: 0.3549, loss: 2.0694, grad_norm: 4.0796
2024-08-25 07:14:35,793 - mmdet - INFO - Epoch [2][1400/1685]	lr: 1.000e-04, eta: 13:36:05, time: 2.945, data_time: 0.010, memory: 19414, loss_occ: 0.5654, acc_occ: 0.8513, loss_centerness: 0.6186, loss_bbox: 0.5114, loss_cls: 0.3450, loss: 2.0405, grad_norm: 3.9051
2024-08-25 07:17:05,640 - mmdet - INFO - Epoch [2][1450/1685]	lr: 1.000e-04, eta: 13:34:20, time: 2.997, data_time: 0.011, memory: 19414, loss_occ: 0.5669, acc_occ: 0.8507, loss_centerness: 0.6206, loss_bbox: 0.5174, loss_cls: 0.3792, loss: 2.0841, grad_norm: 4.4625
2024-08-25 07:19:32,042 - mmdet - INFO - Epoch [2][1500/1685]	lr: 1.000e-04, eta: 13:32:16, time: 2.928, data_time: 0.011, memory: 19414, loss_occ: 0.5921, acc_occ: 0.8434, loss_centerness: 0.6253, loss_bbox: 0.5191, loss_cls: 0.3875, loss: 2.1240, grad_norm: 3.8082
2024-08-25 07:21:59,047 - mmdet - INFO - Epoch [2][1550/1685]	lr: 1.000e-04, eta: 13:30:13, time: 2.940, data_time: 0.014, memory: 19414, loss_occ: 0.5702, acc_occ: 0.8505, loss_centerness: 0.6219, loss_bbox: 0.5139, loss_cls: 0.3544, loss: 2.0604, grad_norm: 3.8447
2024-08-25 07:24:29,421 - mmdet - INFO - Epoch [2][1600/1685]	lr: 1.000e-04, eta: 13:28:28, time: 3.007, data_time: 0.015, memory: 19414, loss_occ: 0.5768, acc_occ: 0.8518, loss_centerness: 0.6173, loss_bbox: 0.5152, loss_cls: 0.3793, loss: 2.0886, grad_norm: 4.0789
2024-08-25 07:26:58,901 - mmdet - INFO - Epoch [2][1650/1685]	lr: 1.000e-04, eta: 13:26:36, time: 2.990, data_time: 0.014, memory: 19414, loss_occ: 0.5814, acc_occ: 0.8478, loss_centerness: 0.6159, loss_bbox: 0.5062, loss_cls: 0.3634, loss: 2.0670, grad_norm: 3.8955
2024-08-25 07:28:40,338 - mmdet - INFO - Saving checkpoint at 2 epochs
2024-08-25 07:30:53,436 - mmdet - INFO - 
+--------------+---------+---------+---------+---------+
| classes      | AP_0.25 | AR_0.25 | AP_0.50 | AR_0.50 |
+--------------+---------+---------+---------+---------+
| sofa         | 0.7225  | 0.8189  | 0.3626  | 0.4777  |
| chair        | 0.5717  | 0.8050  | 0.1645  | 0.3550  |
| table        | 0.5446  | 0.8154  | 0.1551  | 0.3203  |
| cabinet      | 0.4122  | 0.6089  | 0.0739  | 0.1854  |
| toilet       | 0.8955  | 0.9174  | 0.6029  | 0.6942  |
| stool        | 0.1348  | 0.4785  | 0.0334  | 0.1344  |
| sink         | 0.2521  | 0.3471  | 0.0295  | 0.0987  |
| refrigerator | 0.6451  | 0.9024  | 0.2178  | 0.4146  |
| shelf        | 0.3015  | 0.5728  | 0.0078  | 0.0825  |
| tv_monitor   | 0.0002  | 0.0142  | 0.0000  | 0.0000  |
| bathtub      | 0.9471  | 0.9694  | 0.6711  | 0.7449  |
| oven         | 0.4479  | 0.6364  | 0.0911  | 0.2078  |
| bed          | 0.8498  | 0.9337  | 0.5466  | 0.6354  |
| dishwasher   | 0.0576  | 0.8400  | 0.0070  | 0.2000  |
| washer       | 0.6842  | 0.8070  | 0.5446  | 0.6053  |
| stove        | 0.0968  | 0.1837  | 0.0000  | 0.0000  |
| fireplace    | 0.4308  | 0.6852  | 0.0427  | 0.1667  |
+--------------+---------+---------+---------+---------+
| Overall      | 0.4703  | 0.6668  | 0.2089  | 0.3131  |
+--------------+---------+---------+---------+---------+
2024-08-25 07:30:53,887 - mmdet - INFO - Epoch(val) [2][1685]	sofa_AP_0.25: 0.7225, chair_AP_0.25: 0.5717, table_AP_0.25: 0.5446, cabinet_AP_0.25: 0.4122, toilet_AP_0.25: 0.8955, stool_AP_0.25: 0.1348, sink_AP_0.25: 0.2521, refrigerator_AP_0.25: 0.6451, shelf_AP_0.25: 0.3015, tv_monitor_AP_0.25: 0.0002, bathtub_AP_0.25: 0.9471, oven_AP_0.25: 0.4479, bed_AP_0.25: 0.8498, dishwasher_AP_0.25: 0.0576, washer_AP_0.25: 0.6842, stove_AP_0.25: 0.0968, fireplace_AP_0.25: 0.4308, mAP_0.25: 0.4703, sofa_rec_0.25: 0.8189, chair_rec_0.25: 0.8050, table_rec_0.25: 0.8154, cabinet_rec_0.25: 0.6089, toilet_rec_0.25: 0.9174, stool_rec_0.25: 0.4785, sink_rec_0.25: 0.3471, refrigerator_rec_0.25: 0.9024, shelf_rec_0.25: 0.5728, tv_monitor_rec_0.25: 0.0142, bathtub_rec_0.25: 0.9694, oven_rec_0.25: 0.6364, bed_rec_0.25: 0.9337, dishwasher_rec_0.25: 0.8400, washer_rec_0.25: 0.8070, stove_rec_0.25: 0.1837, fireplace_rec_0.25: 0.6852, mAR_0.25: 0.6668, sofa_AP_0.50: 0.3626, chair_AP_0.50: 0.1645, table_AP_0.50: 0.1551, cabinet_AP_0.50: 0.0739, toilet_AP_0.50: 0.6029, stool_AP_0.50: 0.0334, sink_AP_0.50: 0.0295, refrigerator_AP_0.50: 0.2178, shelf_AP_0.50: 0.0078, tv_monitor_AP_0.50: 0.0000, bathtub_AP_0.50: 0.6711, oven_AP_0.50: 0.0911, bed_AP_0.50: 0.5466, dishwasher_AP_0.50: 0.0070, washer_AP_0.50: 0.5446, stove_AP_0.50: 0.0000, fireplace_AP_0.50: 0.0427, mAP_0.50: 0.2089, sofa_rec_0.50: 0.4777, chair_rec_0.50: 0.3550, table_rec_0.50: 0.3203, cabinet_rec_0.50: 0.1854, toilet_rec_0.50: 0.6942, stool_rec_0.50: 0.1344, sink_rec_0.50: 0.0987, refrigerator_rec_0.50: 0.4146, shelf_rec_0.50: 0.0825, tv_monitor_rec_0.50: 0.0000, bathtub_rec_0.50: 0.7449, oven_rec_0.50: 0.2078, bed_rec_0.50: 0.6354, dishwasher_rec_0.50: 0.2000, washer_rec_0.50: 0.6053, stove_rec_0.50: 0.0000, fireplace_rec_0.50: 0.1667, mAR_0.50: 0.3131
2024-08-25 07:33:26,458 - mmdet - INFO - Epoch [3][50/1685]	lr: 1.000e-04, eta: 13:15:05, time: 3.051, data_time: 0.143, memory: 19414, loss_occ: 0.5755, acc_occ: 0.8492, loss_centerness: 0.6200, loss_bbox: 0.5053, loss_cls: 0.3436, loss: 2.0446, grad_norm: 3.7735
2024-08-25 07:35:54,006 - mmdet - INFO - Epoch [3][100/1685]	lr: 1.000e-04, eta: 13:13:10, time: 2.951, data_time: 0.012, memory: 19414, loss_occ: 0.5754, acc_occ: 0.8584, loss_centerness: 0.6224, loss_bbox: 0.4974, loss_cls: 0.3369, loss: 2.0322, grad_norm: 3.8853
2024-08-25 07:38:22,879 - mmdet - INFO - Epoch [3][150/1685]	lr: 1.000e-04, eta: 13:11:20, time: 2.977, data_time: 0.011, memory: 19414, loss_occ: 0.5791, acc_occ: 0.8484, loss_centerness: 0.6175, loss_bbox: 0.5113, loss_cls: 0.3450, loss: 2.0529, grad_norm: 3.6792
2024-08-25 07:40:51,433 - mmdet - INFO - Epoch [3][200/1685]	lr: 1.000e-04, eta: 13:09:28, time: 2.971, data_time: 0.010, memory: 19414, loss_occ: 0.5775, acc_occ: 0.8470, loss_centerness: 0.6217, loss_bbox: 0.5105, loss_cls: 0.3640, loss: 2.0737, grad_norm: 4.3458
2024-08-25 07:43:17,611 - mmdet - INFO - Epoch [3][250/1685]	lr: 1.000e-04, eta: 13:07:24, time: 2.924, data_time: 0.011, memory: 19414, loss_occ: 0.5671, acc_occ: 0.8436, loss_centerness: 0.6215, loss_bbox: 0.5141, loss_cls: 0.3677, loss: 2.0703, grad_norm: 3.8524
2024-08-25 07:45:43,303 - mmdet - INFO - Epoch [3][300/1685]	lr: 1.000e-04, eta: 13:05:17, time: 2.914, data_time: 0.011, memory: 19414, loss_occ: 0.5801, acc_occ: 0.8503, loss_centerness: 0.6237, loss_bbox: 0.5096, loss_cls: 0.3538, loss: 2.0671, grad_norm: 3.8458
2024-08-25 07:48:09,475 - mmdet - INFO - Epoch [3][350/1685]	lr: 1.000e-04, eta: 13:03:11, time: 2.923, data_time: 0.011, memory: 19414, loss_occ: 0.5654, acc_occ: 0.8534, loss_centerness: 0.6225, loss_bbox: 0.5014, loss_cls: 0.3364, loss: 2.0256, grad_norm: 3.9020
2024-08-25 07:50:35,281 - mmdet - INFO - Epoch [3][400/1685]	lr: 1.000e-04, eta: 13:01:04, time: 2.916, data_time: 0.011, memory: 19414, loss_occ: 0.5717, acc_occ: 0.8525, loss_centerness: 0.6269, loss_bbox: 0.4979, loss_cls: 0.3349, loss: 2.0313, grad_norm: 3.6806
2024-08-25 07:53:03,582 - mmdet - INFO - Epoch [3][450/1685]	lr: 1.000e-04, eta: 12:59:06, time: 2.966, data_time: 0.010, memory: 19414, loss_occ: 0.5590, acc_occ: 0.8521, loss_centerness: 0.6192, loss_bbox: 0.5045, loss_cls: 0.3706, loss: 2.0535, grad_norm: 4.2073
2024-08-25 07:55:29,580 - mmdet - INFO - Epoch [3][500/1685]	lr: 1.000e-04, eta: 12:56:59, time: 2.920, data_time: 0.010, memory: 19414, loss_occ: 0.5573, acc_occ: 0.8572, loss_centerness: 0.6208, loss_bbox: 0.4968, loss_cls: 0.3237, loss: 1.9987, grad_norm: 3.5005
2024-08-25 07:57:56,173 - mmdet - INFO - Epoch [3][550/1685]	lr: 1.000e-04, eta: 12:54:53, time: 2.932, data_time: 0.015, memory: 19414, loss_occ: 0.5881, acc_occ: 0.8575, loss_centerness: 0.6210, loss_bbox: 0.4961, loss_cls: 0.3363, loss: 2.0415, grad_norm: 3.8404
2024-08-25 08:00:30,303 - mmdet - INFO - Epoch [3][600/1685]	lr: 1.000e-04, eta: 12:53:17, time: 3.083, data_time: 0.012, memory: 19414, loss_occ: 0.5703, acc_occ: 0.8564, loss_centerness: 0.6186, loss_bbox: 0.4995, loss_cls: 0.3281, loss: 2.0164, grad_norm: 4.0124
2024-08-25 08:02:58,679 - mmdet - INFO - Epoch [3][650/1685]	lr: 1.000e-04, eta: 12:51:17, time: 2.968, data_time: 0.012, memory: 19414, loss_occ: 0.5752, acc_occ: 0.8589, loss_centerness: 0.6223, loss_bbox: 0.5038, loss_cls: 0.3365, loss: 2.0377, grad_norm: 3.8202
2024-08-25 08:05:27,049 - mmdet - INFO - Epoch [3][700/1685]	lr: 1.000e-04, eta: 12:49:16, time: 2.968, data_time: 0.013, memory: 19414, loss_occ: 0.5560, acc_occ: 0.8573, loss_centerness: 0.6186, loss_bbox: 0.4946, loss_cls: 0.3255, loss: 1.9947, grad_norm: 3.8528
2024-08-25 08:07:56,487 - mmdet - INFO - Epoch [3][750/1685]	lr: 1.000e-04, eta: 12:47:19, time: 2.989, data_time: 0.012, memory: 19414, loss_occ: 0.5738, acc_occ: 0.8578, loss_centerness: 0.6192, loss_bbox: 0.4990, loss_cls: 0.3270, loss: 2.0190, grad_norm: 3.9651
2024-08-25 08:10:27,621 - mmdet - INFO - Epoch [3][800/1685]	lr: 1.000e-04, eta: 12:45:27, time: 3.023, data_time: 0.014, memory: 19414, loss_occ: 0.5724, acc_occ: 0.8515, loss_centerness: 0.6196, loss_bbox: 0.4969, loss_cls: 0.3285, loss: 2.0174, grad_norm: 3.6684
2024-08-25 08:12:54,328 - mmdet - INFO - Epoch [3][850/1685]	lr: 1.000e-04, eta: 12:43:18, time: 2.934, data_time: 0.015, memory: 19414, loss_occ: 0.5512, acc_occ: 0.8533, loss_centerness: 0.6153, loss_bbox: 0.4971, loss_cls: 0.3414, loss: 2.0051, grad_norm: 4.0131
2024-08-25 08:15:20,953 - mmdet - INFO - Epoch [3][900/1685]	lr: 1.000e-04, eta: 12:41:08, time: 2.932, data_time: 0.013, memory: 19414, loss_occ: 0.5615, acc_occ: 0.8595, loss_centerness: 0.6262, loss_bbox: 0.4890, loss_cls: 0.3250, loss: 2.0016, grad_norm: 3.7509
2024-08-25 08:17:47,037 - mmdet - INFO - Epoch [3][950/1685]	lr: 1.000e-04, eta: 12:38:56, time: 2.922, data_time: 0.015, memory: 19414, loss_occ: 0.5705, acc_occ: 0.8555, loss_centerness: 0.6209, loss_bbox: 0.4930, loss_cls: 0.3223, loss: 2.0067, grad_norm: 3.8320
2024-08-25 08:20:13,341 - mmdet - INFO - Epoch [3][1000/1685]	lr: 1.000e-04, eta: 12:36:44, time: 2.926, data_time: 0.015, memory: 19414, loss_occ: 0.5804, acc_occ: 0.8560, loss_centerness: 0.6162, loss_bbox: 0.4901, loss_cls: 0.3199, loss: 2.0065, grad_norm: 3.9578
2024-08-25 08:22:34,412 - mmdet - INFO - Epoch [3][1050/1685]	lr: 1.000e-04, eta: 12:34:13, time: 2.821, data_time: 0.019, memory: 19414, loss_occ: 0.5737, acc_occ: 0.8548, loss_centerness: 0.6215, loss_bbox: 0.4890, loss_cls: 0.3192, loss: 2.0034, grad_norm: 3.7970
2024-08-25 08:24:52,184 - mmdet - INFO - Epoch [3][1100/1685]	lr: 1.000e-04, eta: 12:31:30, time: 2.755, data_time: 0.013, memory: 19414, loss_occ: 0.5604, acc_occ: 0.8554, loss_centerness: 0.6200, loss_bbox: 0.4874, loss_cls: 0.3212, loss: 1.9889, grad_norm: 3.9719
2024-08-25 08:27:11,377 - mmdet - INFO - Epoch [3][1150/1685]	lr: 1.000e-04, eta: 12:28:53, time: 2.784, data_time: 0.012, memory: 19414, loss_occ: 0.5547, acc_occ: 0.8587, loss_centerness: 0.6214, loss_bbox: 0.4948, loss_cls: 0.3201, loss: 1.9910, grad_norm: 3.8271
2024-08-25 08:29:29,744 - mmdet - INFO - Epoch [3][1200/1685]	lr: 1.000e-04, eta: 12:26:14, time: 2.767, data_time: 0.011, memory: 19414, loss_occ: 0.5544, acc_occ: 0.8606, loss_centerness: 0.6209, loss_bbox: 0.4897, loss_cls: 0.3226, loss: 1.9876, grad_norm: 3.7025
2024-08-25 08:31:50,960 - mmdet - INFO - Epoch [3][1250/1685]	lr: 1.000e-04, eta: 12:23:45, time: 2.824, data_time: 0.013, memory: 19414, loss_occ: 0.5634, acc_occ: 0.8636, loss_centerness: 0.6170, loss_bbox: 0.4842, loss_cls: 0.3226, loss: 1.9873, grad_norm: 3.8786
2024-08-25 08:34:11,580 - mmdet - INFO - Epoch [3][1300/1685]	lr: 1.000e-04, eta: 12:21:14, time: 2.812, data_time: 0.015, memory: 19414, loss_occ: 0.5743, acc_occ: 0.8563, loss_centerness: 0.6212, loss_bbox: 0.4920, loss_cls: 0.3318, loss: 2.0193, grad_norm: 3.6111
2024-08-25 08:36:36,776 - mmdet - INFO - Epoch [3][1350/1685]	lr: 1.000e-04, eta: 12:18:58, time: 2.904, data_time: 0.015, memory: 19414, loss_occ: 0.5619, acc_occ: 0.8686, loss_centerness: 0.6180, loss_bbox: 0.4859, loss_cls: 0.3038, loss: 1.9697, grad_norm: 3.8362
2024-08-25 08:39:02,298 - mmdet - INFO - Epoch [3][1400/1685]	lr: 1.000e-04, eta: 12:16:43, time: 2.910, data_time: 0.015, memory: 19414, loss_occ: 0.5575, acc_occ: 0.8575, loss_centerness: 0.6171, loss_bbox: 0.4842, loss_cls: 0.3134, loss: 1.9722, grad_norm: 3.8611
2024-08-25 08:41:27,647 - mmdet - INFO - Epoch [3][1450/1685]	lr: 1.000e-04, eta: 12:14:27, time: 2.907, data_time: 0.013, memory: 19414, loss_occ: 0.5660, acc_occ: 0.8616, loss_centerness: 0.6156, loss_bbox: 0.4835, loss_cls: 0.3155, loss: 1.9805, grad_norm: 4.0443
2024-08-25 08:43:56,920 - mmdet - INFO - Epoch [3][1500/1685]	lr: 1.000e-04, eta: 12:12:24, time: 2.985, data_time: 0.012, memory: 19414, loss_occ: 0.5615, acc_occ: 0.8636, loss_centerness: 0.6215, loss_bbox: 0.4852, loss_cls: 0.3128, loss: 1.9810, grad_norm: 3.7469
2024-08-25 08:46:23,862 - mmdet - INFO - Epoch [3][1550/1685]	lr: 1.000e-04, eta: 12:10:13, time: 2.939, data_time: 0.012, memory: 19414, loss_occ: 0.5457, acc_occ: 0.8658, loss_centerness: 0.6216, loss_bbox: 0.4810, loss_cls: 0.3112, loss: 1.9596, grad_norm: 3.6854
2024-08-25 08:48:49,899 - mmdet - INFO - Epoch [3][1600/1685]	lr: 1.000e-04, eta: 12:07:58, time: 2.921, data_time: 0.012, memory: 19414, loss_occ: 0.5692, acc_occ: 0.8659, loss_centerness: 0.6193, loss_bbox: 0.4837, loss_cls: 0.3325, loss: 2.0047, grad_norm: 3.9638
2024-08-25 08:51:15,883 - mmdet - INFO - Epoch [3][1650/1685]	lr: 1.000e-04, eta: 12:05:43, time: 2.920, data_time: 0.012, memory: 19414, loss_occ: 0.5685, acc_occ: 0.8566, loss_centerness: 0.6212, loss_bbox: 0.4893, loss_cls: 0.3172, loss: 1.9961, grad_norm: 3.6845
2024-08-25 08:52:57,879 - mmdet - INFO - Saving checkpoint at 3 epochs
2024-08-25 08:55:11,454 - mmdet - INFO - 
+--------------+---------+---------+---------+---------+
| classes      | AP_0.25 | AR_0.25 | AP_0.50 | AR_0.50 |
+--------------+---------+---------+---------+---------+
| sofa         | 0.7407  | 0.8373  | 0.4536  | 0.5617  |
| chair        | 0.6437  | 0.8387  | 0.2828  | 0.4550  |
| table        | 0.6076  | 0.8333  | 0.2542  | 0.4216  |
| cabinet      | 0.4547  | 0.6195  | 0.1666  | 0.2732  |
| stool        | 0.2098  | 0.5914  | 0.0749  | 0.2527  |
| tv_monitor   | 0.0048  | 0.0676  | 0.0000  | 0.0000  |
| sink         | 0.4025  | 0.4841  | 0.1042  | 0.1943  |
| refrigerator | 0.7362  | 0.9756  | 0.4490  | 0.6220  |
| shelf        | 0.3342  | 0.5971  | 0.0314  | 0.1311  |
| toilet       | 0.8888  | 0.9174  | 0.7211  | 0.7603  |
| oven         | 0.5099  | 0.6948  | 0.1283  | 0.2857  |
| bed          | 0.8599  | 0.9448  | 0.6339  | 0.7293  |
| dishwasher   | 0.1113  | 0.8400  | 0.0816  | 0.4800  |
| fireplace    | 0.5974  | 0.7222  | 0.0829  | 0.2222  |
| bathtub      | 0.9488  | 0.9490  | 0.8297  | 0.8469  |
| washer       | 0.7122  | 0.8684  | 0.5961  | 0.6842  |
| stove        | 0.1065  | 0.2041  | 0.0037  | 0.0204  |
+--------------+---------+---------+---------+---------+
| Overall      | 0.5217  | 0.7050  | 0.2879  | 0.4083  |
+--------------+---------+---------+---------+---------+
2024-08-25 08:55:11,976 - mmdet - INFO - Epoch(val) [3][1685]	sofa_AP_0.25: 0.7407, chair_AP_0.25: 0.6437, table_AP_0.25: 0.6076, cabinet_AP_0.25: 0.4547, stool_AP_0.25: 0.2098, tv_monitor_AP_0.25: 0.0048, sink_AP_0.25: 0.4025, refrigerator_AP_0.25: 0.7362, shelf_AP_0.25: 0.3342, toilet_AP_0.25: 0.8888, oven_AP_0.25: 0.5099, bed_AP_0.25: 0.8599, dishwasher_AP_0.25: 0.1113, fireplace_AP_0.25: 0.5974, bathtub_AP_0.25: 0.9488, washer_AP_0.25: 0.7122, stove_AP_0.25: 0.1065, mAP_0.25: 0.5217, sofa_rec_0.25: 0.8373, chair_rec_0.25: 0.8387, table_rec_0.25: 0.8333, cabinet_rec_0.25: 0.6195, stool_rec_0.25: 0.5914, tv_monitor_rec_0.25: 0.0676, sink_rec_0.25: 0.4841, refrigerator_rec_0.25: 0.9756, shelf_rec_0.25: 0.5971, toilet_rec_0.25: 0.9174, oven_rec_0.25: 0.6948, bed_rec_0.25: 0.9448, dishwasher_rec_0.25: 0.8400, fireplace_rec_0.25: 0.7222, bathtub_rec_0.25: 0.9490, washer_rec_0.25: 0.8684, stove_rec_0.25: 0.2041, mAR_0.25: 0.7050, sofa_AP_0.50: 0.4536, chair_AP_0.50: 0.2828, table_AP_0.50: 0.2542, cabinet_AP_0.50: 0.1666, stool_AP_0.50: 0.0749, tv_monitor_AP_0.50: 0.0000, sink_AP_0.50: 0.1042, refrigerator_AP_0.50: 0.4490, shelf_AP_0.50: 0.0314, toilet_AP_0.50: 0.7211, oven_AP_0.50: 0.1283, bed_AP_0.50: 0.6339, dishwasher_AP_0.50: 0.0816, fireplace_AP_0.50: 0.0829, bathtub_AP_0.50: 0.8297, washer_AP_0.50: 0.5961, stove_AP_0.50: 0.0037, mAP_0.50: 0.2879, sofa_rec_0.50: 0.5617, chair_rec_0.50: 0.4550, table_rec_0.50: 0.4216, cabinet_rec_0.50: 0.2732, stool_rec_0.50: 0.2527, tv_monitor_rec_0.50: 0.0000, sink_rec_0.50: 0.1943, refrigerator_rec_0.50: 0.6220, shelf_rec_0.50: 0.1311, toilet_rec_0.50: 0.7603, oven_rec_0.50: 0.2857, bed_rec_0.50: 0.7293, dishwasher_rec_0.50: 0.4800, fireplace_rec_0.50: 0.2222, bathtub_rec_0.50: 0.8469, washer_rec_0.50: 0.6842, stove_rec_0.50: 0.0204, mAR_0.50: 0.4083
2024-08-25 08:57:46,727 - mmdet - INFO - Epoch [4][50/1685]	lr: 1.000e-04, eta: 11:57:17, time: 3.095, data_time: 0.132, memory: 19414, loss_occ: 0.5490, acc_occ: 0.8616, loss_centerness: 0.6212, loss_bbox: 0.4847, loss_cls: 0.3125, loss: 1.9674, grad_norm: 3.7879
2024-08-25 09:00:14,300 - mmdet - INFO - Epoch [4][100/1685]	lr: 1.000e-04, eta: 11:55:10, time: 2.951, data_time: 0.011, memory: 19414, loss_occ: 0.5625, acc_occ: 0.8631, loss_centerness: 0.6138, loss_bbox: 0.4768, loss_cls: 0.3014, loss: 1.9545, grad_norm: 3.7338
2024-08-25 09:02:48,161 - mmdet - INFO - Epoch [4][150/1685]	lr: 1.000e-04, eta: 11:53:20, time: 3.077, data_time: 0.010, memory: 19414, loss_occ: 0.5627, acc_occ: 0.8620, loss_centerness: 0.6137, loss_bbox: 0.4841, loss_cls: 0.3126, loss: 1.9730, grad_norm: 3.8393
2024-08-25 09:05:15,926 - mmdet - INFO - Epoch [4][200/1685]	lr: 1.000e-04, eta: 11:51:13, time: 2.955, data_time: 0.014, memory: 19414, loss_occ: 0.5803, acc_occ: 0.8642, loss_centerness: 0.6172, loss_bbox: 0.4755, loss_cls: 0.2993, loss: 1.9722, grad_norm: 3.7564
2024-08-25 09:07:43,692 - mmdet - INFO - Epoch [4][250/1685]	lr: 1.000e-04, eta: 11:49:05, time: 2.955, data_time: 0.012, memory: 19414, loss_occ: 0.5557, acc_occ: 0.8598, loss_centerness: 0.6189, loss_bbox: 0.4790, loss_cls: 0.3107, loss: 1.9642, grad_norm: 3.8044
2024-08-25 09:10:13,232 - mmdet - INFO - Epoch [4][300/1685]	lr: 1.000e-04, eta: 11:47:01, time: 2.991, data_time: 0.012, memory: 19414, loss_occ: 0.5681, acc_occ: 0.8605, loss_centerness: 0.6196, loss_bbox: 0.4832, loss_cls: 0.3243, loss: 1.9953, grad_norm: 3.8317
2024-08-25 09:12:43,521 - mmdet - INFO - Epoch [4][350/1685]	lr: 1.000e-04, eta: 11:45:00, time: 3.006, data_time: 0.011, memory: 19414, loss_occ: 0.5541, acc_occ: 0.8651, loss_centerness: 0.6142, loss_bbox: 0.4773, loss_cls: 0.3081, loss: 1.9537, grad_norm: 3.8020
2024-08-25 09:15:12,690 - mmdet - INFO - Epoch [4][400/1685]	lr: 1.000e-04, eta: 11:42:54, time: 2.983, data_time: 0.011, memory: 19414, loss_occ: 0.5415, acc_occ: 0.8665, loss_centerness: 0.6195, loss_bbox: 0.4703, loss_cls: 0.2974, loss: 1.9287, grad_norm: 3.7386
2024-08-25 09:17:42,493 - mmdet - INFO - Epoch [4][450/1685]	lr: 1.000e-04, eta: 11:40:50, time: 2.996, data_time: 0.013, memory: 19414, loss_occ: 0.5695, acc_occ: 0.8626, loss_centerness: 0.6137, loss_bbox: 0.4776, loss_cls: 0.3027, loss: 1.9635, grad_norm: 3.8683
2024-08-25 09:20:10,593 - mmdet - INFO - Epoch [4][500/1685]	lr: 1.000e-04, eta: 11:38:41, time: 2.962, data_time: 0.013, memory: 19414, loss_occ: 0.5544, acc_occ: 0.8638, loss_centerness: 0.6203, loss_bbox: 0.4711, loss_cls: 0.2992, loss: 1.9450, grad_norm: 3.8051
2024-08-25 09:22:36,701 - mmdet - INFO - Epoch [4][550/1685]	lr: 1.000e-04, eta: 11:36:26, time: 2.922, data_time: 0.015, memory: 19414, loss_occ: 0.5521, acc_occ: 0.8649, loss_centerness: 0.6158, loss_bbox: 0.4748, loss_cls: 0.3083, loss: 1.9510, grad_norm: 3.9048
2024-08-25 09:25:03,799 - mmdet - INFO - Epoch [4][600/1685]	lr: 1.000e-04, eta: 11:34:14, time: 2.942, data_time: 0.014, memory: 19414, loss_occ: 0.5511, acc_occ: 0.8654, loss_centerness: 0.6152, loss_bbox: 0.4725, loss_cls: 0.2970, loss: 1.9358, grad_norm: 3.5560
2024-08-25 09:27:29,969 - mmdet - INFO - Epoch [4][650/1685]	lr: 1.000e-04, eta: 11:31:59, time: 2.923, data_time: 0.015, memory: 19416, loss_occ: 0.5399, acc_occ: 0.8625, loss_centerness: 0.6169, loss_bbox: 0.4687, loss_cls: 0.2986, loss: 1.9242, grad_norm: 3.7578
2024-08-25 09:29:59,365 - mmdet - INFO - Epoch [4][700/1685]	lr: 1.000e-04, eta: 11:29:52, time: 2.988, data_time: 0.014, memory: 19416, loss_occ: 0.5577, acc_occ: 0.8656, loss_centerness: 0.6157, loss_bbox: 0.4766, loss_cls: 0.3029, loss: 1.9529, grad_norm: 3.7215
2024-08-25 09:32:26,162 - mmdet - INFO - Epoch [4][750/1685]	lr: 1.000e-04, eta: 11:27:38, time: 2.936, data_time: 0.015, memory: 19416, loss_occ: 0.5442, acc_occ: 0.8636, loss_centerness: 0.6160, loss_bbox: 0.4732, loss_cls: 0.2967, loss: 1.9300, grad_norm: 3.8198
2024-08-25 09:34:53,595 - mmdet - INFO - Epoch [4][800/1685]	lr: 1.000e-04, eta: 11:25:26, time: 2.949, data_time: 0.014, memory: 19416, loss_occ: 0.5655, acc_occ: 0.8662, loss_centerness: 0.6191, loss_bbox: 0.4706, loss_cls: 0.2956, loss: 1.9507, grad_norm: 3.7698
2024-08-25 09:37:19,364 - mmdet - INFO - Epoch [4][850/1685]	lr: 1.000e-04, eta: 11:23:09, time: 2.915, data_time: 0.016, memory: 19416, loss_occ: 0.5443, acc_occ: 0.8678, loss_centerness: 0.6181, loss_bbox: 0.4669, loss_cls: 0.2942, loss: 1.9234, grad_norm: 3.8403
2024-08-25 09:39:43,117 - mmdet - INFO - Epoch [4][900/1685]	lr: 1.000e-04, eta: 11:20:47, time: 2.875, data_time: 0.014, memory: 19416, loss_occ: 0.5689, acc_occ: 0.8671, loss_centerness: 0.6207, loss_bbox: 0.4705, loss_cls: 0.2978, loss: 1.9579, grad_norm: 3.6953
2024-08-25 09:42:08,575 - mmdet - INFO - Epoch [4][950/1685]	lr: 1.000e-04, eta: 11:18:29, time: 2.909, data_time: 0.014, memory: 19416, loss_occ: 0.5827, acc_occ: 0.8723, loss_centerness: 0.6153, loss_bbox: 0.4706, loss_cls: 0.2995, loss: 1.9682, grad_norm: 3.9222
2024-08-25 09:44:36,054 - mmdet - INFO - Epoch [4][1000/1685]	lr: 1.000e-04, eta: 11:16:16, time: 2.950, data_time: 0.014, memory: 19416, loss_occ: 0.5450, acc_occ: 0.8637, loss_centerness: 0.6112, loss_bbox: 0.4623, loss_cls: 0.2869, loss: 1.9054, grad_norm: 3.5630
2024-08-25 09:47:03,240 - mmdet - INFO - Epoch [4][1050/1685]	lr: 1.000e-04, eta: 11:14:02, time: 2.944, data_time: 0.015, memory: 19416, loss_occ: 0.5673, acc_occ: 0.8724, loss_centerness: 0.6192, loss_bbox: 0.4687, loss_cls: 0.2883, loss: 1.9435, grad_norm: 3.7747
2024-08-25 09:49:30,389 - mmdet - INFO - Epoch [4][1100/1685]	lr: 1.000e-04, eta: 11:11:48, time: 2.943, data_time: 0.014, memory: 19416, loss_occ: 0.5545, acc_occ: 0.8685, loss_centerness: 0.6193, loss_bbox: 0.4648, loss_cls: 0.2930, loss: 1.9316, grad_norm: 3.6059
2024-08-25 09:51:58,443 - mmdet - INFO - Epoch [4][1150/1685]	lr: 1.000e-04, eta: 11:09:35, time: 2.961, data_time: 0.013, memory: 19416, loss_occ: 0.5502, acc_occ: 0.8688, loss_centerness: 0.6155, loss_bbox: 0.4617, loss_cls: 0.2834, loss: 1.9108, grad_norm: 3.8864
2024-08-25 09:54:23,228 - mmdet - INFO - Epoch [4][1200/1685]	lr: 1.000e-04, eta: 11:07:15, time: 2.896, data_time: 0.014, memory: 19416, loss_occ: 0.5615, acc_occ: 0.8577, loss_centerness: 0.6179, loss_bbox: 0.4877, loss_cls: 0.3734, loss: 2.0405, grad_norm: 4.4077
2024-08-25 09:56:50,463 - mmdet - INFO - Epoch [4][1250/1685]	lr: 1.000e-04, eta: 11:05:00, time: 2.945, data_time: 0.013, memory: 19416, loss_occ: 0.5568, acc_occ: 0.8623, loss_centerness: 0.6169, loss_bbox: 0.4703, loss_cls: 0.3068, loss: 1.9507, grad_norm: 3.4608
2024-08-25 09:59:16,791 - mmdet - INFO - Epoch [4][1300/1685]	lr: 1.000e-04, eta: 11:02:43, time: 2.927, data_time: 0.016, memory: 19416, loss_occ: 0.5554, acc_occ: 0.8672, loss_centerness: 0.6157, loss_bbox: 0.4707, loss_cls: 0.3019, loss: 1.9437, grad_norm: 3.6677
2024-08-25 10:01:44,697 - mmdet - INFO - Epoch [4][1350/1685]	lr: 1.000e-04, eta: 11:00:30, time: 2.958, data_time: 0.016, memory: 19416, loss_occ: 0.5360, acc_occ: 0.8741, loss_centerness: 0.6133, loss_bbox: 0.4587, loss_cls: 0.2841, loss: 1.8921, grad_norm: 3.7410
2024-08-25 10:04:09,692 - mmdet - INFO - Epoch [4][1400/1685]	lr: 1.000e-04, eta: 10:58:10, time: 2.900, data_time: 0.015, memory: 19416, loss_occ: 0.5542, acc_occ: 0.8692, loss_centerness: 0.6150, loss_bbox: 0.4614, loss_cls: 0.2918, loss: 1.9225, grad_norm: 3.6994
2024-08-25 10:06:33,669 - mmdet - INFO - Epoch [4][1450/1685]	lr: 1.000e-04, eta: 10:55:47, time: 2.880, data_time: 0.015, memory: 19416, loss_occ: 0.5509, acc_occ: 0.8698, loss_centerness: 0.6171, loss_bbox: 0.4689, loss_cls: 0.2883, loss: 1.9252, grad_norm: 3.6123
2024-08-25 10:08:53,432 - mmdet - INFO - Epoch [4][1500/1685]	lr: 1.000e-04, eta: 10:53:16, time: 2.795, data_time: 0.013, memory: 19416, loss_occ: 0.5406, acc_occ: 0.8677, loss_centerness: 0.6189, loss_bbox: 0.4604, loss_cls: 0.2879, loss: 1.9079, grad_norm: 3.7760
2024-08-25 10:11:14,305 - mmdet - INFO - Epoch [4][1550/1685]	lr: 1.000e-04, eta: 10:50:47, time: 2.817, data_time: 0.012, memory: 19416, loss_occ: 0.5571, acc_occ: 0.8672, loss_centerness: 0.6174, loss_bbox: 0.4544, loss_cls: 0.2808, loss: 1.9098, grad_norm: 3.6226
2024-08-25 10:13:34,261 - mmdet - INFO - Epoch [4][1600/1685]	lr: 1.000e-04, eta: 10:48:17, time: 2.799, data_time: 0.011, memory: 19416, loss_occ: 0.5597, acc_occ: 0.8707, loss_centerness: 0.6174, loss_bbox: 0.4642, loss_cls: 0.2931, loss: 1.9345, grad_norm: 3.4907
2024-08-25 10:15:53,315 - mmdet - INFO - Epoch [4][1650/1685]	lr: 1.000e-04, eta: 10:45:45, time: 2.781, data_time: 0.010, memory: 19416, loss_occ: 0.5560, acc_occ: 0.8701, loss_centerness: 0.6169, loss_bbox: 0.4639, loss_cls: 0.2868, loss: 1.9235, grad_norm: 3.8234
2024-08-25 10:17:30,780 - mmdet - INFO - Saving checkpoint at 4 epochs
2024-08-25 10:19:41,657 - mmdet - INFO - 
+--------------+---------+---------+---------+---------+
| classes      | AP_0.25 | AR_0.25 | AP_0.50 | AR_0.50 |
+--------------+---------+---------+---------+---------+
| sofa         | 0.7521  | 0.8478  | 0.5125  | 0.6142  |
| chair        | 0.6490  | 0.8263  | 0.3483  | 0.4888  |
| table        | 0.6267  | 0.8627  | 0.3106  | 0.4673  |
| cabinet      | 0.5034  | 0.6483  | 0.2043  | 0.3184  |
| stool        | 0.2284  | 0.6344  | 0.1006  | 0.3172  |
| tv_monitor   | 0.0112  | 0.0996  | 0.0000  | 0.0036  |
| oven         | 0.5368  | 0.6753  | 0.3211  | 0.4351  |
| shelf        | 0.3837  | 0.6165  | 0.0668  | 0.1650  |
| sink         | 0.4470  | 0.5032  | 0.1323  | 0.1943  |
| refrigerator | 0.7426  | 0.9268  | 0.5972  | 0.7195  |
| toilet       | 0.8909  | 0.9339  | 0.7526  | 0.7851  |
| dishwasher   | 0.1436  | 0.8800  | 0.1292  | 0.6400  |
| stove        | 0.1161  | 0.2245  | 0.0133  | 0.0408  |
| fireplace    | 0.5960  | 0.7222  | 0.1914  | 0.3704  |
| bed          | 0.8611  | 0.9558  | 0.7235  | 0.7735  |
| bathtub      | 0.9488  | 0.9592  | 0.8543  | 0.8776  |
| washer       | 0.7310  | 0.8772  | 0.6066  | 0.7018  |
+--------------+---------+---------+---------+---------+
| Overall      | 0.5393  | 0.7173  | 0.3450  | 0.4654  |
+--------------+---------+---------+---------+---------+
2024-08-25 10:19:42,115 - mmdet - INFO - Epoch(val) [4][1685]	sofa_AP_0.25: 0.7521, chair_AP_0.25: 0.6490, table_AP_0.25: 0.6267, cabinet_AP_0.25: 0.5034, stool_AP_0.25: 0.2284, tv_monitor_AP_0.25: 0.0112, oven_AP_0.25: 0.5368, shelf_AP_0.25: 0.3837, sink_AP_0.25: 0.4470, refrigerator_AP_0.25: 0.7426, toilet_AP_0.25: 0.8909, dishwasher_AP_0.25: 0.1436, stove_AP_0.25: 0.1161, fireplace_AP_0.25: 0.5960, bed_AP_0.25: 0.8611, bathtub_AP_0.25: 0.9488, washer_AP_0.25: 0.7310, mAP_0.25: 0.5393, sofa_rec_0.25: 0.8478, chair_rec_0.25: 0.8263, table_rec_0.25: 0.8627, cabinet_rec_0.25: 0.6483, stool_rec_0.25: 0.6344, tv_monitor_rec_0.25: 0.0996, oven_rec_0.25: 0.6753, shelf_rec_0.25: 0.6165, sink_rec_0.25: 0.5032, refrigerator_rec_0.25: 0.9268, toilet_rec_0.25: 0.9339, dishwasher_rec_0.25: 0.8800, stove_rec_0.25: 0.2245, fireplace_rec_0.25: 0.7222, bed_rec_0.25: 0.9558, bathtub_rec_0.25: 0.9592, washer_rec_0.25: 0.8772, mAR_0.25: 0.7173, sofa_AP_0.50: 0.5125, chair_AP_0.50: 0.3483, table_AP_0.50: 0.3106, cabinet_AP_0.50: 0.2043, stool_AP_0.50: 0.1006, tv_monitor_AP_0.50: 0.0000, oven_AP_0.50: 0.3211, shelf_AP_0.50: 0.0668, sink_AP_0.50: 0.1323, refrigerator_AP_0.50: 0.5972, toilet_AP_0.50: 0.7526, dishwasher_AP_0.50: 0.1292, stove_AP_0.50: 0.0133, fireplace_AP_0.50: 0.1914, bed_AP_0.50: 0.7235, bathtub_AP_0.50: 0.8543, washer_AP_0.50: 0.6066, mAP_0.50: 0.3450, sofa_rec_0.50: 0.6142, chair_rec_0.50: 0.4888, table_rec_0.50: 0.4673, cabinet_rec_0.50: 0.3184, stool_rec_0.50: 0.3172, tv_monitor_rec_0.50: 0.0036, oven_rec_0.50: 0.4351, shelf_rec_0.50: 0.1650, sink_rec_0.50: 0.1943, refrigerator_rec_0.50: 0.7195, toilet_rec_0.50: 0.7851, dishwasher_rec_0.50: 0.6400, stove_rec_0.50: 0.0408, fireplace_rec_0.50: 0.3704, bed_rec_0.50: 0.7735, bathtub_rec_0.50: 0.8776, washer_rec_0.50: 0.7018, mAR_0.50: 0.4654
2024-08-25 10:22:16,661 - mmdet - INFO - Epoch [5][50/1685]	lr: 1.000e-04, eta: 10:38:45, time: 3.090, data_time: 0.138, memory: 19416, loss_occ: 0.5580, acc_occ: 0.8707, loss_centerness: 0.6131, loss_bbox: 0.4558, loss_cls: 0.2788, loss: 1.9058, grad_norm: 3.7487
2024-08-25 10:24:43,597 - mmdet - INFO - Epoch [5][100/1685]	lr: 1.000e-04, eta: 10:36:31, time: 2.939, data_time: 0.011, memory: 19416, loss_occ: 0.5452, acc_occ: 0.8711, loss_centerness: 0.6149, loss_bbox: 0.4555, loss_cls: 0.2745, loss: 1.8901, grad_norm: 3.6880
2024-08-25 10:27:11,357 - mmdet - INFO - Epoch [5][150/1685]	lr: 1.000e-04, eta: 10:34:18, time: 2.955, data_time: 0.010, memory: 19416, loss_occ: 0.5553, acc_occ: 0.8687, loss_centerness: 0.6173, loss_bbox: 0.4635, loss_cls: 0.2851, loss: 1.9212, grad_norm: 3.6172
2024-08-25 10:29:39,198 - mmdet - INFO - Epoch [5][200/1685]	lr: 1.000e-04, eta: 10:32:05, time: 2.957, data_time: 0.011, memory: 19416, loss_occ: 0.5613, acc_occ: 0.8684, loss_centerness: 0.6138, loss_bbox: 0.4543, loss_cls: 0.2757, loss: 1.9051, grad_norm: 3.5568
2024-08-25 10:32:08,590 - mmdet - INFO - Epoch [5][250/1685]	lr: 1.000e-04, eta: 10:29:54, time: 2.988, data_time: 0.010, memory: 19416, loss_occ: 0.5617, acc_occ: 0.8721, loss_centerness: 0.6162, loss_bbox: 0.4563, loss_cls: 0.2722, loss: 1.9064, grad_norm: 3.7866
2024-08-25 10:34:37,150 - mmdet - INFO - Epoch [5][300/1685]	lr: 1.000e-04, eta: 10:27:42, time: 2.971, data_time: 0.010, memory: 19416, loss_occ: 0.5436, acc_occ: 0.8696, loss_centerness: 0.6149, loss_bbox: 0.4586, loss_cls: 0.2819, loss: 1.8991, grad_norm: 3.8712
2024-08-25 10:37:04,637 - mmdet - INFO - Epoch [5][350/1685]	lr: 1.000e-04, eta: 10:25:28, time: 2.950, data_time: 0.013, memory: 19416, loss_occ: 0.5370, acc_occ: 0.8681, loss_centerness: 0.6183, loss_bbox: 0.4582, loss_cls: 0.2800, loss: 1.8935, grad_norm: 3.9388
2024-08-25 10:39:31,480 - mmdet - INFO - Epoch [5][400/1685]	lr: 1.000e-04, eta: 10:23:12, time: 2.937, data_time: 0.017, memory: 19416, loss_occ: 0.5342, acc_occ: 0.8646, loss_centerness: 0.6199, loss_bbox: 0.4533, loss_cls: 0.2730, loss: 1.8806, grad_norm: 3.6685
2024-08-25 10:41:59,199 - mmdet - INFO - Epoch [5][450/1685]	lr: 1.000e-04, eta: 10:20:58, time: 2.954, data_time: 0.018, memory: 19416, loss_occ: 0.5401, acc_occ: 0.8717, loss_centerness: 0.6123, loss_bbox: 0.4560, loss_cls: 0.2742, loss: 1.8825, grad_norm: 3.5925
2024-08-25 10:44:26,868 - mmdet - INFO - Epoch [5][500/1685]	lr: 1.000e-04, eta: 10:18:43, time: 2.953, data_time: 0.015, memory: 19416, loss_occ: 0.5472, acc_occ: 0.8742, loss_centerness: 0.6151, loss_bbox: 0.4490, loss_cls: 0.2660, loss: 1.8772, grad_norm: 3.7758
2024-08-25 10:46:51,535 - mmdet - INFO - Epoch [5][550/1685]	lr: 1.000e-04, eta: 10:16:23, time: 2.893, data_time: 0.015, memory: 19416, loss_occ: 0.5558, acc_occ: 0.8728, loss_centerness: 0.6115, loss_bbox: 0.4600, loss_cls: 0.2808, loss: 1.9082, grad_norm: 3.7766
2024-08-25 10:49:20,808 - mmdet - INFO - Epoch [5][600/1685]	lr: 1.000e-04, eta: 10:14:11, time: 2.985, data_time: 0.017, memory: 19416, loss_occ: 0.5523, acc_occ: 0.8753, loss_centerness: 0.6107, loss_bbox: 0.4499, loss_cls: 0.2701, loss: 1.8830, grad_norm: 4.0132
2024-08-25 10:51:50,914 - mmdet - INFO - Epoch [5][650/1685]	lr: 1.000e-04, eta: 10:12:00, time: 3.002, data_time: 0.015, memory: 19416, loss_occ: 0.5578, acc_occ: 0.8734, loss_centerness: 0.6182, loss_bbox: 0.4477, loss_cls: 0.2748, loss: 1.8984, grad_norm: 3.6875
2024-08-25 10:54:19,720 - mmdet - INFO - Epoch [5][700/1685]	lr: 1.000e-04, eta: 10:09:47, time: 2.976, data_time: 0.014, memory: 19416, loss_occ: 0.5471, acc_occ: 0.8754, loss_centerness: 0.6175, loss_bbox: 0.4443, loss_cls: 0.2652, loss: 1.8742, grad_norm: 3.7580
2024-08-25 10:56:46,472 - mmdet - INFO - Epoch [5][750/1685]	lr: 1.000e-04, eta: 10:07:30, time: 2.935, data_time: 0.016, memory: 19416, loss_occ: 0.5515, acc_occ: 0.8727, loss_centerness: 0.6128, loss_bbox: 0.4546, loss_cls: 0.2747, loss: 1.8935, grad_norm: 3.6431
2024-08-25 10:59:11,053 - mmdet - INFO - Epoch [5][800/1685]	lr: 1.000e-04, eta: 10:05:09, time: 2.892, data_time: 0.014, memory: 19416, loss_occ: 0.5397, acc_occ: 0.8690, loss_centerness: 0.6167, loss_bbox: 0.4501, loss_cls: 0.2776, loss: 1.8841, grad_norm: 3.7005
2024-08-25 11:01:37,035 - mmdet - INFO - Epoch [5][850/1685]	lr: 1.000e-04, eta: 10:02:51, time: 2.920, data_time: 0.014, memory: 19416, loss_occ: 0.5421, acc_occ: 0.8742, loss_centerness: 0.6167, loss_bbox: 0.4521, loss_cls: 0.2740, loss: 1.8849, grad_norm: 3.6553
2024-08-25 11:04:04,555 - mmdet - INFO - Epoch [5][900/1685]	lr: 1.000e-04, eta: 10:00:35, time: 2.950, data_time: 0.015, memory: 19416, loss_occ: 0.5719, acc_occ: 0.8731, loss_centerness: 0.6092, loss_bbox: 0.4502, loss_cls: 0.2660, loss: 1.8972, grad_norm: 3.6441
2024-08-25 11:06:31,037 - mmdet - INFO - Epoch [5][950/1685]	lr: 1.000e-04, eta: 9:58:17, time: 2.930, data_time: 0.015, memory: 19416, loss_occ: 0.5647, acc_occ: 0.8678, loss_centerness: 0.6158, loss_bbox: 0.4532, loss_cls: 0.2769, loss: 1.9107, grad_norm: 3.5294
2024-08-25 11:08:57,818 - mmdet - INFO - Epoch [5][1000/1685]	lr: 1.000e-04, eta: 9:55:59, time: 2.936, data_time: 0.019, memory: 19416, loss_occ: 0.5401, acc_occ: 0.8724, loss_centerness: 0.6166, loss_bbox: 0.4575, loss_cls: 0.2797, loss: 1.8938, grad_norm: 3.6779
2024-08-25 11:11:32,431 - mmdet - INFO - Epoch [5][1050/1685]	lr: 1.000e-04, eta: 9:53:54, time: 3.092, data_time: 0.014, memory: 19416, loss_occ: 0.5498, acc_occ: 0.8742, loss_centerness: 0.6134, loss_bbox: 0.4541, loss_cls: 0.2736, loss: 1.8908, grad_norm: 3.7654
2024-08-25 11:14:00,368 - mmdet - INFO - Epoch [5][1100/1685]	lr: 1.000e-04, eta: 9:51:38, time: 2.959, data_time: 0.012, memory: 19416, loss_occ: 0.5364, acc_occ: 0.8727, loss_centerness: 0.6158, loss_bbox: 0.4470, loss_cls: 0.2736, loss: 1.8728, grad_norm: 3.5908
2024-08-25 11:16:28,017 - mmdet - INFO - Epoch [5][1150/1685]	lr: 1.000e-04, eta: 9:49:21, time: 2.953, data_time: 0.015, memory: 19416, loss_occ: 0.5355, acc_occ: 0.8761, loss_centerness: 0.6114, loss_bbox: 0.4448, loss_cls: 0.2903, loss: 1.8820, grad_norm: 4.1318
2024-08-25 11:18:50,543 - mmdet - INFO - Epoch [5][1200/1685]	lr: 1.000e-04, eta: 9:46:57, time: 2.851, data_time: 0.014, memory: 19416, loss_occ: 0.5544, acc_occ: 0.8675, loss_centerness: 0.6112, loss_bbox: 0.4532, loss_cls: 0.2999, loss: 1.9186, grad_norm: 3.7285
2024-08-25 11:21:14,509 - mmdet - INFO - Epoch [5][1250/1685]	lr: 1.000e-04, eta: 9:44:34, time: 2.879, data_time: 0.014, memory: 19416, loss_occ: 0.5509, acc_occ: 0.8706, loss_centerness: 0.6099, loss_bbox: 0.4467, loss_cls: 0.2830, loss: 1.8904, grad_norm: 4.0024
2024-08-25 11:23:38,300 - mmdet - INFO - Epoch [5][1300/1685]	lr: 1.000e-04, eta: 9:42:11, time: 2.876, data_time: 0.015, memory: 19416, loss_occ: 0.5469, acc_occ: 0.8739, loss_centerness: 0.6163, loss_bbox: 0.4502, loss_cls: 0.2814, loss: 1.8949, grad_norm: 3.9314
2024-08-25 11:26:02,964 - mmdet - INFO - Epoch [5][1350/1685]	lr: 1.000e-04, eta: 9:39:50, time: 2.893, data_time: 0.015, memory: 19416, loss_occ: 0.5322, acc_occ: 0.8741, loss_centerness: 0.6141, loss_bbox: 0.4439, loss_cls: 0.2687, loss: 1.8589, grad_norm: 3.5144
2024-08-25 11:28:29,044 - mmdet - INFO - Epoch [5][1400/1685]	lr: 1.000e-04, eta: 9:37:30, time: 2.922, data_time: 0.014, memory: 19416, loss_occ: 0.5582, acc_occ: 0.8726, loss_centerness: 0.6155, loss_bbox: 0.4493, loss_cls: 0.2754, loss: 1.8985, grad_norm: 3.5284
2024-08-25 11:30:54,927 - mmdet - INFO - Epoch [5][1450/1685]	lr: 1.000e-04, eta: 9:35:10, time: 2.918, data_time: 0.013, memory: 19416, loss_occ: 0.5766, acc_occ: 0.8731, loss_centerness: 0.6162, loss_bbox: 0.4424, loss_cls: 0.2650, loss: 1.9003, grad_norm: 3.7211
2024-08-25 11:33:19,807 - mmdet - INFO - Epoch [5][1500/1685]	lr: 1.000e-04, eta: 9:32:49, time: 2.898, data_time: 0.015, memory: 19416, loss_occ: 0.5489, acc_occ: 0.8732, loss_centerness: 0.6113, loss_bbox: 0.4414, loss_cls: 0.2622, loss: 1.8639, grad_norm: 3.8783
2024-08-25 11:35:47,335 - mmdet - INFO - Epoch [5][1550/1685]	lr: 1.000e-04, eta: 9:30:32, time: 2.951, data_time: 0.016, memory: 19416, loss_occ: 0.5309, acc_occ: 0.8775, loss_centerness: 0.6121, loss_bbox: 0.4517, loss_cls: 0.2709, loss: 1.8658, grad_norm: 3.6135
2024-08-25 11:38:14,442 - mmdet - INFO - Epoch [5][1600/1685]	lr: 1.000e-04, eta: 9:28:13, time: 2.942, data_time: 0.014, memory: 19416, loss_occ: 0.5505, acc_occ: 0.8764, loss_centerness: 0.6140, loss_bbox: 0.4458, loss_cls: 0.2735, loss: 1.8838, grad_norm: 3.5788
2024-08-25 11:40:40,860 - mmdet - INFO - Epoch [5][1650/1685]	lr: 1.000e-04, eta: 9:25:54, time: 2.928, data_time: 0.014, memory: 19416, loss_occ: 0.5331, acc_occ: 0.8760, loss_centerness: 0.6133, loss_bbox: 0.4416, loss_cls: 0.2630, loss: 1.8509, grad_norm: 3.5817
2024-08-25 11:42:24,703 - mmdet - INFO - Saving checkpoint at 5 epochs
2024-08-25 11:44:36,676 - mmdet - INFO - 
+--------------+---------+---------+---------+---------+
| classes      | AP_0.25 | AR_0.25 | AP_0.50 | AR_0.50 |
+--------------+---------+---------+---------+---------+
| sofa         | 0.7555  | 0.8451  | 0.5960  | 0.6640  |
| chair        | 0.6758  | 0.8450  | 0.3618  | 0.5088  |
| table        | 0.6700  | 0.8644  | 0.3421  | 0.5033  |
| cabinet      | 0.5055  | 0.6506  | 0.2123  | 0.3259  |
| stool        | 0.1830  | 0.5860  | 0.0796  | 0.2419  |
| tv_monitor   | 0.0223  | 0.1068  | 0.0000  | 0.0000  |
| refrigerator | 0.7631  | 0.9512  | 0.6519  | 0.7561  |
| oven         | 0.5442  | 0.7208  | 0.3123  | 0.4351  |
| shelf        | 0.4040  | 0.6553  | 0.1128  | 0.2427  |
| toilet       | 0.9060  | 0.9421  | 0.7215  | 0.7686  |
| dishwasher   | 0.0807  | 0.8800  | 0.0588  | 0.6000  |
| bathtub      | 0.9488  | 0.9490  | 0.8449  | 0.8776  |
| bed          | 0.8647  | 0.9337  | 0.7556  | 0.8011  |
| stove        | 0.1017  | 0.2143  | 0.0002  | 0.0102  |
| washer       | 0.7505  | 0.8684  | 0.6139  | 0.7105  |
| fireplace    | 0.6004  | 0.7593  | 0.1121  | 0.2963  |
| sink         | 0.4609  | 0.5032  | 0.1506  | 0.2166  |
+--------------+---------+---------+---------+---------+
| Overall      | 0.5434  | 0.7221  | 0.3486  | 0.4682  |
+--------------+---------+---------+---------+---------+
2024-08-25 11:44:37,214 - mmdet - INFO - Epoch(val) [5][1685]	sofa_AP_0.25: 0.7555, chair_AP_0.25: 0.6758, table_AP_0.25: 0.6700, cabinet_AP_0.25: 0.5055, stool_AP_0.25: 0.1830, tv_monitor_AP_0.25: 0.0223, refrigerator_AP_0.25: 0.7631, oven_AP_0.25: 0.5442, shelf_AP_0.25: 0.4040, toilet_AP_0.25: 0.9060, dishwasher_AP_0.25: 0.0807, bathtub_AP_0.25: 0.9488, bed_AP_0.25: 0.8647, stove_AP_0.25: 0.1017, washer_AP_0.25: 0.7505, fireplace_AP_0.25: 0.6004, sink_AP_0.25: 0.4609, mAP_0.25: 0.5434, sofa_rec_0.25: 0.8451, chair_rec_0.25: 0.8450, table_rec_0.25: 0.8644, cabinet_rec_0.25: 0.6506, stool_rec_0.25: 0.5860, tv_monitor_rec_0.25: 0.1068, refrigerator_rec_0.25: 0.9512, oven_rec_0.25: 0.7208, shelf_rec_0.25: 0.6553, toilet_rec_0.25: 0.9421, dishwasher_rec_0.25: 0.8800, bathtub_rec_0.25: 0.9490, bed_rec_0.25: 0.9337, stove_rec_0.25: 0.2143, washer_rec_0.25: 0.8684, fireplace_rec_0.25: 0.7593, sink_rec_0.25: 0.5032, mAR_0.25: 0.7221, sofa_AP_0.50: 0.5960, chair_AP_0.50: 0.3618, table_AP_0.50: 0.3421, cabinet_AP_0.50: 0.2123, stool_AP_0.50: 0.0796, tv_monitor_AP_0.50: 0.0000, refrigerator_AP_0.50: 0.6519, oven_AP_0.50: 0.3123, shelf_AP_0.50: 0.1128, toilet_AP_0.50: 0.7215, dishwasher_AP_0.50: 0.0588, bathtub_AP_0.50: 0.8449, bed_AP_0.50: 0.7556, stove_AP_0.50: 0.0002, washer_AP_0.50: 0.6139, fireplace_AP_0.50: 0.1121, sink_AP_0.50: 0.1506, mAP_0.50: 0.3486, sofa_rec_0.50: 0.6640, chair_rec_0.50: 0.5088, table_rec_0.50: 0.5033, cabinet_rec_0.50: 0.3259, stool_rec_0.50: 0.2419, tv_monitor_rec_0.50: 0.0000, refrigerator_rec_0.50: 0.7561, oven_rec_0.50: 0.4351, shelf_rec_0.50: 0.2427, toilet_rec_0.50: 0.7686, dishwasher_rec_0.50: 0.6000, bathtub_rec_0.50: 0.8776, bed_rec_0.50: 0.8011, stove_rec_0.50: 0.0102, washer_rec_0.50: 0.7105, fireplace_rec_0.50: 0.2963, sink_rec_0.50: 0.2166, mAR_0.50: 0.4682
2024-08-25 11:47:13,179 - mmdet - INFO - Epoch [6][50/1685]	lr: 1.000e-04, eta: 9:19:48, time: 3.119, data_time: 0.146, memory: 19416, loss_occ: 0.5315, acc_occ: 0.8752, loss_centerness: 0.6171, loss_bbox: 0.4371, loss_cls: 0.2594, loss: 1.8451, grad_norm: 3.2962
2024-08-25 11:49:41,994 - mmdet - INFO - Epoch [6][100/1685]	lr: 1.000e-04, eta: 9:17:33, time: 2.976, data_time: 0.011, memory: 19416, loss_occ: 0.5500, acc_occ: 0.8742, loss_centerness: 0.6155, loss_bbox: 0.4461, loss_cls: 0.2618, loss: 1.8734, grad_norm: 3.6261
2024-08-25 11:52:07,824 - mmdet - INFO - Epoch [6][150/1685]	lr: 1.000e-04, eta: 9:15:14, time: 2.917, data_time: 0.011, memory: 19416, loss_occ: 0.5544, acc_occ: 0.8774, loss_centerness: 0.6138, loss_bbox: 0.4406, loss_cls: 0.2608, loss: 1.8696, grad_norm: 3.8420
2024-08-25 11:54:28,416 - mmdet - INFO - Epoch [6][200/1685]	lr: 1.000e-04, eta: 9:12:47, time: 2.812, data_time: 0.013, memory: 19416, loss_occ: 0.5585, acc_occ: 0.8710, loss_centerness: 0.6124, loss_bbox: 0.4427, loss_cls: 0.2660, loss: 1.8795, grad_norm: 3.8207
2024-08-25 11:56:48,301 - mmdet - INFO - Epoch [6][250/1685]	lr: 1.000e-04, eta: 9:10:20, time: 2.798, data_time: 0.017, memory: 19416, loss_occ: 0.5566, acc_occ: 0.8775, loss_centerness: 0.6119, loss_bbox: 0.4327, loss_cls: 0.2475, loss: 1.8486, grad_norm: 3.6717
2024-08-25 11:59:09,120 - mmdet - INFO - Epoch [6][300/1685]	lr: 1.000e-04, eta: 9:07:54, time: 2.816, data_time: 0.011, memory: 19416, loss_occ: 0.5416, acc_occ: 0.8734, loss_centerness: 0.6141, loss_bbox: 0.4363, loss_cls: 0.2549, loss: 1.8469, grad_norm: 3.8137
2024-08-25 12:01:31,297 - mmdet - INFO - Epoch [6][350/1685]	lr: 1.000e-04, eta: 9:05:30, time: 2.844, data_time: 0.010, memory: 19416, loss_occ: 0.5499, acc_occ: 0.8773, loss_centerness: 0.6116, loss_bbox: 0.4351, loss_cls: 0.2612, loss: 1.8579, grad_norm: 3.7474
2024-08-25 12:03:51,449 - mmdet - INFO - Epoch [6][400/1685]	lr: 1.000e-04, eta: 9:03:04, time: 2.803, data_time: 0.010, memory: 19416, loss_occ: 0.5413, acc_occ: 0.8766, loss_centerness: 0.6102, loss_bbox: 0.4362, loss_cls: 0.2667, loss: 1.8543, grad_norm: 3.6301
2024-08-25 12:06:18,027 - mmdet - INFO - Epoch [6][450/1685]	lr: 1.000e-04, eta: 9:00:45, time: 2.932, data_time: 0.012, memory: 19416, loss_occ: 0.5585, acc_occ: 0.8741, loss_centerness: 0.6128, loss_bbox: 0.4410, loss_cls: 0.2608, loss: 1.8731, grad_norm: 3.8950
2024-08-25 12:08:45,681 - mmdet - INFO - Epoch [6][500/1685]	lr: 1.000e-04, eta: 8:58:28, time: 2.953, data_time: 0.011, memory: 19416, loss_occ: 0.5408, acc_occ: 0.8836, loss_centerness: 0.6115, loss_bbox: 0.4351, loss_cls: 0.2508, loss: 1.8382, grad_norm: 3.6415
2024-08-25 12:11:14,620 - mmdet - INFO - Epoch [6][550/1685]	lr: 1.000e-04, eta: 8:56:12, time: 2.979, data_time: 0.014, memory: 19416, loss_occ: 0.5483, acc_occ: 0.8710, loss_centerness: 0.6146, loss_bbox: 0.4416, loss_cls: 0.2530, loss: 1.8575, grad_norm: 3.8795
2024-08-25 12:13:45,038 - mmdet - INFO - Epoch [6][600/1685]	lr: 1.000e-04, eta: 8:53:59, time: 3.008, data_time: 0.010, memory: 19416, loss_occ: 0.5485, acc_occ: 0.8748, loss_centerness: 0.6094, loss_bbox: 0.4384, loss_cls: 0.2516, loss: 1.8478, grad_norm: 3.5790
2024-08-25 12:16:14,589 - mmdet - INFO - Epoch [6][650/1685]	lr: 1.000e-04, eta: 8:51:43, time: 2.991, data_time: 0.012, memory: 19416, loss_occ: 0.5489, acc_occ: 0.8786, loss_centerness: 0.6150, loss_bbox: 0.4359, loss_cls: 0.2549, loss: 1.8547, grad_norm: 4.0069
2024-08-25 12:18:44,628 - mmdet - INFO - Epoch [6][700/1685]	lr: 1.000e-04, eta: 8:49:29, time: 3.001, data_time: 0.012, memory: 19416, loss_occ: 0.5440, acc_occ: 0.8753, loss_centerness: 0.6130, loss_bbox: 0.4349, loss_cls: 0.2491, loss: 1.8410, grad_norm: 3.5560
2024-08-25 12:21:13,969 - mmdet - INFO - Epoch [6][750/1685]	lr: 1.000e-04, eta: 8:47:13, time: 2.987, data_time: 0.018, memory: 19416, loss_occ: 0.5532, acc_occ: 0.8759, loss_centerness: 0.6149, loss_bbox: 0.4341, loss_cls: 0.2568, loss: 1.8590, grad_norm: 3.8050
2024-08-25 12:23:43,566 - mmdet - INFO - Epoch [6][800/1685]	lr: 1.000e-04, eta: 8:44:57, time: 2.992, data_time: 0.014, memory: 19416, loss_occ: 0.5419, acc_occ: 0.8753, loss_centerness: 0.6150, loss_bbox: 0.4427, loss_cls: 0.2925, loss: 1.8922, grad_norm: 4.1547
2024-08-25 12:26:11,577 - mmdet - INFO - Epoch [6][850/1685]	lr: 1.000e-04, eta: 8:42:40, time: 2.960, data_time: 0.015, memory: 19416, loss_occ: 0.5517, acc_occ: 0.8821, loss_centerness: 0.6151, loss_bbox: 0.4383, loss_cls: 0.2667, loss: 1.8718, grad_norm: 3.6664
2024-08-25 12:28:38,031 - mmdet - INFO - Epoch [6][900/1685]	lr: 1.000e-04, eta: 8:40:20, time: 2.929, data_time: 0.015, memory: 19416, loss_occ: 0.5275, acc_occ: 0.8795, loss_centerness: 0.6126, loss_bbox: 0.4333, loss_cls: 0.2554, loss: 1.8288, grad_norm: 3.7166
2024-08-25 12:31:03,944 - mmdet - INFO - Epoch [6][950/1685]	lr: 1.000e-04, eta: 8:38:00, time: 2.918, data_time: 0.014, memory: 19416, loss_occ: 0.5324, acc_occ: 0.8771, loss_centerness: 0.6133, loss_bbox: 0.4387, loss_cls: 0.2637, loss: 1.8481, grad_norm: 3.6650
2024-08-25 12:33:29,091 - mmdet - INFO - Epoch [6][1000/1685]	lr: 1.000e-04, eta: 8:35:39, time: 2.903, data_time: 0.014, memory: 19416, loss_occ: 0.5518, acc_occ: 0.8774, loss_centerness: 0.6131, loss_bbox: 0.4424, loss_cls: 0.2612, loss: 1.8685, grad_norm: 3.8777
2024-08-25 12:35:57,297 - mmdet - INFO - Epoch [6][1050/1685]	lr: 1.000e-04, eta: 8:33:21, time: 2.964, data_time: 0.014, memory: 19416, loss_occ: 0.5355, acc_occ: 0.8779, loss_centerness: 0.6112, loss_bbox: 0.4297, loss_cls: 0.2525, loss: 1.8290, grad_norm: 3.6032
2024-08-25 12:38:27,043 - mmdet - INFO - Epoch [6][1100/1685]	lr: 1.000e-04, eta: 8:31:05, time: 2.995, data_time: 0.017, memory: 19416, loss_occ: 0.5583, acc_occ: 0.8761, loss_centerness: 0.6135, loss_bbox: 0.4307, loss_cls: 0.2530, loss: 1.8556, grad_norm: 3.5956
2024-08-25 12:40:53,315 - mmdet - INFO - Epoch [6][1150/1685]	lr: 1.000e-04, eta: 8:28:45, time: 2.925, data_time: 0.014, memory: 19416, loss_occ: 0.5410, acc_occ: 0.8784, loss_centerness: 0.6152, loss_bbox: 0.4388, loss_cls: 0.2594, loss: 1.8544, grad_norm: 3.5607
2024-08-25 12:43:20,363 - mmdet - INFO - Epoch [6][1200/1685]	lr: 1.000e-04, eta: 8:26:25, time: 2.941, data_time: 0.017, memory: 19416, loss_occ: 0.5417, acc_occ: 0.8751, loss_centerness: 0.6145, loss_bbox: 0.4363, loss_cls: 0.2550, loss: 1.8475, grad_norm: 3.7290
2024-08-25 12:45:45,645 - mmdet - INFO - Epoch [6][1250/1685]	lr: 1.000e-04, eta: 8:24:04, time: 2.906, data_time: 0.016, memory: 19416, loss_occ: 0.5372, acc_occ: 0.8789, loss_centerness: 0.6143, loss_bbox: 0.4368, loss_cls: 0.2598, loss: 1.8480, grad_norm: 3.7408
2024-08-25 12:48:13,967 - mmdet - INFO - Epoch [6][1300/1685]	lr: 1.000e-04, eta: 8:21:46, time: 2.966, data_time: 0.015, memory: 19416, loss_occ: 0.5471, acc_occ: 0.8761, loss_centerness: 0.6133, loss_bbox: 0.4341, loss_cls: 0.2561, loss: 1.8506, grad_norm: 3.6970
2024-08-25 12:50:42,343 - mmdet - INFO - Epoch [6][1350/1685]	lr: 1.000e-04, eta: 8:19:28, time: 2.968, data_time: 0.014, memory: 19416, loss_occ: 0.5373, acc_occ: 0.8700, loss_centerness: 0.6153, loss_bbox: 0.4375, loss_cls: 0.2567, loss: 1.8468, grad_norm: 3.7656
2024-08-25 12:53:08,234 - mmdet - INFO - Epoch [6][1400/1685]	lr: 1.000e-04, eta: 8:17:07, time: 2.918, data_time: 0.014, memory: 19416, loss_occ: 0.5440, acc_occ: 0.8793, loss_centerness: 0.6124, loss_bbox: 0.4336, loss_cls: 0.2601, loss: 1.8501, grad_norm: 3.8494
2024-08-25 12:55:34,591 - mmdet - INFO - Epoch [6][1450/1685]	lr: 1.000e-04, eta: 8:14:47, time: 2.927, data_time: 0.014, memory: 19416, loss_occ: 0.5307, acc_occ: 0.8791, loss_centerness: 0.6114, loss_bbox: 0.4308, loss_cls: 0.2462, loss: 1.8191, grad_norm: 3.5783
2024-08-25 12:58:02,737 - mmdet - INFO - Epoch [6][1500/1685]	lr: 1.000e-04, eta: 8:12:28, time: 2.963, data_time: 0.014, memory: 19416, loss_occ: 0.5313, acc_occ: 0.8758, loss_centerness: 0.6129, loss_bbox: 0.4298, loss_cls: 0.2494, loss: 1.8234, grad_norm: 3.4281
2024-08-25 13:00:31,039 - mmdet - INFO - Epoch [6][1550/1685]	lr: 1.000e-04, eta: 8:10:09, time: 2.966, data_time: 0.014, memory: 19416, loss_occ: 0.5308, acc_occ: 0.8769, loss_centerness: 0.6113, loss_bbox: 0.4302, loss_cls: 0.2585, loss: 1.8308, grad_norm: 3.5687
2024-08-25 13:02:58,250 - mmdet - INFO - Epoch [6][1600/1685]	lr: 1.000e-04, eta: 8:07:50, time: 2.944, data_time: 0.015, memory: 19416, loss_occ: 0.5248, acc_occ: 0.8811, loss_centerness: 0.6124, loss_bbox: 0.4213, loss_cls: 0.2388, loss: 1.7973, grad_norm: 3.7680
2024-08-25 13:05:28,763 - mmdet - INFO - Epoch [6][1650/1685]	lr: 1.000e-04, eta: 8:05:33, time: 3.010, data_time: 0.014, memory: 19416, loss_occ: 0.5414, acc_occ: 0.8801, loss_centerness: 0.6081, loss_bbox: 0.4335, loss_cls: 0.2507, loss: 1.8337, grad_norm: 3.7175
2024-08-25 13:07:07,766 - mmdet - INFO - Saving checkpoint at 6 epochs
2024-08-25 13:09:18,199 - mmdet - INFO - 
+--------------+---------+---------+---------+---------+
| classes      | AP_0.25 | AR_0.25 | AP_0.50 | AR_0.50 |
+--------------+---------+---------+---------+---------+
| sofa         | 0.7638  | 0.8530  | 0.6014  | 0.6693  |
| chair        | 0.6840  | 0.8462  | 0.4113  | 0.5550  |
| table        | 0.6646  | 0.8611  | 0.3885  | 0.5212  |
| cabinet      | 0.5329  | 0.6550  | 0.2541  | 0.3579  |
| stool        | 0.2323  | 0.6022  | 0.0870  | 0.2366  |
| tv_monitor   | 0.0070  | 0.0783  | 0.0000  | 0.0000  |
| oven         | 0.6111  | 0.7403  | 0.3241  | 0.4351  |
| sink         | 0.4764  | 0.5318  | 0.1710  | 0.2357  |
| shelf        | 0.4346  | 0.6748  | 0.1148  | 0.2427  |
| toilet       | 0.9107  | 0.9421  | 0.7456  | 0.7851  |
| dishwasher   | 0.1364  | 0.8800  | 0.1139  | 0.6400  |
| refrigerator | 0.7823  | 0.9878  | 0.6640  | 0.7805  |
| bathtub      | 0.9463  | 0.9592  | 0.7658  | 0.8367  |
| fireplace    | 0.5740  | 0.7407  | 0.1323  | 0.2778  |
| washer       | 0.7604  | 0.8947  | 0.6410  | 0.7368  |
| bed          | 0.8670  | 0.9337  | 0.7530  | 0.8177  |
| stove        | 0.1522  | 0.2245  | 0.0119  | 0.0408  |
+--------------+---------+---------+---------+---------+
| Overall      | 0.5609  | 0.7297  | 0.3635  | 0.4805  |
+--------------+---------+---------+---------+---------+
2024-08-25 13:09:18,689 - mmdet - INFO - Epoch(val) [6][1685]	sofa_AP_0.25: 0.7638, chair_AP_0.25: 0.6840, table_AP_0.25: 0.6646, cabinet_AP_0.25: 0.5329, stool_AP_0.25: 0.2323, tv_monitor_AP_0.25: 0.0070, oven_AP_0.25: 0.6111, sink_AP_0.25: 0.4764, shelf_AP_0.25: 0.4346, toilet_AP_0.25: 0.9107, dishwasher_AP_0.25: 0.1364, refrigerator_AP_0.25: 0.7823, bathtub_AP_0.25: 0.9463, fireplace_AP_0.25: 0.5740, washer_AP_0.25: 0.7604, bed_AP_0.25: 0.8670, stove_AP_0.25: 0.1522, mAP_0.25: 0.5609, sofa_rec_0.25: 0.8530, chair_rec_0.25: 0.8462, table_rec_0.25: 0.8611, cabinet_rec_0.25: 0.6550, stool_rec_0.25: 0.6022, tv_monitor_rec_0.25: 0.0783, oven_rec_0.25: 0.7403, sink_rec_0.25: 0.5318, shelf_rec_0.25: 0.6748, toilet_rec_0.25: 0.9421, dishwasher_rec_0.25: 0.8800, refrigerator_rec_0.25: 0.9878, bathtub_rec_0.25: 0.9592, fireplace_rec_0.25: 0.7407, washer_rec_0.25: 0.8947, bed_rec_0.25: 0.9337, stove_rec_0.25: 0.2245, mAR_0.25: 0.7297, sofa_AP_0.50: 0.6014, chair_AP_0.50: 0.4113, table_AP_0.50: 0.3885, cabinet_AP_0.50: 0.2541, stool_AP_0.50: 0.0870, tv_monitor_AP_0.50: 0.0000, oven_AP_0.50: 0.3241, sink_AP_0.50: 0.1710, shelf_AP_0.50: 0.1148, toilet_AP_0.50: 0.7456, dishwasher_AP_0.50: 0.1139, refrigerator_AP_0.50: 0.6640, bathtub_AP_0.50: 0.7658, fireplace_AP_0.50: 0.1323, washer_AP_0.50: 0.6410, bed_AP_0.50: 0.7530, stove_AP_0.50: 0.0119, mAP_0.50: 0.3635, sofa_rec_0.50: 0.6693, chair_rec_0.50: 0.5550, table_rec_0.50: 0.5212, cabinet_rec_0.50: 0.3579, stool_rec_0.50: 0.2366, tv_monitor_rec_0.50: 0.0000, oven_rec_0.50: 0.4351, sink_rec_0.50: 0.2357, shelf_rec_0.50: 0.2427, toilet_rec_0.50: 0.7851, dishwasher_rec_0.50: 0.6400, refrigerator_rec_0.50: 0.7805, bathtub_rec_0.50: 0.8367, fireplace_rec_0.50: 0.2778, washer_rec_0.50: 0.7368, bed_rec_0.50: 0.8177, stove_rec_0.50: 0.0408, mAR_0.50: 0.4805
2024-08-25 13:11:53,090 - mmdet - INFO - Epoch [7][50/1685]	lr: 1.000e-04, eta: 8:00:00, time: 3.087, data_time: 0.143, memory: 19416, loss_occ: 0.5426, acc_occ: 0.8812, loss_centerness: 0.6091, loss_bbox: 0.4318, loss_cls: 0.2474, loss: 1.8310, grad_norm: 3.5595
2024-08-25 13:14:19,301 - mmdet - INFO - Epoch [7][100/1685]	lr: 1.000e-04, eta: 7:57:40, time: 2.924, data_time: 0.010, memory: 19416, loss_occ: 0.5316, acc_occ: 0.8808, loss_centerness: 0.6145, loss_bbox: 0.4247, loss_cls: 0.2445, loss: 1.8153, grad_norm: 3.7076
2024-08-25 13:16:45,728 - mmdet - INFO - Epoch [7][150/1685]	lr: 1.000e-04, eta: 7:55:20, time: 2.929, data_time: 0.011, memory: 19416, loss_occ: 0.5386, acc_occ: 0.8774, loss_centerness: 0.6115, loss_bbox: 0.4253, loss_cls: 0.2481, loss: 1.8235, grad_norm: 3.5225
2024-08-25 13:19:19,961 - mmdet - INFO - Epoch [7][200/1685]	lr: 1.000e-04, eta: 7:53:07, time: 3.085, data_time: 0.010, memory: 19416, loss_occ: 0.5336, acc_occ: 0.8845, loss_centerness: 0.6100, loss_bbox: 0.4217, loss_cls: 0.2371, loss: 1.8024, grad_norm: 3.6797
2024-08-25 13:21:43,876 - mmdet - INFO - Epoch [7][250/1685]	lr: 1.000e-04, eta: 7:50:45, time: 2.878, data_time: 0.011, memory: 19416, loss_occ: 0.5367, acc_occ: 0.8825, loss_centerness: 0.6130, loss_bbox: 0.4195, loss_cls: 0.2358, loss: 1.8050, grad_norm: 3.9129
2024-08-25 13:24:11,295 - mmdet - INFO - Epoch [7][300/1685]	lr: 1.000e-04, eta: 7:48:25, time: 2.948, data_time: 0.014, memory: 19416, loss_occ: 0.5487, acc_occ: 0.8800, loss_centerness: 0.6116, loss_bbox: 0.4282, loss_cls: 0.2399, loss: 1.8284, grad_norm: 3.7194
2024-08-25 13:26:38,857 - mmdet - INFO - Epoch [7][350/1685]	lr: 1.000e-04, eta: 7:46:06, time: 2.951, data_time: 0.016, memory: 19416, loss_occ: 0.5428, acc_occ: 0.8775, loss_centerness: 0.6129, loss_bbox: 0.4282, loss_cls: 0.2472, loss: 1.8311, grad_norm: 3.5501
2024-08-25 13:29:05,173 - mmdet - INFO - Epoch [7][400/1685]	lr: 1.000e-04, eta: 7:43:46, time: 2.926, data_time: 0.016, memory: 19416, loss_occ: 0.5408, acc_occ: 0.8795, loss_centerness: 0.6090, loss_bbox: 0.4126, loss_cls: 0.2362, loss: 1.7986, grad_norm: 3.6363
2024-08-25 13:31:30,128 - mmdet - INFO - Epoch [7][450/1685]	lr: 1.000e-04, eta: 7:41:24, time: 2.899, data_time: 0.014, memory: 19416, loss_occ: 0.5527, acc_occ: 0.8752, loss_centerness: 0.6118, loss_bbox: 0.4232, loss_cls: 0.2459, loss: 1.8337, grad_norm: 3.7233
2024-08-25 13:33:55,229 - mmdet - INFO - Epoch [7][500/1685]	lr: 1.000e-04, eta: 7:39:02, time: 2.902, data_time: 0.015, memory: 19416, loss_occ: 0.5465, acc_occ: 0.8794, loss_centerness: 0.6126, loss_bbox: 0.4239, loss_cls: 0.2442, loss: 1.8273, grad_norm: 3.4417
2024-08-25 13:36:14,727 - mmdet - INFO - Epoch [7][550/1685]	lr: 1.000e-04, eta: 7:36:36, time: 2.790, data_time: 0.015, memory: 19416, loss_occ: 0.5411, acc_occ: 0.8810, loss_centerness: 0.6122, loss_bbox: 0.4197, loss_cls: 0.2354, loss: 1.8084, grad_norm: 3.5209
2024-08-25 13:38:36,159 - mmdet - INFO - Epoch [7][600/1685]	lr: 1.000e-04, eta: 7:34:11, time: 2.829, data_time: 0.013, memory: 19416, loss_occ: 0.5433, acc_occ: 0.8788, loss_centerness: 0.6136, loss_bbox: 0.4243, loss_cls: 0.2361, loss: 1.8173, grad_norm: 3.6199
2024-08-25 13:40:55,984 - mmdet - INFO - Epoch [7][650/1685]	lr: 1.000e-04, eta: 7:31:44, time: 2.796, data_time: 0.012, memory: 19416, loss_occ: 0.5446, acc_occ: 0.8790, loss_centerness: 0.6104, loss_bbox: 0.4186, loss_cls: 0.2442, loss: 1.8177, grad_norm: 3.6947
2024-08-25 13:43:17,301 - mmdet - INFO - Epoch [7][700/1685]	lr: 1.000e-04, eta: 7:29:19, time: 2.826, data_time: 0.012, memory: 19416, loss_occ: 0.5398, acc_occ: 0.8801, loss_centerness: 0.6138, loss_bbox: 0.4201, loss_cls: 0.2357, loss: 1.8093, grad_norm: 3.5582
2024-08-25 13:45:36,981 - mmdet - INFO - Epoch [7][750/1685]	lr: 1.000e-04, eta: 7:26:53, time: 2.794, data_time: 0.011, memory: 19416, loss_occ: 0.5465, acc_occ: 0.8814, loss_centerness: 0.6125, loss_bbox: 0.4182, loss_cls: 0.2321, loss: 1.8094, grad_norm: 3.6406
2024-08-25 13:48:02,588 - mmdet - INFO - Epoch [7][800/1685]	lr: 1.000e-04, eta: 7:24:32, time: 2.912, data_time: 0.010, memory: 19416, loss_occ: 0.5335, acc_occ: 0.8804, loss_centerness: 0.6136, loss_bbox: 0.4276, loss_cls: 0.2508, loss: 1.8255, grad_norm: 3.6046
2024-08-25 13:50:29,864 - mmdet - INFO - Epoch [7][850/1685]	lr: 1.000e-04, eta: 7:22:12, time: 2.946, data_time: 0.015, memory: 19416, loss_occ: 0.5292, acc_occ: 0.8785, loss_centerness: 0.6133, loss_bbox: 0.4223, loss_cls: 0.2409, loss: 1.8057, grad_norm: 3.7989
2024-08-25 13:52:57,973 - mmdet - INFO - Epoch [7][900/1685]	lr: 1.000e-04, eta: 7:19:53, time: 2.962, data_time: 0.012, memory: 19416, loss_occ: 0.5294, acc_occ: 0.8814, loss_centerness: 0.6128, loss_bbox: 0.4236, loss_cls: 0.2501, loss: 1.8159, grad_norm: 3.6264
2024-08-25 13:55:23,848 - mmdet - INFO - Epoch [7][950/1685]	lr: 1.000e-04, eta: 7:17:32, time: 2.918, data_time: 0.010, memory: 19416, loss_occ: 0.5329, acc_occ: 0.8746, loss_centerness: 0.6125, loss_bbox: 0.4216, loss_cls: 0.2431, loss: 1.8101, grad_norm: 3.6792
2024-08-25 13:57:52,792 - mmdet - INFO - Epoch [7][1000/1685]	lr: 1.000e-04, eta: 7:15:13, time: 2.979, data_time: 0.011, memory: 19416, loss_occ: 0.5379, acc_occ: 0.8825, loss_centerness: 0.6120, loss_bbox: 0.4221, loss_cls: 0.2462, loss: 1.8182, grad_norm: 3.5953
2024-08-25 14:00:19,987 - mmdet - INFO - Epoch [7][1050/1685]	lr: 1.000e-04, eta: 7:12:53, time: 2.944, data_time: 0.010, memory: 19416, loss_occ: 0.5411, acc_occ: 0.8776, loss_centerness: 0.6103, loss_bbox: 0.4241, loss_cls: 0.2449, loss: 1.8204, grad_norm: 3.6059
2024-08-25 14:02:48,394 - mmdet - INFO - Epoch [7][1100/1685]	lr: 1.000e-04, eta: 7:10:34, time: 2.968, data_time: 0.010, memory: 19416, loss_occ: 0.5144, acc_occ: 0.8780, loss_centerness: 0.6119, loss_bbox: 0.4176, loss_cls: 0.2404, loss: 1.7844, grad_norm: 3.5142
2024-08-25 14:05:14,476 - mmdet - INFO - Epoch [7][1150/1685]	lr: 1.000e-04, eta: 7:08:12, time: 2.922, data_time: 0.010, memory: 19416, loss_occ: 0.5585, acc_occ: 0.8795, loss_centerness: 0.6114, loss_bbox: 0.4242, loss_cls: 0.2452, loss: 1.8394, grad_norm: 3.9722
2024-08-25 14:07:42,666 - mmdet - INFO - Epoch [7][1200/1685]	lr: 1.000e-04, eta: 7:05:53, time: 2.964, data_time: 0.011, memory: 19416, loss_occ: 0.5496, acc_occ: 0.8822, loss_centerness: 0.6119, loss_bbox: 0.4248, loss_cls: 0.2441, loss: 1.8304, grad_norm: 3.8077
2024-08-25 14:10:09,033 - mmdet - INFO - Epoch [7][1250/1685]	lr: 1.000e-04, eta: 7:03:32, time: 2.927, data_time: 0.011, memory: 19416, loss_occ: 0.5280, acc_occ: 0.8786, loss_centerness: 0.6114, loss_bbox: 0.4294, loss_cls: 0.2474, loss: 1.8162, grad_norm: 3.5900
2024-08-25 14:12:35,776 - mmdet - INFO - Epoch [7][1300/1685]	lr: 1.000e-04, eta: 7:01:11, time: 2.935, data_time: 0.012, memory: 19416, loss_occ: 0.5466, acc_occ: 0.8833, loss_centerness: 0.6069, loss_bbox: 0.4147, loss_cls: 0.2346, loss: 1.8029, grad_norm: 3.6462
2024-08-25 14:15:04,379 - mmdet - INFO - Epoch [7][1350/1685]	lr: 1.000e-04, eta: 6:58:51, time: 2.972, data_time: 0.013, memory: 19416, loss_occ: 0.5364, acc_occ: 0.8846, loss_centerness: 0.6145, loss_bbox: 0.4159, loss_cls: 0.2342, loss: 1.8009, grad_norm: 3.6525
2024-08-25 14:17:34,325 - mmdet - INFO - Epoch [7][1400/1685]	lr: 1.000e-04, eta: 6:56:33, time: 2.999, data_time: 0.014, memory: 19416, loss_occ: 0.5354, acc_occ: 0.8791, loss_centerness: 0.6119, loss_bbox: 0.4151, loss_cls: 0.2321, loss: 1.7945, grad_norm: 3.7834
2024-08-25 14:20:01,911 - mmdet - INFO - Epoch [7][1450/1685]	lr: 1.000e-04, eta: 6:54:13, time: 2.952, data_time: 0.015, memory: 19416, loss_occ: 0.5404, acc_occ: 0.8781, loss_centerness: 0.6119, loss_bbox: 0.4226, loss_cls: 0.2446, loss: 1.8195, grad_norm: 3.7179
2024-08-25 14:22:34,680 - mmdet - INFO - Epoch [7][1500/1685]	lr: 1.000e-04, eta: 6:51:56, time: 3.055, data_time: 0.015, memory: 19416, loss_occ: 0.5140, acc_occ: 0.8848, loss_centerness: 0.6095, loss_bbox: 0.4044, loss_cls: 0.2304, loss: 1.7584, grad_norm: 3.6568
2024-08-25 14:25:02,147 - mmdet - INFO - Epoch [7][1550/1685]	lr: 1.000e-04, eta: 6:49:35, time: 2.949, data_time: 0.013, memory: 19416, loss_occ: 0.5328, acc_occ: 0.8831, loss_centerness: 0.6082, loss_bbox: 0.4157, loss_cls: 0.2431, loss: 1.7998, grad_norm: 3.8599
2024-08-25 14:27:28,388 - mmdet - INFO - Epoch [7][1600/1685]	lr: 1.000e-04, eta: 6:47:14, time: 2.925, data_time: 0.014, memory: 19416, loss_occ: 0.5395, acc_occ: 0.8846, loss_centerness: 0.6094, loss_bbox: 0.4220, loss_cls: 0.2411, loss: 1.8120, grad_norm: 3.6758
2024-08-25 14:29:54,146 - mmdet - INFO - Epoch [7][1650/1685]	lr: 1.000e-04, eta: 6:44:52, time: 2.915, data_time: 0.015, memory: 19416, loss_occ: 0.5335, acc_occ: 0.8803, loss_centerness: 0.6123, loss_bbox: 0.4227, loss_cls: 0.2356, loss: 1.8042, grad_norm: 3.7439
2024-08-25 14:31:34,229 - mmdet - INFO - Saving checkpoint at 7 epochs
2024-08-25 14:33:43,111 - mmdet - INFO - 
+--------------+---------+---------+---------+---------+
| classes      | AP_0.25 | AR_0.25 | AP_0.50 | AR_0.50 |
+--------------+---------+---------+---------+---------+
| sofa         | 0.7676  | 0.8504  | 0.6272  | 0.6877  |
| chair        | 0.7202  | 0.8662  | 0.4167  | 0.5463  |
| table        | 0.6899  | 0.8660  | 0.3978  | 0.5588  |
| cabinet      | 0.5223  | 0.6634  | 0.2531  | 0.3641  |
| stool        | 0.2276  | 0.6075  | 0.1155  | 0.3065  |
| tv_monitor   | 0.0070  | 0.0854  | 0.0000  | 0.0000  |
| oven         | 0.6140  | 0.7273  | 0.3693  | 0.4740  |
| dishwasher   | 0.1607  | 0.8800  | 0.1393  | 0.6000  |
| shelf        | 0.4437  | 0.6408  | 0.1048  | 0.1942  |
| refrigerator | 0.7623  | 0.9512  | 0.6814  | 0.8049  |
| fireplace    | 0.6493  | 0.7222  | 0.2093  | 0.2778  |
| bathtub      | 0.9487  | 0.9490  | 0.8751  | 0.8980  |
| toilet       | 0.9060  | 0.9174  | 0.7884  | 0.8182  |
| sink         | 0.4761  | 0.5255  | 0.1886  | 0.2325  |
| washer       | 0.7539  | 0.8684  | 0.6397  | 0.7193  |
| bed          | 0.8779  | 0.9503  | 0.8099  | 0.8619  |
| stove        | 0.1623  | 0.2449  | 0.0059  | 0.0306  |
+--------------+---------+---------+---------+---------+
| Overall      | 0.5700  | 0.7245  | 0.3895  | 0.4926  |
+--------------+---------+---------+---------+---------+
2024-08-25 14:33:43,636 - mmdet - INFO - Epoch(val) [7][1685]	sofa_AP_0.25: 0.7676, chair_AP_0.25: 0.7202, table_AP_0.25: 0.6899, cabinet_AP_0.25: 0.5223, stool_AP_0.25: 0.2276, tv_monitor_AP_0.25: 0.0070, oven_AP_0.25: 0.6140, dishwasher_AP_0.25: 0.1607, shelf_AP_0.25: 0.4437, refrigerator_AP_0.25: 0.7623, fireplace_AP_0.25: 0.6493, bathtub_AP_0.25: 0.9487, toilet_AP_0.25: 0.9060, sink_AP_0.25: 0.4761, washer_AP_0.25: 0.7539, bed_AP_0.25: 0.8779, stove_AP_0.25: 0.1623, mAP_0.25: 0.5700, sofa_rec_0.25: 0.8504, chair_rec_0.25: 0.8662, table_rec_0.25: 0.8660, cabinet_rec_0.25: 0.6634, stool_rec_0.25: 0.6075, tv_monitor_rec_0.25: 0.0854, oven_rec_0.25: 0.7273, dishwasher_rec_0.25: 0.8800, shelf_rec_0.25: 0.6408, refrigerator_rec_0.25: 0.9512, fireplace_rec_0.25: 0.7222, bathtub_rec_0.25: 0.9490, toilet_rec_0.25: 0.9174, sink_rec_0.25: 0.5255, washer_rec_0.25: 0.8684, bed_rec_0.25: 0.9503, stove_rec_0.25: 0.2449, mAR_0.25: 0.7245, sofa_AP_0.50: 0.6272, chair_AP_0.50: 0.4167, table_AP_0.50: 0.3978, cabinet_AP_0.50: 0.2531, stool_AP_0.50: 0.1155, tv_monitor_AP_0.50: 0.0000, oven_AP_0.50: 0.3693, dishwasher_AP_0.50: 0.1393, shelf_AP_0.50: 0.1048, refrigerator_AP_0.50: 0.6814, fireplace_AP_0.50: 0.2093, bathtub_AP_0.50: 0.8751, toilet_AP_0.50: 0.7884, sink_AP_0.50: 0.1886, washer_AP_0.50: 0.6397, bed_AP_0.50: 0.8099, stove_AP_0.50: 0.0059, mAP_0.50: 0.3895, sofa_rec_0.50: 0.6877, chair_rec_0.50: 0.5463, table_rec_0.50: 0.5588, cabinet_rec_0.50: 0.3641, stool_rec_0.50: 0.3065, tv_monitor_rec_0.50: 0.0000, oven_rec_0.50: 0.4740, dishwasher_rec_0.50: 0.6000, shelf_rec_0.50: 0.1942, refrigerator_rec_0.50: 0.8049, fireplace_rec_0.50: 0.2778, bathtub_rec_0.50: 0.8980, toilet_rec_0.50: 0.8182, sink_rec_0.50: 0.2325, washer_rec_0.50: 0.7193, bed_rec_0.50: 0.8619, stove_rec_0.50: 0.0306, mAR_0.50: 0.4926
2024-08-25 14:36:16,052 - mmdet - INFO - Epoch [8][50/1685]	lr: 1.000e-04, eta: 6:39:43, time: 3.048, data_time: 0.172, memory: 19416, loss_occ: 0.5266, acc_occ: 0.8793, loss_centerness: 0.6117, loss_bbox: 0.4157, loss_cls: 0.2355, loss: 1.7895, grad_norm: 3.4876
2024-08-25 14:38:37,450 - mmdet - INFO - Epoch [8][100/1685]	lr: 1.000e-04, eta: 6:37:18, time: 2.828, data_time: 0.015, memory: 19416, loss_occ: 0.5446, acc_occ: 0.8855, loss_centerness: 0.6105, loss_bbox: 0.4130, loss_cls: 0.2295, loss: 1.7976, grad_norm: 3.5317
2024-08-25 14:41:00,998 - mmdet - INFO - Epoch [8][150/1685]	lr: 1.000e-04, eta: 6:34:55, time: 2.871, data_time: 0.015, memory: 19416, loss_occ: 0.5454, acc_occ: 0.8795, loss_centerness: 0.6040, loss_bbox: 0.4079, loss_cls: 0.2310, loss: 1.7882, grad_norm: 3.9694
2024-08-25 14:43:22,301 - mmdet - INFO - Epoch [8][200/1685]	lr: 1.000e-04, eta: 6:32:31, time: 2.826, data_time: 0.011, memory: 19416, loss_occ: 0.5357, acc_occ: 0.8804, loss_centerness: 0.6120, loss_bbox: 0.4180, loss_cls: 0.2380, loss: 1.8037, grad_norm: 3.8889
2024-08-25 14:45:50,931 - mmdet - INFO - Epoch [8][250/1685]	lr: 1.000e-04, eta: 6:30:12, time: 2.973, data_time: 0.012, memory: 19416, loss_occ: 0.5441, acc_occ: 0.8802, loss_centerness: 0.6076, loss_bbox: 0.4112, loss_cls: 0.2434, loss: 1.8062, grad_norm: 3.9379
2024-08-25 14:48:13,443 - mmdet - INFO - Epoch [8][300/1685]	lr: 1.000e-04, eta: 6:27:48, time: 2.850, data_time: 0.011, memory: 19416, loss_occ: 0.5401, acc_occ: 0.8790, loss_centerness: 0.6141, loss_bbox: 0.4215, loss_cls: 0.2460, loss: 1.8216, grad_norm: 3.5379
2024-08-25 14:50:37,682 - mmdet - INFO - Epoch [8][350/1685]	lr: 1.000e-04, eta: 6:25:25, time: 2.885, data_time: 0.011, memory: 19416, loss_occ: 0.5309, acc_occ: 0.8824, loss_centerness: 0.6061, loss_bbox: 0.4111, loss_cls: 0.2361, loss: 1.7842, grad_norm: 3.9229
2024-08-25 14:53:02,627 - mmdet - INFO - Epoch [8][400/1685]	lr: 1.000e-04, eta: 6:23:03, time: 2.899, data_time: 0.014, memory: 19416, loss_occ: 0.5256, acc_occ: 0.8855, loss_centerness: 0.6078, loss_bbox: 0.4115, loss_cls: 0.2305, loss: 1.7755, grad_norm: 3.6652
2024-08-25 14:55:28,553 - mmdet - INFO - Epoch [8][450/1685]	lr: 1.000e-04, eta: 6:20:42, time: 2.919, data_time: 0.014, memory: 19416, loss_occ: 0.5359, acc_occ: 0.8815, loss_centerness: 0.6133, loss_bbox: 0.4106, loss_cls: 0.2298, loss: 1.7896, grad_norm: 3.6065
2024-08-25 14:57:52,489 - mmdet - INFO - Epoch [8][500/1685]	lr: 1.000e-04, eta: 6:18:19, time: 2.879, data_time: 0.015, memory: 19416, loss_occ: 0.5194, acc_occ: 0.8814, loss_centerness: 0.6136, loss_bbox: 0.4137, loss_cls: 0.2381, loss: 1.7847, grad_norm: 3.4038
2024-08-25 15:00:15,286 - mmdet - INFO - Epoch [8][550/1685]	lr: 1.000e-04, eta: 6:15:56, time: 2.856, data_time: 0.014, memory: 19416, loss_occ: 0.5096, acc_occ: 0.8841, loss_centerness: 0.6098, loss_bbox: 0.4098, loss_cls: 0.2310, loss: 1.7601, grad_norm: 3.6976
2024-08-25 15:02:38,228 - mmdet - INFO - Epoch [8][600/1685]	lr: 1.000e-04, eta: 6:13:32, time: 2.859, data_time: 0.015, memory: 19416, loss_occ: 0.5302, acc_occ: 0.8861, loss_centerness: 0.6127, loss_bbox: 0.4154, loss_cls: 0.2272, loss: 1.7856, grad_norm: 3.8247
2024-08-25 15:05:04,942 - mmdet - INFO - Epoch [8][650/1685]	lr: 1.000e-04, eta: 6:11:11, time: 2.934, data_time: 0.014, memory: 19416, loss_occ: 0.5291, acc_occ: 0.8865, loss_centerness: 0.6087, loss_bbox: 0.4034, loss_cls: 0.2228, loss: 1.7640, grad_norm: 3.5240
2024-08-25 15:07:29,982 - mmdet - INFO - Epoch [8][700/1685]	lr: 1.000e-04, eta: 6:08:49, time: 2.901, data_time: 0.014, memory: 19416, loss_occ: 0.5384, acc_occ: 0.8844, loss_centerness: 0.6105, loss_bbox: 0.4096, loss_cls: 0.2279, loss: 1.7864, grad_norm: 3.4331
2024-08-25 15:09:54,670 - mmdet - INFO - Epoch [8][750/1685]	lr: 1.000e-04, eta: 6:06:27, time: 2.894, data_time: 0.014, memory: 19416, loss_occ: 0.5343, acc_occ: 0.8845, loss_centerness: 0.6128, loss_bbox: 0.4123, loss_cls: 0.2319, loss: 1.7915, grad_norm: 3.7248
2024-08-25 15:12:17,973 - mmdet - INFO - Epoch [8][800/1685]	lr: 1.000e-04, eta: 6:04:04, time: 2.866, data_time: 0.020, memory: 19416, loss_occ: 0.5256, acc_occ: 0.8780, loss_centerness: 0.6148, loss_bbox: 0.4201, loss_cls: 0.2402, loss: 1.8008, grad_norm: 3.6209
2024-08-25 15:14:41,604 - mmdet - INFO - Epoch [8][850/1685]	lr: 1.000e-04, eta: 6:01:41, time: 2.873, data_time: 0.014, memory: 19416, loss_occ: 0.5328, acc_occ: 0.8862, loss_centerness: 0.6124, loss_bbox: 0.4090, loss_cls: 0.2312, loss: 1.7854, grad_norm: 3.4882
2024-08-25 15:17:04,744 - mmdet - INFO - Epoch [8][900/1685]	lr: 1.000e-04, eta: 5:59:17, time: 2.863, data_time: 0.014, memory: 19416, loss_occ: 0.5340, acc_occ: 0.8863, loss_centerness: 0.6050, loss_bbox: 0.3991, loss_cls: 0.2182, loss: 1.7562, grad_norm: 3.5859
2024-08-25 15:19:30,924 - mmdet - INFO - Epoch [8][950/1685]	lr: 1.000e-04, eta: 5:56:56, time: 2.924, data_time: 0.014, memory: 19416, loss_occ: 0.5391, acc_occ: 0.8818, loss_centerness: 0.6131, loss_bbox: 0.4161, loss_cls: 0.2284, loss: 1.7965, grad_norm: 3.6630
2024-08-25 15:21:55,506 - mmdet - INFO - Epoch [8][1000/1685]	lr: 1.000e-04, eta: 5:54:33, time: 2.892, data_time: 0.016, memory: 19416, loss_occ: 0.5499, acc_occ: 0.8868, loss_centerness: 0.6055, loss_bbox: 0.4124, loss_cls: 0.2280, loss: 1.7958, grad_norm: 3.6969
2024-08-25 15:24:23,007 - mmdet - INFO - Epoch [8][1050/1685]	lr: 1.000e-04, eta: 5:52:12, time: 2.950, data_time: 0.013, memory: 19416, loss_occ: 0.5514, acc_occ: 0.8843, loss_centerness: 0.6130, loss_bbox: 0.4114, loss_cls: 0.2265, loss: 1.8023, grad_norm: 3.6475
2024-08-25 15:26:48,366 - mmdet - INFO - Epoch [8][1100/1685]	lr: 1.000e-04, eta: 5:49:50, time: 2.907, data_time: 0.017, memory: 19416, loss_occ: 0.5270, acc_occ: 0.8857, loss_centerness: 0.6080, loss_bbox: 0.4036, loss_cls: 0.2276, loss: 1.7662, grad_norm: 3.8101
2024-08-25 15:29:08,962 - mmdet - INFO - Epoch [8][1150/1685]	lr: 1.000e-04, eta: 5:47:26, time: 2.812, data_time: 0.014, memory: 19416, loss_occ: 0.5302, acc_occ: 0.8814, loss_centerness: 0.6122, loss_bbox: 0.4115, loss_cls: 0.2337, loss: 1.7876, grad_norm: 3.7487
2024-08-25 15:31:28,759 - mmdet - INFO - Epoch [8][1200/1685]	lr: 1.000e-04, eta: 5:45:00, time: 2.796, data_time: 0.015, memory: 19416, loss_occ: 0.5175, acc_occ: 0.8827, loss_centerness: 0.6091, loss_bbox: 0.4121, loss_cls: 0.2303, loss: 1.7690, grad_norm: 3.8045
2024-08-25 15:33:47,709 - mmdet - INFO - Epoch [8][1250/1685]	lr: 1.000e-04, eta: 5:42:35, time: 2.779, data_time: 0.014, memory: 19416, loss_occ: 0.5266, acc_occ: 0.8848, loss_centerness: 0.6094, loss_bbox: 0.4115, loss_cls: 0.2302, loss: 1.7777, grad_norm: 3.7271
2024-08-25 15:36:08,105 - mmdet - INFO - Epoch [8][1300/1685]	lr: 1.000e-04, eta: 5:40:10, time: 2.808, data_time: 0.013, memory: 19416, loss_occ: 0.5237, acc_occ: 0.8847, loss_centerness: 0.6091, loss_bbox: 0.4083, loss_cls: 0.2265, loss: 1.7675, grad_norm: 3.9505
2024-08-25 15:38:29,170 - mmdet - INFO - Epoch [8][1350/1685]	lr: 1.000e-04, eta: 5:37:46, time: 2.821, data_time: 0.012, memory: 19416, loss_occ: 0.5261, acc_occ: 0.8862, loss_centerness: 0.6095, loss_bbox: 0.3995, loss_cls: 0.2184, loss: 1.7535, grad_norm: 3.6799
2024-08-25 15:40:49,706 - mmdet - INFO - Epoch [8][1400/1685]	lr: 1.000e-04, eta: 5:35:21, time: 2.811, data_time: 0.011, memory: 19416, loss_occ: 0.5301, acc_occ: 0.8848, loss_centerness: 0.6143, loss_bbox: 0.4100, loss_cls: 0.2231, loss: 1.7774, grad_norm: 3.8315
2024-08-25 15:43:08,319 - mmdet - INFO - Epoch [8][1450/1685]	lr: 1.000e-04, eta: 5:32:55, time: 2.772, data_time: 0.010, memory: 19416, loss_occ: 0.5271, acc_occ: 0.8840, loss_centerness: 0.6137, loss_bbox: 0.4055, loss_cls: 0.2291, loss: 1.7754, grad_norm: 3.6950
2024-08-25 15:45:27,486 - mmdet - INFO - Epoch [8][1500/1685]	lr: 1.000e-04, eta: 5:30:30, time: 2.783, data_time: 0.011, memory: 19416, loss_occ: 0.5187, acc_occ: 0.8849, loss_centerness: 0.6142, loss_bbox: 0.4068, loss_cls: 0.2312, loss: 1.7709, grad_norm: 3.6711
2024-08-25 15:47:52,510 - mmdet - INFO - Epoch [8][1550/1685]	lr: 1.000e-04, eta: 5:28:08, time: 2.900, data_time: 0.015, memory: 19416, loss_occ: 0.5274, acc_occ: 0.8833, loss_centerness: 0.6072, loss_bbox: 0.4066, loss_cls: 0.2254, loss: 1.7667, grad_norm: 3.5885
2024-08-25 15:50:17,988 - mmdet - INFO - Epoch [8][1600/1685]	lr: 1.000e-04, eta: 5:25:46, time: 2.910, data_time: 0.016, memory: 19416, loss_occ: 0.5399, acc_occ: 0.8863, loss_centerness: 0.6099, loss_bbox: 0.4046, loss_cls: 0.2199, loss: 1.7743, grad_norm: 3.6127
2024-08-25 15:52:42,994 - mmdet - INFO - Epoch [8][1650/1685]	lr: 1.000e-04, eta: 5:23:23, time: 2.900, data_time: 0.013, memory: 19416, loss_occ: 0.5442, acc_occ: 0.8856, loss_centerness: 0.6067, loss_bbox: 0.3946, loss_cls: 0.2317, loss: 1.7772, grad_norm: 3.8732
2024-08-25 15:54:23,548 - mmdet - INFO - Saving checkpoint at 8 epochs
2024-08-25 15:56:32,783 - mmdet - INFO - 
+--------------+---------+---------+---------+---------+
| classes      | AP_0.25 | AR_0.25 | AP_0.50 | AR_0.50 |
+--------------+---------+---------+---------+---------+
| sofa         | 0.7574  | 0.8530  | 0.6059  | 0.6719  |
| chair        | 0.7031  | 0.8450  | 0.4356  | 0.5675  |
| table        | 0.6911  | 0.8758  | 0.3943  | 0.5458  |
| cabinet      | 0.5499  | 0.6687  | 0.2927  | 0.3969  |
| stool        | 0.2269  | 0.6183  | 0.0970  | 0.3011  |
| refrigerator | 0.8312  | 0.9756  | 0.7490  | 0.8049  |
| tv_monitor   | 0.0236  | 0.1459  | 0.0001  | 0.0071  |
| fireplace    | 0.5237  | 0.7222  | 0.1138  | 0.2407  |
| oven         | 0.6397  | 0.7532  | 0.4279  | 0.5065  |
| shelf        | 0.4051  | 0.6311  | 0.1306  | 0.2330  |
| dishwasher   | 0.1579  | 0.8800  | 0.1165  | 0.5600  |
| washer       | 0.7656  | 0.8684  | 0.6811  | 0.7456  |
| bed          | 0.8617  | 0.9392  | 0.7931  | 0.8453  |
| bathtub      | 0.9482  | 0.9490  | 0.9161  | 0.9184  |
| sink         | 0.5196  | 0.5924  | 0.0994  | 0.1943  |
| toilet       | 0.9099  | 0.9339  | 0.7751  | 0.7934  |
| stove        | 0.2223  | 0.2959  | 0.0111  | 0.0510  |
+--------------+---------+---------+---------+---------+
| Overall      | 0.5728  | 0.7381  | 0.3905  | 0.4931  |
+--------------+---------+---------+---------+---------+
2024-08-25 15:56:33,264 - mmdet - INFO - Epoch(val) [8][1685]	sofa_AP_0.25: 0.7574, chair_AP_0.25: 0.7031, table_AP_0.25: 0.6911, cabinet_AP_0.25: 0.5499, stool_AP_0.25: 0.2269, refrigerator_AP_0.25: 0.8312, tv_monitor_AP_0.25: 0.0236, fireplace_AP_0.25: 0.5237, oven_AP_0.25: 0.6397, shelf_AP_0.25: 0.4051, dishwasher_AP_0.25: 0.1579, washer_AP_0.25: 0.7656, bed_AP_0.25: 0.8617, bathtub_AP_0.25: 0.9482, sink_AP_0.25: 0.5196, toilet_AP_0.25: 0.9099, stove_AP_0.25: 0.2223, mAP_0.25: 0.5728, sofa_rec_0.25: 0.8530, chair_rec_0.25: 0.8450, table_rec_0.25: 0.8758, cabinet_rec_0.25: 0.6687, stool_rec_0.25: 0.6183, refrigerator_rec_0.25: 0.9756, tv_monitor_rec_0.25: 0.1459, fireplace_rec_0.25: 0.7222, oven_rec_0.25: 0.7532, shelf_rec_0.25: 0.6311, dishwasher_rec_0.25: 0.8800, washer_rec_0.25: 0.8684, bed_rec_0.25: 0.9392, bathtub_rec_0.25: 0.9490, sink_rec_0.25: 0.5924, toilet_rec_0.25: 0.9339, stove_rec_0.25: 0.2959, mAR_0.25: 0.7381, sofa_AP_0.50: 0.6059, chair_AP_0.50: 0.4356, table_AP_0.50: 0.3943, cabinet_AP_0.50: 0.2927, stool_AP_0.50: 0.0970, refrigerator_AP_0.50: 0.7490, tv_monitor_AP_0.50: 0.0001, fireplace_AP_0.50: 0.1138, oven_AP_0.50: 0.4279, shelf_AP_0.50: 0.1306, dishwasher_AP_0.50: 0.1165, washer_AP_0.50: 0.6811, bed_AP_0.50: 0.7931, bathtub_AP_0.50: 0.9161, sink_AP_0.50: 0.0994, toilet_AP_0.50: 0.7751, stove_AP_0.50: 0.0111, mAP_0.50: 0.3905, sofa_rec_0.50: 0.6719, chair_rec_0.50: 0.5675, table_rec_0.50: 0.5458, cabinet_rec_0.50: 0.3969, stool_rec_0.50: 0.3011, refrigerator_rec_0.50: 0.8049, tv_monitor_rec_0.50: 0.0071, fireplace_rec_0.50: 0.2407, oven_rec_0.50: 0.5065, shelf_rec_0.50: 0.2330, dishwasher_rec_0.50: 0.5600, washer_rec_0.50: 0.7456, bed_rec_0.50: 0.8453, bathtub_rec_0.50: 0.9184, sink_rec_0.50: 0.1943, toilet_rec_0.50: 0.7934, stove_rec_0.50: 0.0510, mAR_0.50: 0.4931
2024-08-25 15:59:07,420 - mmdet - INFO - Epoch [9][50/1685]	lr: 1.000e-05, eta: 5:18:36, time: 3.083, data_time: 0.146, memory: 19416, loss_occ: 0.5387, acc_occ: 0.8847, loss_centerness: 0.6119, loss_bbox: 0.3974, loss_cls: 0.2266, loss: 1.7746, grad_norm: 3.4438
2024-08-25 16:01:37,056 - mmdet - INFO - Epoch [9][100/1685]	lr: 1.000e-05, eta: 5:16:16, time: 2.993, data_time: 0.011, memory: 19416, loss_occ: 0.5300, acc_occ: 0.8850, loss_centerness: 0.6133, loss_bbox: 0.3920, loss_cls: 0.2123, loss: 1.7477, grad_norm: 3.1716
2024-08-25 16:04:03,538 - mmdet - INFO - Epoch [9][150/1685]	lr: 1.000e-05, eta: 5:13:55, time: 2.930, data_time: 0.012, memory: 19416, loss_occ: 0.5202, acc_occ: 0.8846, loss_centerness: 0.6110, loss_bbox: 0.3885, loss_cls: 0.2128, loss: 1.7325, grad_norm: 3.1607
2024-08-25 16:06:32,409 - mmdet - INFO - Epoch [9][200/1685]	lr: 1.000e-05, eta: 5:11:35, time: 2.977, data_time: 0.010, memory: 19416, loss_occ: 0.5192, acc_occ: 0.8853, loss_centerness: 0.6079, loss_bbox: 0.3787, loss_cls: 0.2082, loss: 1.7140, grad_norm: 3.3002
2024-08-25 16:09:01,535 - mmdet - INFO - Epoch [9][250/1685]	lr: 1.000e-05, eta: 5:09:15, time: 2.982, data_time: 0.009, memory: 19416, loss_occ: 0.5169, acc_occ: 0.8877, loss_centerness: 0.6067, loss_bbox: 0.3776, loss_cls: 0.2062, loss: 1.7073, grad_norm: 3.3715
2024-08-25 16:11:29,490 - mmdet - INFO - Epoch [9][300/1685]	lr: 1.000e-05, eta: 5:06:54, time: 2.959, data_time: 0.010, memory: 19416, loss_occ: 0.5267, acc_occ: 0.8895, loss_centerness: 0.6095, loss_bbox: 0.3853, loss_cls: 0.2092, loss: 1.7306, grad_norm: 3.2199
2024-08-25 16:13:59,661 - mmdet - INFO - Epoch [9][350/1685]	lr: 1.000e-05, eta: 5:04:35, time: 3.003, data_time: 0.012, memory: 19416, loss_occ: 0.5319, acc_occ: 0.8820, loss_centerness: 0.6083, loss_bbox: 0.3839, loss_cls: 0.2145, loss: 1.7387, grad_norm: 3.3601
2024-08-25 16:16:28,301 - mmdet - INFO - Epoch [9][400/1685]	lr: 1.000e-05, eta: 5:02:14, time: 2.973, data_time: 0.010, memory: 19416, loss_occ: 0.5189, acc_occ: 0.8849, loss_centerness: 0.6112, loss_bbox: 0.3852, loss_cls: 0.2092, loss: 1.7245, grad_norm: 3.2349
2024-08-25 16:18:55,657 - mmdet - INFO - Epoch [9][450/1685]	lr: 1.000e-05, eta: 4:59:53, time: 2.947, data_time: 0.011, memory: 19416, loss_occ: 0.5293, acc_occ: 0.8920, loss_centerness: 0.6062, loss_bbox: 0.3796, loss_cls: 0.2014, loss: 1.7165, grad_norm: 3.2978
2024-08-25 16:21:26,039 - mmdet - INFO - Epoch [9][500/1685]	lr: 1.000e-05, eta: 4:57:34, time: 3.008, data_time: 0.012, memory: 19416, loss_occ: 0.5274, acc_occ: 0.8909, loss_centerness: 0.6050, loss_bbox: 0.3785, loss_cls: 0.2048, loss: 1.7157, grad_norm: 3.5043
2024-08-25 16:23:55,547 - mmdet - INFO - Epoch [9][550/1685]	lr: 1.000e-05, eta: 4:55:13, time: 2.990, data_time: 0.011, memory: 19416, loss_occ: 0.5280, acc_occ: 0.8827, loss_centerness: 0.6106, loss_bbox: 0.3815, loss_cls: 0.2109, loss: 1.7310, grad_norm: 3.2070
2024-08-25 16:26:21,965 - mmdet - INFO - Epoch [9][600/1685]	lr: 1.000e-05, eta: 4:52:52, time: 2.928, data_time: 0.013, memory: 19416, loss_occ: 0.5298, acc_occ: 0.8924, loss_centerness: 0.6106, loss_bbox: 0.3866, loss_cls: 0.2112, loss: 1.7381, grad_norm: 3.3293
2024-08-25 16:28:55,080 - mmdet - INFO - Epoch [9][650/1685]	lr: 1.000e-05, eta: 4:50:33, time: 3.062, data_time: 0.014, memory: 19416, loss_occ: 0.5306, acc_occ: 0.8894, loss_centerness: 0.6083, loss_bbox: 0.3830, loss_cls: 0.2074, loss: 1.7292, grad_norm: 3.2516
2024-08-25 16:31:23,274 - mmdet - INFO - Epoch [9][700/1685]	lr: 1.000e-05, eta: 4:48:12, time: 2.964, data_time: 0.014, memory: 19416, loss_occ: 0.5327, acc_occ: 0.8933, loss_centerness: 0.6034, loss_bbox: 0.3703, loss_cls: 0.1958, loss: 1.7022, grad_norm: 3.4398
2024-08-25 16:33:47,001 - mmdet - INFO - Epoch [9][750/1685]	lr: 1.000e-05, eta: 4:45:49, time: 2.875, data_time: 0.014, memory: 19416, loss_occ: 0.5214, acc_occ: 0.8926, loss_centerness: 0.6081, loss_bbox: 0.3740, loss_cls: 0.2039, loss: 1.7073, grad_norm: 3.3981
2024-08-25 16:36:17,789 - mmdet - INFO - Epoch [9][800/1685]	lr: 1.000e-05, eta: 4:43:29, time: 3.016, data_time: 0.014, memory: 19416, loss_occ: 0.5234, acc_occ: 0.8938, loss_centerness: 0.6054, loss_bbox: 0.3745, loss_cls: 0.1935, loss: 1.6968, grad_norm: 3.2278
2024-08-25 16:38:45,215 - mmdet - INFO - Epoch [9][850/1685]	lr: 1.000e-05, eta: 4:41:08, time: 2.949, data_time: 0.013, memory: 19416, loss_occ: 0.5345, acc_occ: 0.8900, loss_centerness: 0.6096, loss_bbox: 0.3772, loss_cls: 0.2021, loss: 1.7234, grad_norm: 3.4557
2024-08-25 16:41:12,516 - mmdet - INFO - Epoch [9][900/1685]	lr: 1.000e-05, eta: 4:38:46, time: 2.946, data_time: 0.014, memory: 19416, loss_occ: 0.5297, acc_occ: 0.8893, loss_centerness: 0.6083, loss_bbox: 0.3770, loss_cls: 0.1989, loss: 1.7139, grad_norm: 3.3454
2024-08-25 16:43:40,994 - mmdet - INFO - Epoch [9][950/1685]	lr: 1.000e-05, eta: 4:36:25, time: 2.970, data_time: 0.016, memory: 19416, loss_occ: 0.5293, acc_occ: 0.8887, loss_centerness: 0.6074, loss_bbox: 0.3692, loss_cls: 0.1963, loss: 1.7022, grad_norm: 3.2302
2024-08-25 16:46:08,121 - mmdet - INFO - Epoch [9][1000/1685]	lr: 1.000e-05, eta: 4:34:03, time: 2.943, data_time: 0.013, memory: 19416, loss_occ: 0.5124, acc_occ: 0.8900, loss_centerness: 0.6042, loss_bbox: 0.3744, loss_cls: 0.1997, loss: 1.6907, grad_norm: 3.3107
2024-08-25 16:48:33,221 - mmdet - INFO - Epoch [9][1050/1685]	lr: 1.000e-05, eta: 4:31:41, time: 2.902, data_time: 0.015, memory: 19416, loss_occ: 0.5235, acc_occ: 0.8899, loss_centerness: 0.6059, loss_bbox: 0.3699, loss_cls: 0.1954, loss: 1.6946, grad_norm: 3.2114
2024-08-25 16:51:00,847 - mmdet - INFO - Epoch [9][1100/1685]	lr: 1.000e-05, eta: 4:29:19, time: 2.953, data_time: 0.015, memory: 19416, loss_occ: 0.5150, acc_occ: 0.8924, loss_centerness: 0.6081, loss_bbox: 0.3760, loss_cls: 0.1996, loss: 1.6987, grad_norm: 3.2953
2024-08-25 16:53:27,126 - mmdet - INFO - Epoch [9][1150/1685]	lr: 1.000e-05, eta: 4:26:57, time: 2.925, data_time: 0.020, memory: 19416, loss_occ: 0.5117, acc_occ: 0.8960, loss_centerness: 0.6056, loss_bbox: 0.3693, loss_cls: 0.1998, loss: 1.6864, grad_norm: 3.3264
2024-08-25 16:55:55,628 - mmdet - INFO - Epoch [9][1200/1685]	lr: 1.000e-05, eta: 4:24:36, time: 2.970, data_time: 0.015, memory: 19416, loss_occ: 0.5220, acc_occ: 0.8882, loss_centerness: 0.6100, loss_bbox: 0.3774, loss_cls: 0.2059, loss: 1.7153, grad_norm: 3.4599
2024-08-25 16:58:24,745 - mmdet - INFO - Epoch [9][1250/1685]	lr: 1.000e-05, eta: 4:22:15, time: 2.982, data_time: 0.014, memory: 19416, loss_occ: 0.5259, acc_occ: 0.8925, loss_centerness: 0.6053, loss_bbox: 0.3796, loss_cls: 0.2003, loss: 1.7110, grad_norm: 3.2487
2024-08-25 17:00:52,735 - mmdet - INFO - Epoch [9][1300/1685]	lr: 1.000e-05, eta: 4:19:53, time: 2.960, data_time: 0.014, memory: 19416, loss_occ: 0.5332, acc_occ: 0.8942, loss_centerness: 0.6030, loss_bbox: 0.3716, loss_cls: 0.2009, loss: 1.7086, grad_norm: 3.3460
2024-08-25 17:03:24,981 - mmdet - INFO - Epoch [9][1350/1685]	lr: 1.000e-05, eta: 4:17:33, time: 3.045, data_time: 0.015, memory: 19416, loss_occ: 0.5218, acc_occ: 0.8910, loss_centerness: 0.6099, loss_bbox: 0.3771, loss_cls: 0.2009, loss: 1.7096, grad_norm: 3.2771
2024-08-25 17:05:54,439 - mmdet - INFO - Epoch [9][1400/1685]	lr: 1.000e-05, eta: 4:15:12, time: 2.989, data_time: 0.014, memory: 19416, loss_occ: 0.5198, acc_occ: 0.8872, loss_centerness: 0.6091, loss_bbox: 0.3713, loss_cls: 0.1972, loss: 1.6974, grad_norm: 3.3092
2024-08-25 17:08:24,194 - mmdet - INFO - Epoch [9][1450/1685]	lr: 1.000e-05, eta: 4:12:51, time: 2.995, data_time: 0.014, memory: 19416, loss_occ: 0.5134, acc_occ: 0.8942, loss_centerness: 0.6051, loss_bbox: 0.3701, loss_cls: 0.1945, loss: 1.6831, grad_norm: 3.4570
2024-08-25 17:10:53,219 - mmdet - INFO - Epoch [9][1500/1685]	lr: 1.000e-05, eta: 4:10:29, time: 2.980, data_time: 0.014, memory: 19416, loss_occ: 0.5120, acc_occ: 0.8895, loss_centerness: 0.6072, loss_bbox: 0.3771, loss_cls: 0.1974, loss: 1.6936, grad_norm: 3.2696
2024-08-25 17:13:21,825 - mmdet - INFO - Epoch [9][1550/1685]	lr: 1.000e-05, eta: 4:08:08, time: 2.972, data_time: 0.013, memory: 19416, loss_occ: 0.5502, acc_occ: 0.8897, loss_centerness: 0.6080, loss_bbox: 0.3689, loss_cls: 0.1958, loss: 1.7229, grad_norm: 3.3956
2024-08-25 17:15:49,333 - mmdet - INFO - Epoch [9][1600/1685]	lr: 1.000e-05, eta: 4:05:46, time: 2.950, data_time: 0.013, memory: 19416, loss_occ: 0.5219, acc_occ: 0.8928, loss_centerness: 0.6086, loss_bbox: 0.3713, loss_cls: 0.2004, loss: 1.7023, grad_norm: 3.5883
2024-08-25 17:18:13,098 - mmdet - INFO - Epoch [9][1650/1685]	lr: 1.000e-05, eta: 4:03:22, time: 2.875, data_time: 0.014, memory: 19416, loss_occ: 0.5247, acc_occ: 0.8941, loss_centerness: 0.6077, loss_bbox: 0.3670, loss_cls: 0.1906, loss: 1.6901, grad_norm: 3.4170
2024-08-25 17:19:51,651 - mmdet - INFO - Saving checkpoint at 9 epochs
2024-08-25 17:22:00,080 - mmdet - INFO - 
+--------------+---------+---------+---------+---------+
| classes      | AP_0.25 | AR_0.25 | AP_0.50 | AR_0.50 |
+--------------+---------+---------+---------+---------+
| sofa         | 0.7906  | 0.8766  | 0.6539  | 0.7034  |
| table        | 0.6998  | 0.8856  | 0.4414  | 0.5915  |
| chair        | 0.7212  | 0.8413  | 0.4766  | 0.5800  |
| cabinet      | 0.5641  | 0.6727  | 0.3064  | 0.4022  |
| stool        | 0.2676  | 0.6720  | 0.1484  | 0.3925  |
| oven         | 0.6032  | 0.7078  | 0.4214  | 0.4870  |
| tv_monitor   | 0.0214  | 0.1495  | 0.0003  | 0.0142  |
| dishwasher   | 0.2096  | 0.8800  | 0.1627  | 0.6400  |
| refrigerator | 0.8258  | 0.9634  | 0.7697  | 0.8171  |
| shelf        | 0.4490  | 0.6893  | 0.1768  | 0.2816  |
| stove        | 0.1990  | 0.2551  | 0.0096  | 0.0510  |
| bathtub      | 0.9476  | 0.9694  | 0.9118  | 0.9184  |
| fireplace    | 0.6431  | 0.7778  | 0.2812  | 0.4259  |
| washer       | 0.7855  | 0.8860  | 0.7025  | 0.7807  |
| sink         | 0.5470  | 0.6115  | 0.1894  | 0.2707  |
| bed          | 0.8767  | 0.9448  | 0.8026  | 0.8508  |
| toilet       | 0.9095  | 0.9174  | 0.8248  | 0.8347  |
+--------------+---------+---------+---------+---------+
| Overall      | 0.5918  | 0.7471  | 0.4282  | 0.5319  |
+--------------+---------+---------+---------+---------+
2024-08-25 17:22:00,596 - mmdet - INFO - Epoch(val) [9][1685]	sofa_AP_0.25: 0.7906, table_AP_0.25: 0.6998, chair_AP_0.25: 0.7212, cabinet_AP_0.25: 0.5641, stool_AP_0.25: 0.2676, oven_AP_0.25: 0.6032, tv_monitor_AP_0.25: 0.0214, dishwasher_AP_0.25: 0.2096, refrigerator_AP_0.25: 0.8258, shelf_AP_0.25: 0.4490, stove_AP_0.25: 0.1990, bathtub_AP_0.25: 0.9476, fireplace_AP_0.25: 0.6431, washer_AP_0.25: 0.7855, sink_AP_0.25: 0.5470, bed_AP_0.25: 0.8767, toilet_AP_0.25: 0.9095, mAP_0.25: 0.5918, sofa_rec_0.25: 0.8766, table_rec_0.25: 0.8856, chair_rec_0.25: 0.8413, cabinet_rec_0.25: 0.6727, stool_rec_0.25: 0.6720, oven_rec_0.25: 0.7078, tv_monitor_rec_0.25: 0.1495, dishwasher_rec_0.25: 0.8800, refrigerator_rec_0.25: 0.9634, shelf_rec_0.25: 0.6893, stove_rec_0.25: 0.2551, bathtub_rec_0.25: 0.9694, fireplace_rec_0.25: 0.7778, washer_rec_0.25: 0.8860, sink_rec_0.25: 0.6115, bed_rec_0.25: 0.9448, toilet_rec_0.25: 0.9174, mAR_0.25: 0.7471, sofa_AP_0.50: 0.6539, table_AP_0.50: 0.4414, chair_AP_0.50: 0.4766, cabinet_AP_0.50: 0.3064, stool_AP_0.50: 0.1484, oven_AP_0.50: 0.4214, tv_monitor_AP_0.50: 0.0003, dishwasher_AP_0.50: 0.1627, refrigerator_AP_0.50: 0.7697, shelf_AP_0.50: 0.1768, stove_AP_0.50: 0.0096, bathtub_AP_0.50: 0.9118, fireplace_AP_0.50: 0.2812, washer_AP_0.50: 0.7025, sink_AP_0.50: 0.1894, bed_AP_0.50: 0.8026, toilet_AP_0.50: 0.8248, mAP_0.50: 0.4282, sofa_rec_0.50: 0.7034, table_rec_0.50: 0.5915, chair_rec_0.50: 0.5800, cabinet_rec_0.50: 0.4022, stool_rec_0.50: 0.3925, oven_rec_0.50: 0.4870, tv_monitor_rec_0.50: 0.0142, dishwasher_rec_0.50: 0.6400, refrigerator_rec_0.50: 0.8171, shelf_rec_0.50: 0.2816, stove_rec_0.50: 0.0510, bathtub_rec_0.50: 0.9184, fireplace_rec_0.50: 0.4259, washer_rec_0.50: 0.7807, sink_rec_0.50: 0.2707, bed_rec_0.50: 0.8508, toilet_rec_0.50: 0.8347, mAR_0.50: 0.5319
2024-08-25 17:24:27,856 - mmdet - INFO - Epoch [10][50/1685]	lr: 1.000e-05, eta: 3:58:47, time: 2.945, data_time: 0.119, memory: 19416, loss_occ: 0.5142, acc_occ: 0.8920, loss_centerness: 0.6064, loss_bbox: 0.3673, loss_cls: 0.2012, loss: 1.6892, grad_norm: 3.3928
2024-08-25 17:26:49,265 - mmdet - INFO - Epoch [10][100/1685]	lr: 1.000e-05, eta: 3:56:23, time: 2.828, data_time: 0.011, memory: 19416, loss_occ: 0.5128, acc_occ: 0.8885, loss_centerness: 0.6038, loss_bbox: 0.3616, loss_cls: 0.1974, loss: 1.6756, grad_norm: 3.4867
2024-08-25 17:29:10,003 - mmdet - INFO - Epoch [10][150/1685]	lr: 1.000e-05, eta: 3:53:59, time: 2.815, data_time: 0.012, memory: 19416, loss_occ: 0.5411, acc_occ: 0.8926, loss_centerness: 0.6042, loss_bbox: 0.3605, loss_cls: 0.1854, loss: 1.6913, grad_norm: 3.3696
2024-08-25 17:31:39,364 - mmdet - INFO - Epoch [10][200/1685]	lr: 1.000e-05, eta: 3:51:38, time: 2.987, data_time: 0.014, memory: 19416, loss_occ: 0.5312, acc_occ: 0.8895, loss_centerness: 0.6100, loss_bbox: 0.3737, loss_cls: 0.2013, loss: 1.7162, grad_norm: 3.3901
2024-08-25 17:33:59,981 - mmdet - INFO - Epoch [10][250/1685]	lr: 1.000e-05, eta: 3:49:14, time: 2.812, data_time: 0.013, memory: 19416, loss_occ: 0.5127, acc_occ: 0.8922, loss_centerness: 0.6057, loss_bbox: 0.3656, loss_cls: 0.1898, loss: 1.6739, grad_norm: 3.4068
2024-08-25 17:36:14,174 - mmdet - INFO - Epoch [10][300/1685]	lr: 1.000e-05, eta: 3:46:48, time: 2.684, data_time: 0.013, memory: 19416, loss_occ: 0.5225, acc_occ: 0.8887, loss_centerness: 0.6084, loss_bbox: 0.3781, loss_cls: 0.1967, loss: 1.7057, grad_norm: 3.1431
2024-08-25 17:38:28,988 - mmdet - INFO - Epoch [10][350/1685]	lr: 1.000e-05, eta: 3:44:23, time: 2.696, data_time: 0.014, memory: 19416, loss_occ: 0.5383, acc_occ: 0.8947, loss_centerness: 0.6005, loss_bbox: 0.3625, loss_cls: 0.1924, loss: 1.6937, grad_norm: 3.6279
2024-08-25 17:40:43,125 - mmdet - INFO - Epoch [10][400/1685]	lr: 1.000e-05, eta: 3:41:57, time: 2.683, data_time: 0.013, memory: 19416, loss_occ: 0.5148, acc_occ: 0.8903, loss_centerness: 0.6062, loss_bbox: 0.3732, loss_cls: 0.1986, loss: 1.6927, grad_norm: 3.2356
2024-08-25 17:42:56,548 - mmdet - INFO - Epoch [10][450/1685]	lr: 1.000e-05, eta: 3:39:31, time: 2.668, data_time: 0.012, memory: 19416, loss_occ: 0.5227, acc_occ: 0.8893, loss_centerness: 0.6046, loss_bbox: 0.3750, loss_cls: 0.1987, loss: 1.7010, grad_norm: 3.3968
2024-08-25 17:45:10,513 - mmdet - INFO - Epoch [10][500/1685]	lr: 1.000e-05, eta: 3:37:05, time: 2.679, data_time: 0.012, memory: 19416, loss_occ: 0.4998, acc_occ: 0.8935, loss_centerness: 0.6083, loss_bbox: 0.3720, loss_cls: 0.1967, loss: 1.6767, grad_norm: 3.4516
2024-08-25 17:47:23,817 - mmdet - INFO - Epoch [10][550/1685]	lr: 1.000e-05, eta: 3:34:40, time: 2.666, data_time: 0.011, memory: 19416, loss_occ: 0.5236, acc_occ: 0.8909, loss_centerness: 0.6032, loss_bbox: 0.3739, loss_cls: 0.1937, loss: 1.6945, grad_norm: 3.3339
2024-08-25 17:49:37,586 - mmdet - INFO - Epoch [10][600/1685]	lr: 1.000e-05, eta: 3:32:14, time: 2.675, data_time: 0.010, memory: 19416, loss_occ: 0.5198, acc_occ: 0.8919, loss_centerness: 0.6031, loss_bbox: 0.3702, loss_cls: 0.1928, loss: 1.6859, grad_norm: 3.4762
2024-08-25 17:51:51,152 - mmdet - INFO - Epoch [10][650/1685]	lr: 1.000e-05, eta: 3:29:48, time: 2.671, data_time: 0.010, memory: 19416, loss_occ: 0.5338, acc_occ: 0.8889, loss_centerness: 0.6118, loss_bbox: 0.3699, loss_cls: 0.1923, loss: 1.7078, grad_norm: 3.2608
2024-08-25 17:54:04,683 - mmdet - INFO - Epoch [10][700/1685]	lr: 1.000e-05, eta: 3:27:23, time: 2.671, data_time: 0.010, memory: 19416, loss_occ: 0.5309, acc_occ: 0.8911, loss_centerness: 0.6061, loss_bbox: 0.3753, loss_cls: 0.1972, loss: 1.7094, grad_norm: 3.3060
2024-08-25 17:56:17,644 - mmdet - INFO - Epoch [10][750/1685]	lr: 1.000e-05, eta: 3:24:57, time: 2.659, data_time: 0.009, memory: 19416, loss_occ: 0.5281, acc_occ: 0.8934, loss_centerness: 0.6109, loss_bbox: 0.3651, loss_cls: 0.1930, loss: 1.6971, grad_norm: 3.3760
2024-08-25 17:58:31,916 - mmdet - INFO - Epoch [10][800/1685]	lr: 1.000e-05, eta: 3:22:32, time: 2.685, data_time: 0.009, memory: 19416, loss_occ: 0.5171, acc_occ: 0.8903, loss_centerness: 0.6056, loss_bbox: 0.3692, loss_cls: 0.1912, loss: 1.6831, grad_norm: 3.4126
2024-08-25 18:00:47,230 - mmdet - INFO - Epoch [10][850/1685]	lr: 1.000e-05, eta: 3:20:08, time: 2.706, data_time: 0.009, memory: 19416, loss_occ: 0.5262, acc_occ: 0.8930, loss_centerness: 0.6098, loss_bbox: 0.3614, loss_cls: 0.1845, loss: 1.6819, grad_norm: 3.4189
2024-08-25 18:03:00,521 - mmdet - INFO - Epoch [10][900/1685]	lr: 1.000e-05, eta: 3:17:42, time: 2.666, data_time: 0.012, memory: 19416, loss_occ: 0.5119, acc_occ: 0.8948, loss_centerness: 0.6057, loss_bbox: 0.3804, loss_cls: 0.1981, loss: 1.6962, grad_norm: 3.4320
2024-08-25 18:05:13,934 - mmdet - INFO - Epoch [10][950/1685]	lr: 1.000e-05, eta: 3:15:17, time: 2.668, data_time: 0.013, memory: 19416, loss_occ: 0.5149, acc_occ: 0.8973, loss_centerness: 0.6067, loss_bbox: 0.3635, loss_cls: 0.1883, loss: 1.6735, grad_norm: 3.3767
2024-08-25 18:07:27,766 - mmdet - INFO - Epoch [10][1000/1685]	lr: 1.000e-05, eta: 3:12:52, time: 2.677, data_time: 0.013, memory: 19416, loss_occ: 0.5363, acc_occ: 0.8891, loss_centerness: 0.6072, loss_bbox: 0.3707, loss_cls: 0.1990, loss: 1.7132, grad_norm: 3.4198
2024-08-25 18:09:41,355 - mmdet - INFO - Epoch [10][1050/1685]	lr: 1.000e-05, eta: 3:10:27, time: 2.672, data_time: 0.013, memory: 19416, loss_occ: 0.5090, acc_occ: 0.8930, loss_centerness: 0.6032, loss_bbox: 0.3675, loss_cls: 0.1922, loss: 1.6719, grad_norm: 3.4211
2024-08-25 18:11:55,682 - mmdet - INFO - Epoch [10][1100/1685]	lr: 1.000e-05, eta: 3:08:03, time: 2.687, data_time: 0.014, memory: 19416, loss_occ: 0.5180, acc_occ: 0.8978, loss_centerness: 0.6105, loss_bbox: 0.3607, loss_cls: 0.1887, loss: 1.6779, grad_norm: 3.5078
2024-08-25 18:14:10,303 - mmdet - INFO - Epoch [10][1150/1685]	lr: 1.000e-05, eta: 3:05:38, time: 2.692, data_time: 0.013, memory: 19416, loss_occ: 0.5447, acc_occ: 0.8896, loss_centerness: 0.6075, loss_bbox: 0.3665, loss_cls: 0.1960, loss: 1.7146, grad_norm: 3.5229
2024-08-25 18:16:24,868 - mmdet - INFO - Epoch [10][1200/1685]	lr: 1.000e-05, eta: 3:03:14, time: 2.691, data_time: 0.013, memory: 19416, loss_occ: 0.5172, acc_occ: 0.8903, loss_centerness: 0.6061, loss_bbox: 0.3667, loss_cls: 0.1941, loss: 1.6841, grad_norm: 3.3316
2024-08-25 18:18:38,813 - mmdet - INFO - Epoch [10][1250/1685]	lr: 1.000e-05, eta: 3:00:49, time: 2.679, data_time: 0.013, memory: 19416, loss_occ: 0.5142, acc_occ: 0.8944, loss_centerness: 0.6049, loss_bbox: 0.3597, loss_cls: 0.1855, loss: 1.6643, grad_norm: 3.4000
2024-08-25 18:20:53,545 - mmdet - INFO - Epoch [10][1300/1685]	lr: 1.000e-05, eta: 2:58:25, time: 2.695, data_time: 0.013, memory: 19416, loss_occ: 0.5236, acc_occ: 0.8913, loss_centerness: 0.6048, loss_bbox: 0.3723, loss_cls: 0.1945, loss: 1.6952, grad_norm: 3.3927
2024-08-25 18:23:07,996 - mmdet - INFO - Epoch [10][1350/1685]	lr: 1.000e-05, eta: 2:56:00, time: 2.689, data_time: 0.014, memory: 19416, loss_occ: 0.5271, acc_occ: 0.8915, loss_centerness: 0.6050, loss_bbox: 0.3579, loss_cls: 0.1891, loss: 1.6791, grad_norm: 3.6836
2024-08-25 18:25:22,286 - mmdet - INFO - Epoch [10][1400/1685]	lr: 1.000e-05, eta: 2:53:36, time: 2.686, data_time: 0.013, memory: 19416, loss_occ: 0.5323, acc_occ: 0.8848, loss_centerness: 0.6098, loss_bbox: 0.3664, loss_cls: 0.1944, loss: 1.7029, grad_norm: 3.3728
2024-08-25 18:27:35,949 - mmdet - INFO - Epoch [10][1450/1685]	lr: 1.000e-05, eta: 2:51:11, time: 2.673, data_time: 0.012, memory: 19416, loss_occ: 0.5098, acc_occ: 0.8941, loss_centerness: 0.6058, loss_bbox: 0.3596, loss_cls: 0.1811, loss: 1.6562, grad_norm: 3.4654
2024-08-25 18:29:49,091 - mmdet - INFO - Epoch [10][1500/1685]	lr: 1.000e-05, eta: 2:48:47, time: 2.663, data_time: 0.012, memory: 19416, loss_occ: 0.5312, acc_occ: 0.8895, loss_centerness: 0.6075, loss_bbox: 0.3720, loss_cls: 0.1981, loss: 1.7088, grad_norm: 3.4793
2024-08-25 18:32:02,275 - mmdet - INFO - Epoch [10][1550/1685]	lr: 1.000e-05, eta: 2:46:23, time: 2.664, data_time: 0.012, memory: 19416, loss_occ: 0.5127, acc_occ: 0.8904, loss_centerness: 0.6076, loss_bbox: 0.3761, loss_cls: 0.1956, loss: 1.6921, grad_norm: 3.3681
2024-08-25 18:34:14,980 - mmdet - INFO - Epoch [10][1600/1685]	lr: 1.000e-05, eta: 2:43:58, time: 2.654, data_time: 0.012, memory: 19416, loss_occ: 0.5086, acc_occ: 0.8909, loss_centerness: 0.6027, loss_bbox: 0.3699, loss_cls: 0.1918, loss: 1.6730, grad_norm: 3.4440
2024-08-25 18:36:27,991 - mmdet - INFO - Epoch [10][1650/1685]	lr: 1.000e-05, eta: 2:41:34, time: 2.660, data_time: 0.012, memory: 19416, loss_occ: 0.5365, acc_occ: 0.8887, loss_centerness: 0.6086, loss_bbox: 0.3692, loss_cls: 0.1961, loss: 1.7104, grad_norm: 3.4030
2024-08-25 18:38:00,798 - mmdet - INFO - Saving checkpoint at 10 epochs
2024-08-25 18:40:13,773 - mmdet - INFO - 
+--------------+---------+---------+---------+---------+
| classes      | AP_0.25 | AR_0.25 | AP_0.50 | AR_0.50 |
+--------------+---------+---------+---------+---------+
| sofa         | 0.7911  | 0.8661  | 0.6564  | 0.7087  |
| table        | 0.7018  | 0.8824  | 0.4350  | 0.5817  |
| chair        | 0.7288  | 0.8425  | 0.4843  | 0.5837  |
| cabinet      | 0.5573  | 0.6687  | 0.3089  | 0.4044  |
| stool        | 0.2722  | 0.6774  | 0.1599  | 0.3871  |
| tv_monitor   | 0.0215  | 0.1744  | 0.0001  | 0.0071  |
| oven         | 0.6304  | 0.7468  | 0.4373  | 0.5195  |
| refrigerator | 0.8269  | 0.9634  | 0.7642  | 0.8171  |
| bathtub      | 0.9476  | 0.9796  | 0.8972  | 0.9082  |
| dishwasher   | 0.1905  | 0.8800  | 0.1332  | 0.6400  |
| shelf        | 0.4546  | 0.6893  | 0.1809  | 0.2864  |
| stove        | 0.2135  | 0.2653  | 0.0160  | 0.0714  |
| fireplace    | 0.6477  | 0.7963  | 0.1936  | 0.3333  |
| washer       | 0.7887  | 0.8860  | 0.7126  | 0.7719  |
| sink         | 0.5467  | 0.6115  | 0.2043  | 0.2739  |
| bed          | 0.8831  | 0.9448  | 0.8204  | 0.8729  |
| toilet       | 0.9104  | 0.9174  | 0.8176  | 0.8264  |
+--------------+---------+---------+---------+---------+
| Overall      | 0.5948  | 0.7525  | 0.4248  | 0.5290  |
+--------------+---------+---------+---------+---------+
2024-08-25 18:40:14,224 - mmdet - INFO - Epoch(val) [10][1685]	sofa_AP_0.25: 0.7911, table_AP_0.25: 0.7018, chair_AP_0.25: 0.7288, cabinet_AP_0.25: 0.5573, stool_AP_0.25: 0.2722, tv_monitor_AP_0.25: 0.0215, oven_AP_0.25: 0.6304, refrigerator_AP_0.25: 0.8269, bathtub_AP_0.25: 0.9476, dishwasher_AP_0.25: 0.1905, shelf_AP_0.25: 0.4546, stove_AP_0.25: 0.2135, fireplace_AP_0.25: 0.6477, washer_AP_0.25: 0.7887, sink_AP_0.25: 0.5467, bed_AP_0.25: 0.8831, toilet_AP_0.25: 0.9104, mAP_0.25: 0.5948, sofa_rec_0.25: 0.8661, table_rec_0.25: 0.8824, chair_rec_0.25: 0.8425, cabinet_rec_0.25: 0.6687, stool_rec_0.25: 0.6774, tv_monitor_rec_0.25: 0.1744, oven_rec_0.25: 0.7468, refrigerator_rec_0.25: 0.9634, bathtub_rec_0.25: 0.9796, dishwasher_rec_0.25: 0.8800, shelf_rec_0.25: 0.6893, stove_rec_0.25: 0.2653, fireplace_rec_0.25: 0.7963, washer_rec_0.25: 0.8860, sink_rec_0.25: 0.6115, bed_rec_0.25: 0.9448, toilet_rec_0.25: 0.9174, mAR_0.25: 0.7525, sofa_AP_0.50: 0.6564, table_AP_0.50: 0.4350, chair_AP_0.50: 0.4843, cabinet_AP_0.50: 0.3089, stool_AP_0.50: 0.1599, tv_monitor_AP_0.50: 0.0001, oven_AP_0.50: 0.4373, refrigerator_AP_0.50: 0.7642, bathtub_AP_0.50: 0.8972, dishwasher_AP_0.50: 0.1332, shelf_AP_0.50: 0.1809, stove_AP_0.50: 0.0160, fireplace_AP_0.50: 0.1936, washer_AP_0.50: 0.7126, sink_AP_0.50: 0.2043, bed_AP_0.50: 0.8204, toilet_AP_0.50: 0.8176, mAP_0.50: 0.4248, sofa_rec_0.50: 0.7087, table_rec_0.50: 0.5817, chair_rec_0.50: 0.5837, cabinet_rec_0.50: 0.4044, stool_rec_0.50: 0.3871, tv_monitor_rec_0.50: 0.0071, oven_rec_0.50: 0.5195, refrigerator_rec_0.50: 0.8171, bathtub_rec_0.50: 0.9082, dishwasher_rec_0.50: 0.6400, shelf_rec_0.50: 0.2864, stove_rec_0.50: 0.0714, fireplace_rec_0.50: 0.3333, washer_rec_0.50: 0.7719, sink_rec_0.50: 0.2739, bed_rec_0.50: 0.8729, toilet_rec_0.50: 0.8264, mAR_0.50: 0.5290
2024-08-25 18:42:37,556 - mmdet - INFO - Epoch [11][50/1685]	lr: 1.000e-05, eta: 2:37:13, time: 2.866, data_time: 0.224, memory: 19416, loss_occ: 0.5162, acc_occ: 0.8896, loss_centerness: 0.6061, loss_bbox: 0.3707, loss_cls: 0.1882, loss: 1.6812, grad_norm: 3.4836
2024-08-25 18:44:50,988 - mmdet - INFO - Epoch [11][100/1685]	lr: 1.000e-05, eta: 2:34:49, time: 2.669, data_time: 0.011, memory: 19416, loss_occ: 0.5363, acc_occ: 0.8916, loss_centerness: 0.6080, loss_bbox: 0.3668, loss_cls: 0.1902, loss: 1.7013, grad_norm: 3.3656
2024-08-25 18:47:04,575 - mmdet - INFO - Epoch [11][150/1685]	lr: 1.000e-05, eta: 2:32:25, time: 2.672, data_time: 0.011, memory: 19416, loss_occ: 0.5300, acc_occ: 0.8879, loss_centerness: 0.6054, loss_bbox: 0.3782, loss_cls: 0.1986, loss: 1.7123, grad_norm: 3.3013
2024-08-25 18:49:17,282 - mmdet - INFO - Epoch [11][200/1685]	lr: 1.000e-05, eta: 2:30:01, time: 2.654, data_time: 0.011, memory: 19416, loss_occ: 0.5065, acc_occ: 0.8946, loss_centerness: 0.6075, loss_bbox: 0.3610, loss_cls: 0.1856, loss: 1.6606, grad_norm: 3.3275
2024-08-25 18:51:30,630 - mmdet - INFO - Epoch [11][250/1685]	lr: 1.000e-05, eta: 2:27:38, time: 2.667, data_time: 0.012, memory: 19416, loss_occ: 0.5177, acc_occ: 0.8915, loss_centerness: 0.6086, loss_bbox: 0.3630, loss_cls: 0.1887, loss: 1.6781, grad_norm: 3.4725
2024-08-25 18:53:44,644 - mmdet - INFO - Epoch [11][300/1685]	lr: 1.000e-05, eta: 2:25:14, time: 2.680, data_time: 0.013, memory: 19416, loss_occ: 0.5206, acc_occ: 0.8892, loss_centerness: 0.6055, loss_bbox: 0.3688, loss_cls: 0.1983, loss: 1.6931, grad_norm: 3.5531
2024-08-25 18:55:58,750 - mmdet - INFO - Epoch [11][350/1685]	lr: 1.000e-05, eta: 2:22:51, time: 2.682, data_time: 0.015, memory: 19416, loss_occ: 0.5289, acc_occ: 0.8933, loss_centerness: 0.6083, loss_bbox: 0.3599, loss_cls: 0.1870, loss: 1.6840, grad_norm: 3.5693
2024-08-25 18:58:11,286 - mmdet - INFO - Epoch [11][400/1685]	lr: 1.000e-05, eta: 2:20:28, time: 2.651, data_time: 0.012, memory: 19416, loss_occ: 0.5227, acc_occ: 0.8926, loss_centerness: 0.6030, loss_bbox: 0.3615, loss_cls: 0.1862, loss: 1.6734, grad_norm: 3.5383
2024-08-25 19:00:25,592 - mmdet - INFO - Epoch [11][450/1685]	lr: 1.000e-05, eta: 2:18:04, time: 2.686, data_time: 0.012, memory: 19416, loss_occ: 0.5236, acc_occ: 0.8955, loss_centerness: 0.6074, loss_bbox: 0.3631, loss_cls: 0.1930, loss: 1.6872, grad_norm: 3.7164
2024-08-25 19:02:38,363 - mmdet - INFO - Epoch [11][500/1685]	lr: 1.000e-05, eta: 2:15:41, time: 2.655, data_time: 0.018, memory: 19416, loss_occ: 0.5082, acc_occ: 0.8966, loss_centerness: 0.6038, loss_bbox: 0.3604, loss_cls: 0.1891, loss: 1.6614, grad_norm: 3.4775
2024-08-25 19:04:50,497 - mmdet - INFO - Epoch [11][550/1685]	lr: 1.000e-05, eta: 2:13:18, time: 2.643, data_time: 0.013, memory: 19416, loss_occ: 0.5277, acc_occ: 0.8928, loss_centerness: 0.6032, loss_bbox: 0.3665, loss_cls: 0.1898, loss: 1.6871, grad_norm: 3.5476
2024-08-25 19:07:01,815 - mmdet - INFO - Epoch [11][600/1685]	lr: 1.000e-05, eta: 2:10:54, time: 2.626, data_time: 0.015, memory: 19416, loss_occ: 0.5095, acc_occ: 0.8938, loss_centerness: 0.6084, loss_bbox: 0.3627, loss_cls: 0.1841, loss: 1.6648, grad_norm: 3.3793
2024-08-25 19:09:13,800 - mmdet - INFO - Epoch [11][650/1685]	lr: 1.000e-05, eta: 2:08:31, time: 2.640, data_time: 0.010, memory: 19416, loss_occ: 0.5038, acc_occ: 0.8891, loss_centerness: 0.6072, loss_bbox: 0.3703, loss_cls: 0.2003, loss: 1.6816, grad_norm: 3.3735
2024-08-25 19:11:24,899 - mmdet - INFO - Epoch [11][700/1685]	lr: 1.000e-05, eta: 2:06:08, time: 2.622, data_time: 0.010, memory: 19416, loss_occ: 0.5299, acc_occ: 0.8876, loss_centerness: 0.6114, loss_bbox: 0.3689, loss_cls: 0.1923, loss: 1.7026, grad_norm: 3.4553
2024-08-25 19:13:36,200 - mmdet - INFO - Epoch [11][750/1685]	lr: 1.000e-05, eta: 2:03:44, time: 2.626, data_time: 0.010, memory: 19416, loss_occ: 0.5112, acc_occ: 0.8967, loss_centerness: 0.6074, loss_bbox: 0.3620, loss_cls: 0.1872, loss: 1.6678, grad_norm: 3.4776
2024-08-25 19:15:47,788 - mmdet - INFO - Epoch [11][800/1685]	lr: 1.000e-05, eta: 2:01:21, time: 2.632, data_time: 0.012, memory: 19416, loss_occ: 0.5366, acc_occ: 0.8959, loss_centerness: 0.6077, loss_bbox: 0.3656, loss_cls: 0.1897, loss: 1.6997, grad_norm: 3.4700
2024-08-25 19:18:00,489 - mmdet - INFO - Epoch [11][850/1685]	lr: 1.000e-05, eta: 1:58:58, time: 2.654, data_time: 0.014, memory: 19416, loss_occ: 0.5150, acc_occ: 0.8895, loss_centerness: 0.6049, loss_bbox: 0.3625, loss_cls: 0.1919, loss: 1.6743, grad_norm: 3.4798
2024-08-25 19:20:13,635 - mmdet - INFO - Epoch [11][900/1685]	lr: 1.000e-05, eta: 1:56:35, time: 2.663, data_time: 0.014, memory: 19416, loss_occ: 0.5160, acc_occ: 0.8960, loss_centerness: 0.6022, loss_bbox: 0.3620, loss_cls: 0.1888, loss: 1.6690, grad_norm: 3.4143
2024-08-25 19:22:27,615 - mmdet - INFO - Epoch [11][950/1685]	lr: 1.000e-05, eta: 1:54:13, time: 2.680, data_time: 0.013, memory: 19416, loss_occ: 0.5082, acc_occ: 0.8970, loss_centerness: 0.6064, loss_bbox: 0.3553, loss_cls: 0.1851, loss: 1.6550, grad_norm: 3.4794
2024-08-25 19:24:40,200 - mmdet - INFO - Epoch [11][1000/1685]	lr: 1.000e-05, eta: 1:51:50, time: 2.652, data_time: 0.012, memory: 19416, loss_occ: 0.5170, acc_occ: 0.8931, loss_centerness: 0.6006, loss_bbox: 0.3531, loss_cls: 0.1845, loss: 1.6551, grad_norm: 3.5551
2024-08-25 19:26:53,213 - mmdet - INFO - Epoch [11][1050/1685]	lr: 1.000e-05, eta: 1:49:27, time: 2.660, data_time: 0.011, memory: 19416, loss_occ: 0.5339, acc_occ: 0.8922, loss_centerness: 0.6086, loss_bbox: 0.3644, loss_cls: 0.1921, loss: 1.6990, grad_norm: 3.4025
2024-08-25 19:29:06,500 - mmdet - INFO - Epoch [11][1100/1685]	lr: 1.000e-05, eta: 1:47:05, time: 2.666, data_time: 0.010, memory: 19416, loss_occ: 0.5177, acc_occ: 0.8950, loss_centerness: 0.6078, loss_bbox: 0.3665, loss_cls: 0.1916, loss: 1.6836, grad_norm: 3.4948
2024-08-25 19:31:19,624 - mmdet - INFO - Epoch [11][1150/1685]	lr: 1.000e-05, eta: 1:44:42, time: 2.662, data_time: 0.010, memory: 19416, loss_occ: 0.5320, acc_occ: 0.8901, loss_centerness: 0.6076, loss_bbox: 0.3649, loss_cls: 0.1889, loss: 1.6934, grad_norm: 3.3793
2024-08-25 19:33:32,853 - mmdet - INFO - Epoch [11][1200/1685]	lr: 1.000e-05, eta: 1:42:20, time: 2.665, data_time: 0.011, memory: 19416, loss_occ: 0.5094, acc_occ: 0.8911, loss_centerness: 0.6078, loss_bbox: 0.3686, loss_cls: 0.1977, loss: 1.6835, grad_norm: 3.4905
2024-08-25 19:35:45,729 - mmdet - INFO - Epoch [11][1250/1685]	lr: 1.000e-05, eta: 1:39:57, time: 2.658, data_time: 0.013, memory: 19416, loss_occ: 0.5442, acc_occ: 0.8938, loss_centerness: 0.6053, loss_bbox: 0.3683, loss_cls: 0.1901, loss: 1.7079, grad_norm: 3.6599
2024-08-25 19:37:58,528 - mmdet - INFO - Epoch [11][1300/1685]	lr: 1.000e-05, eta: 1:37:35, time: 2.656, data_time: 0.014, memory: 19416, loss_occ: 0.5215, acc_occ: 0.8967, loss_centerness: 0.6030, loss_bbox: 0.3582, loss_cls: 0.1852, loss: 1.6679, grad_norm: 3.5097
2024-08-25 19:40:11,476 - mmdet - INFO - Epoch [11][1350/1685]	lr: 1.000e-05, eta: 1:35:12, time: 2.659, data_time: 0.014, memory: 19416, loss_occ: 0.5178, acc_occ: 0.8948, loss_centerness: 0.6045, loss_bbox: 0.3568, loss_cls: 0.1812, loss: 1.6603, grad_norm: 3.3807
2024-08-25 19:42:24,451 - mmdet - INFO - Epoch [11][1400/1685]	lr: 1.000e-05, eta: 1:32:50, time: 2.659, data_time: 0.013, memory: 19416, loss_occ: 0.5244, acc_occ: 0.8958, loss_centerness: 0.6003, loss_bbox: 0.3617, loss_cls: 0.1855, loss: 1.6719, grad_norm: 3.6829
2024-08-25 19:44:38,045 - mmdet - INFO - Epoch [11][1450/1685]	lr: 1.000e-05, eta: 1:30:28, time: 2.672, data_time: 0.013, memory: 19416, loss_occ: 0.5293, acc_occ: 0.8937, loss_centerness: 0.6081, loss_bbox: 0.3594, loss_cls: 0.1834, loss: 1.6802, grad_norm: 3.5663
2024-08-25 19:46:52,472 - mmdet - INFO - Epoch [11][1500/1685]	lr: 1.000e-05, eta: 1:28:06, time: 2.689, data_time: 0.012, memory: 19416, loss_occ: 0.5296, acc_occ: 0.8909, loss_centerness: 0.6044, loss_bbox: 0.3654, loss_cls: 0.1921, loss: 1.6914, grad_norm: 3.5271
2024-08-25 19:49:05,309 - mmdet - INFO - Epoch [11][1550/1685]	lr: 1.000e-05, eta: 1:25:44, time: 2.657, data_time: 0.013, memory: 19416, loss_occ: 0.5159, acc_occ: 0.8906, loss_centerness: 0.6048, loss_bbox: 0.3596, loss_cls: 0.1889, loss: 1.6692, grad_norm: 3.4148
2024-08-25 19:51:18,827 - mmdet - INFO - Epoch [11][1600/1685]	lr: 1.000e-05, eta: 1:23:21, time: 2.670, data_time: 0.013, memory: 19416, loss_occ: 0.5200, acc_occ: 0.8931, loss_centerness: 0.6109, loss_bbox: 0.3649, loss_cls: 0.1892, loss: 1.6849, grad_norm: 3.2959
2024-08-25 19:53:31,937 - mmdet - INFO - Epoch [11][1650/1685]	lr: 1.000e-05, eta: 1:20:59, time: 2.662, data_time: 0.013, memory: 19416, loss_occ: 0.5138, acc_occ: 0.8942, loss_centerness: 0.6032, loss_bbox: 0.3640, loss_cls: 0.1857, loss: 1.6668, grad_norm: 3.4827
2024-08-25 19:55:04,648 - mmdet - INFO - Saving checkpoint at 11 epochs
2024-08-25 19:57:09,746 - mmdet - INFO - 
+--------------+---------+---------+---------+---------+
| classes      | AP_0.25 | AR_0.25 | AP_0.50 | AR_0.50 |
+--------------+---------+---------+---------+---------+
| sofa         | 0.7932  | 0.8635  | 0.6532  | 0.7034  |
| table        | 0.6935  | 0.8742  | 0.4345  | 0.5866  |
| chair        | 0.7278  | 0.8525  | 0.4792  | 0.5863  |
| cabinet      | 0.5681  | 0.6785  | 0.3162  | 0.4124  |
| stool        | 0.2708  | 0.6774  | 0.1537  | 0.3710  |
| tv_monitor   | 0.0283  | 0.1779  | 0.0000  | 0.0071  |
| oven         | 0.6129  | 0.7273  | 0.4049  | 0.4870  |
| refrigerator | 0.8333  | 0.9634  | 0.7537  | 0.8049  |
| bathtub      | 0.9447  | 0.9694  | 0.9042  | 0.9184  |
| shelf        | 0.4613  | 0.6893  | 0.1714  | 0.2767  |
| dishwasher   | 0.1960  | 0.8800  | 0.1472  | 0.7200  |
| fireplace    | 0.6930  | 0.7778  | 0.2391  | 0.3704  |
| stove        | 0.2333  | 0.2857  | 0.0258  | 0.0816  |
| bed          | 0.8766  | 0.9392  | 0.8133  | 0.8619  |
| washer       | 0.7886  | 0.9035  | 0.6952  | 0.7719  |
| sink         | 0.5581  | 0.6146  | 0.1922  | 0.2739  |
| toilet       | 0.9100  | 0.9174  | 0.8313  | 0.8430  |
+--------------+---------+---------+---------+---------+
| Overall      | 0.5994  | 0.7525  | 0.4244  | 0.5339  |
+--------------+---------+---------+---------+---------+
2024-08-25 19:57:10,229 - mmdet - INFO - Epoch(val) [11][1685]	sofa_AP_0.25: 0.7932, table_AP_0.25: 0.6935, chair_AP_0.25: 0.7278, cabinet_AP_0.25: 0.5681, stool_AP_0.25: 0.2708, tv_monitor_AP_0.25: 0.0283, oven_AP_0.25: 0.6129, refrigerator_AP_0.25: 0.8333, bathtub_AP_0.25: 0.9447, shelf_AP_0.25: 0.4613, dishwasher_AP_0.25: 0.1960, fireplace_AP_0.25: 0.6930, stove_AP_0.25: 0.2333, bed_AP_0.25: 0.8766, washer_AP_0.25: 0.7886, sink_AP_0.25: 0.5581, toilet_AP_0.25: 0.9100, mAP_0.25: 0.5994, sofa_rec_0.25: 0.8635, table_rec_0.25: 0.8742, chair_rec_0.25: 0.8525, cabinet_rec_0.25: 0.6785, stool_rec_0.25: 0.6774, tv_monitor_rec_0.25: 0.1779, oven_rec_0.25: 0.7273, refrigerator_rec_0.25: 0.9634, bathtub_rec_0.25: 0.9694, shelf_rec_0.25: 0.6893, dishwasher_rec_0.25: 0.8800, fireplace_rec_0.25: 0.7778, stove_rec_0.25: 0.2857, bed_rec_0.25: 0.9392, washer_rec_0.25: 0.9035, sink_rec_0.25: 0.6146, toilet_rec_0.25: 0.9174, mAR_0.25: 0.7525, sofa_AP_0.50: 0.6532, table_AP_0.50: 0.4345, chair_AP_0.50: 0.4792, cabinet_AP_0.50: 0.3162, stool_AP_0.50: 0.1537, tv_monitor_AP_0.50: 0.0000, oven_AP_0.50: 0.4049, refrigerator_AP_0.50: 0.7537, bathtub_AP_0.50: 0.9042, shelf_AP_0.50: 0.1714, dishwasher_AP_0.50: 0.1472, fireplace_AP_0.50: 0.2391, stove_AP_0.50: 0.0258, bed_AP_0.50: 0.8133, washer_AP_0.50: 0.6952, sink_AP_0.50: 0.1922, toilet_AP_0.50: 0.8313, mAP_0.50: 0.4244, sofa_rec_0.50: 0.7034, table_rec_0.50: 0.5866, chair_rec_0.50: 0.5863, cabinet_rec_0.50: 0.4124, stool_rec_0.50: 0.3710, tv_monitor_rec_0.50: 0.0071, oven_rec_0.50: 0.4870, refrigerator_rec_0.50: 0.8049, bathtub_rec_0.50: 0.9184, shelf_rec_0.50: 0.2767, dishwasher_rec_0.50: 0.7200, fireplace_rec_0.50: 0.3704, stove_rec_0.50: 0.0816, bed_rec_0.50: 0.8619, washer_rec_0.50: 0.7719, sink_rec_0.50: 0.2739, toilet_rec_0.50: 0.8430, mAR_0.50: 0.5339
2024-08-25 19:59:30,682 - mmdet - INFO - Epoch [12][50/1685]	lr: 1.000e-06, eta: 1:16:50, time: 2.809, data_time: 0.142, memory: 19416, loss_occ: 0.5309, acc_occ: 0.8906, loss_centerness: 0.6053, loss_bbox: 0.3597, loss_cls: 0.1812, loss: 1.6770, grad_norm: 3.4358
2024-08-25 20:01:45,085 - mmdet - INFO - Epoch [12][100/1685]	lr: 1.000e-06, eta: 1:14:29, time: 2.688, data_time: 0.012, memory: 19416, loss_occ: 0.5164, acc_occ: 0.8912, loss_centerness: 0.6084, loss_bbox: 0.3692, loss_cls: 0.1917, loss: 1.6857, grad_norm: 3.3086
2024-08-25 20:03:58,367 - mmdet - INFO - Epoch [12][150/1685]	lr: 1.000e-06, eta: 1:12:07, time: 2.666, data_time: 0.011, memory: 19416, loss_occ: 0.5050, acc_occ: 0.8923, loss_centerness: 0.6024, loss_bbox: 0.3586, loss_cls: 0.1890, loss: 1.6550, grad_norm: 3.5637
2024-08-25 20:06:11,238 - mmdet - INFO - Epoch [12][200/1685]	lr: 1.000e-06, eta: 1:09:46, time: 2.657, data_time: 0.011, memory: 19416, loss_occ: 0.5240, acc_occ: 0.8932, loss_centerness: 0.6059, loss_bbox: 0.3585, loss_cls: 0.1835, loss: 1.6719, grad_norm: 3.3317
2024-08-25 20:08:24,628 - mmdet - INFO - Epoch [12][250/1685]	lr: 1.000e-06, eta: 1:07:24, time: 2.668, data_time: 0.010, memory: 19416, loss_occ: 0.5306, acc_occ: 0.8951, loss_centerness: 0.6060, loss_bbox: 0.3606, loss_cls: 0.1831, loss: 1.6802, grad_norm: 3.3378
2024-08-25 20:10:37,998 - mmdet - INFO - Epoch [12][300/1685]	lr: 1.000e-06, eta: 1:05:03, time: 2.667, data_time: 0.009, memory: 19416, loss_occ: 0.5333, acc_occ: 0.8929, loss_centerness: 0.6068, loss_bbox: 0.3669, loss_cls: 0.1889, loss: 1.6958, grad_norm: 3.3385
2024-08-25 20:12:51,384 - mmdet - INFO - Epoch [12][350/1685]	lr: 1.000e-06, eta: 1:02:41, time: 2.668, data_time: 0.009, memory: 19416, loss_occ: 0.5182, acc_occ: 0.8939, loss_centerness: 0.6063, loss_bbox: 0.3564, loss_cls: 0.1865, loss: 1.6674, grad_norm: 3.5349
2024-08-25 20:15:04,942 - mmdet - INFO - Epoch [12][400/1685]	lr: 1.000e-06, eta: 1:00:20, time: 2.671, data_time: 0.009, memory: 19416, loss_occ: 0.5160, acc_occ: 0.8924, loss_centerness: 0.6099, loss_bbox: 0.3639, loss_cls: 0.1912, loss: 1.6809, grad_norm: 3.3688
2024-08-25 20:17:18,797 - mmdet - INFO - Epoch [12][450/1685]	lr: 1.000e-06, eta: 0:57:58, time: 2.677, data_time: 0.010, memory: 19416, loss_occ: 0.5331, acc_occ: 0.8955, loss_centerness: 0.6048, loss_bbox: 0.3551, loss_cls: 0.1849, loss: 1.6779, grad_norm: 3.4629
2024-08-25 20:19:32,041 - mmdet - INFO - Epoch [12][500/1685]	lr: 1.000e-06, eta: 0:55:37, time: 2.665, data_time: 0.010, memory: 19416, loss_occ: 0.5084, acc_occ: 0.8894, loss_centerness: 0.6053, loss_bbox: 0.3641, loss_cls: 0.1874, loss: 1.6651, grad_norm: 3.3231
2024-08-25 20:21:46,119 - mmdet - INFO - Epoch [12][550/1685]	lr: 1.000e-06, eta: 0:53:16, time: 2.682, data_time: 0.013, memory: 19416, loss_occ: 0.5197, acc_occ: 0.8992, loss_centerness: 0.6041, loss_bbox: 0.3559, loss_cls: 0.1814, loss: 1.6611, grad_norm: 3.4104
2024-08-25 20:24:00,703 - mmdet - INFO - Epoch [12][600/1685]	lr: 1.000e-06, eta: 0:50:55, time: 2.692, data_time: 0.014, memory: 19416, loss_occ: 0.5137, acc_occ: 0.8898, loss_centerness: 0.6075, loss_bbox: 0.3637, loss_cls: 0.1974, loss: 1.6823, grad_norm: 3.5975
2024-08-25 20:26:14,048 - mmdet - INFO - Epoch [12][650/1685]	lr: 1.000e-06, eta: 0:48:34, time: 2.667, data_time: 0.014, memory: 19416, loss_occ: 0.5300, acc_occ: 0.8953, loss_centerness: 0.6048, loss_bbox: 0.3496, loss_cls: 0.1790, loss: 1.6634, grad_norm: 3.4151
2024-08-25 20:28:27,687 - mmdet - INFO - Epoch [12][700/1685]	lr: 1.000e-06, eta: 0:46:12, time: 2.673, data_time: 0.013, memory: 19417, loss_occ: 0.5236, acc_occ: 0.8957, loss_centerness: 0.6079, loss_bbox: 0.3570, loss_cls: 0.1861, loss: 1.6746, grad_norm: 3.4876
2024-08-25 20:30:41,626 - mmdet - INFO - Epoch [12][750/1685]	lr: 1.000e-06, eta: 0:43:51, time: 2.679, data_time: 0.013, memory: 19417, loss_occ: 0.5166, acc_occ: 0.8918, loss_centerness: 0.6043, loss_bbox: 0.3642, loss_cls: 0.1947, loss: 1.6799, grad_norm: 3.4202
2024-08-25 20:32:54,926 - mmdet - INFO - Epoch [12][800/1685]	lr: 1.000e-06, eta: 0:41:30, time: 2.666, data_time: 0.013, memory: 19417, loss_occ: 0.5121, acc_occ: 0.8932, loss_centerness: 0.6075, loss_bbox: 0.3613, loss_cls: 0.1872, loss: 1.6682, grad_norm: 3.3438
2024-08-25 20:35:08,064 - mmdet - INFO - Epoch [12][850/1685]	lr: 1.000e-06, eta: 0:39:09, time: 2.663, data_time: 0.014, memory: 19417, loss_occ: 0.5089, acc_occ: 0.8918, loss_centerness: 0.6059, loss_bbox: 0.3576, loss_cls: 0.1845, loss: 1.6569, grad_norm: 3.4506
2024-08-25 20:37:21,399 - mmdet - INFO - Epoch [12][900/1685]	lr: 1.000e-06, eta: 0:36:48, time: 2.667, data_time: 0.014, memory: 19417, loss_occ: 0.5141, acc_occ: 0.8951, loss_centerness: 0.6018, loss_bbox: 0.3519, loss_cls: 0.1821, loss: 1.6499, grad_norm: 3.4665
2024-08-25 20:39:34,921 - mmdet - INFO - Epoch [12][950/1685]	lr: 1.000e-06, eta: 0:34:27, time: 2.670, data_time: 0.012, memory: 19417, loss_occ: 0.5091, acc_occ: 0.8951, loss_centerness: 0.6074, loss_bbox: 0.3518, loss_cls: 0.1769, loss: 1.6452, grad_norm: 3.3552
2024-08-25 20:41:47,613 - mmdet - INFO - Epoch [12][1000/1685]	lr: 1.000e-06, eta: 0:32:06, time: 2.654, data_time: 0.012, memory: 19417, loss_occ: 0.5304, acc_occ: 0.8963, loss_centerness: 0.6035, loss_bbox: 0.3606, loss_cls: 0.1868, loss: 1.6812, grad_norm: 3.3832
2024-08-25 20:44:01,067 - mmdet - INFO - Epoch [12][1050/1685]	lr: 1.000e-06, eta: 0:29:45, time: 2.669, data_time: 0.012, memory: 19417, loss_occ: 0.5343, acc_occ: 0.8949, loss_centerness: 0.6039, loss_bbox: 0.3525, loss_cls: 0.1805, loss: 1.6711, grad_norm: 3.5071
2024-08-25 20:46:14,000 - mmdet - INFO - Epoch [12][1100/1685]	lr: 1.000e-06, eta: 0:27:25, time: 2.659, data_time: 0.013, memory: 19417, loss_occ: 0.5099, acc_occ: 0.8951, loss_centerness: 0.6035, loss_bbox: 0.3585, loss_cls: 0.1859, loss: 1.6579, grad_norm: 3.4951
2024-08-25 20:48:27,767 - mmdet - INFO - Epoch [12][1150/1685]	lr: 1.000e-06, eta: 0:25:04, time: 2.675, data_time: 0.012, memory: 19417, loss_occ: 0.5320, acc_occ: 0.8932, loss_centerness: 0.6084, loss_bbox: 0.3598, loss_cls: 0.1852, loss: 1.6854, grad_norm: 3.4438
2024-08-25 20:50:40,297 - mmdet - INFO - Epoch [12][1200/1685]	lr: 1.000e-06, eta: 0:22:43, time: 2.651, data_time: 0.013, memory: 19417, loss_occ: 0.5332, acc_occ: 0.8922, loss_centerness: 0.6055, loss_bbox: 0.3570, loss_cls: 0.1851, loss: 1.6807, grad_norm: 3.4139
2024-08-25 20:52:51,797 - mmdet - INFO - Epoch [12][1250/1685]	lr: 1.000e-06, eta: 0:20:22, time: 2.630, data_time: 0.013, memory: 19417, loss_occ: 0.5203, acc_occ: 0.8968, loss_centerness: 0.6019, loss_bbox: 0.3521, loss_cls: 0.1822, loss: 1.6565, grad_norm: 3.3893
2024-08-25 20:55:02,689 - mmdet - INFO - Epoch [12][1300/1685]	lr: 1.000e-06, eta: 0:18:02, time: 2.618, data_time: 0.013, memory: 19417, loss_occ: 0.5274, acc_occ: 0.8960, loss_centerness: 0.6045, loss_bbox: 0.3539, loss_cls: 0.1795, loss: 1.6653, grad_norm: 3.4154
2024-08-25 20:57:13,413 - mmdet - INFO - Epoch [12][1350/1685]	lr: 1.000e-06, eta: 0:15:41, time: 2.614, data_time: 0.012, memory: 19417, loss_occ: 0.5121, acc_occ: 0.8930, loss_centerness: 0.6046, loss_bbox: 0.3566, loss_cls: 0.1823, loss: 1.6556, grad_norm: 3.4016
2024-08-25 20:59:25,277 - mmdet - INFO - Epoch [12][1400/1685]	lr: 1.000e-06, eta: 0:13:20, time: 2.637, data_time: 0.010, memory: 19417, loss_occ: 0.5066, acc_occ: 0.8923, loss_centerness: 0.6023, loss_bbox: 0.3519, loss_cls: 0.1788, loss: 1.6396, grad_norm: 3.5052
2024-08-25 21:01:35,908 - mmdet - INFO - Epoch [12][1450/1685]	lr: 1.000e-06, eta: 0:11:00, time: 2.613, data_time: 0.010, memory: 19417, loss_occ: 0.5305, acc_occ: 0.8937, loss_centerness: 0.6033, loss_bbox: 0.3584, loss_cls: 0.1871, loss: 1.6792, grad_norm: 3.3667
2024-08-25 21:03:46,742 - mmdet - INFO - Epoch [12][1500/1685]	lr: 1.000e-06, eta: 0:08:39, time: 2.617, data_time: 0.011, memory: 19417, loss_occ: 0.5176, acc_occ: 0.8950, loss_centerness: 0.6082, loss_bbox: 0.3685, loss_cls: 0.1922, loss: 1.6865, grad_norm: 3.2869
2024-08-25 21:05:59,864 - mmdet - INFO - Epoch [12][1550/1685]	lr: 1.000e-06, eta: 0:06:19, time: 2.662, data_time: 0.013, memory: 19417, loss_occ: 0.5105, acc_occ: 0.8931, loss_centerness: 0.6030, loss_bbox: 0.3491, loss_cls: 0.1822, loss: 1.6447, grad_norm: 3.3358
2024-08-25 21:08:14,464 - mmdet - INFO - Epoch [12][1600/1685]	lr: 1.000e-06, eta: 0:03:58, time: 2.692, data_time: 0.014, memory: 19417, loss_occ: 0.5155, acc_occ: 0.8906, loss_centerness: 0.6071, loss_bbox: 0.3639, loss_cls: 0.1883, loss: 1.6748, grad_norm: 3.3972
2024-08-25 21:10:27,349 - mmdet - INFO - Epoch [12][1650/1685]	lr: 1.000e-06, eta: 0:01:38, time: 2.658, data_time: 0.013, memory: 19417, loss_occ: 0.5200, acc_occ: 0.8987, loss_centerness: 0.6074, loss_bbox: 0.3594, loss_cls: 0.1857, loss: 1.6725, grad_norm: 3.4239
2024-08-25 21:12:00,895 - mmdet - INFO - Saving checkpoint at 12 epochs
2024-08-25 21:14:05,500 - mmdet - INFO - 
+--------------+---------+---------+---------+---------+
| classes      | AP_0.25 | AR_0.25 | AP_0.50 | AR_0.50 |
+--------------+---------+---------+---------+---------+
| sofa         | 0.7923  | 0.8661  | 0.6551  | 0.7060  |
| table        | 0.7011  | 0.8742  | 0.4430  | 0.5931  |
| chair        | 0.7318  | 0.8512  | 0.4873  | 0.5863  |
| cabinet      | 0.5662  | 0.6741  | 0.3159  | 0.4124  |
| stool        | 0.2654  | 0.6667  | 0.1428  | 0.3548  |
| tv_monitor   | 0.0355  | 0.1922  | 0.0000  | 0.0071  |
| oven         | 0.6247  | 0.7338  | 0.4182  | 0.5065  |
| refrigerator | 0.8312  | 0.9634  | 0.7677  | 0.8293  |
| bathtub      | 0.9456  | 0.9694  | 0.9072  | 0.9184  |
| dishwasher   | 0.2024  | 0.8800  | 0.1470  | 0.6800  |
| shelf        | 0.4523  | 0.6699  | 0.1734  | 0.2718  |
| fireplace    | 0.6539  | 0.7593  | 0.2664  | 0.3704  |
| stove        | 0.2360  | 0.2857  | 0.0228  | 0.0714  |
| bed          | 0.8865  | 0.9503  | 0.8309  | 0.8840  |
| washer       | 0.7840  | 0.8772  | 0.6873  | 0.7456  |
| sink         | 0.5519  | 0.6242  | 0.1858  | 0.2707  |
| toilet       | 0.9092  | 0.9174  | 0.8179  | 0.8264  |
+--------------+---------+---------+---------+---------+
| Overall      | 0.5982  | 0.7503  | 0.4276  | 0.5314  |
+--------------+---------+---------+---------+---------+
2024-08-25 21:14:05,982 - mmdet - INFO - Epoch(val) [12][1685]	sofa_AP_0.25: 0.7923, table_AP_0.25: 0.7011, chair_AP_0.25: 0.7318, cabinet_AP_0.25: 0.5662, stool_AP_0.25: 0.2654, tv_monitor_AP_0.25: 0.0355, oven_AP_0.25: 0.6247, refrigerator_AP_0.25: 0.8312, bathtub_AP_0.25: 0.9456, dishwasher_AP_0.25: 0.2024, shelf_AP_0.25: 0.4523, fireplace_AP_0.25: 0.6539, stove_AP_0.25: 0.2360, bed_AP_0.25: 0.8865, washer_AP_0.25: 0.7840, sink_AP_0.25: 0.5519, toilet_AP_0.25: 0.9092, mAP_0.25: 0.5982, sofa_rec_0.25: 0.8661, table_rec_0.25: 0.8742, chair_rec_0.25: 0.8512, cabinet_rec_0.25: 0.6741, stool_rec_0.25: 0.6667, tv_monitor_rec_0.25: 0.1922, oven_rec_0.25: 0.7338, refrigerator_rec_0.25: 0.9634, bathtub_rec_0.25: 0.9694, dishwasher_rec_0.25: 0.8800, shelf_rec_0.25: 0.6699, fireplace_rec_0.25: 0.7593, stove_rec_0.25: 0.2857, bed_rec_0.25: 0.9503, washer_rec_0.25: 0.8772, sink_rec_0.25: 0.6242, toilet_rec_0.25: 0.9174, mAR_0.25: 0.7503, sofa_AP_0.50: 0.6551, table_AP_0.50: 0.4430, chair_AP_0.50: 0.4873, cabinet_AP_0.50: 0.3159, stool_AP_0.50: 0.1428, tv_monitor_AP_0.50: 0.0000, oven_AP_0.50: 0.4182, refrigerator_AP_0.50: 0.7677, bathtub_AP_0.50: 0.9072, dishwasher_AP_0.50: 0.1470, shelf_AP_0.50: 0.1734, fireplace_AP_0.50: 0.2664, stove_AP_0.50: 0.0228, bed_AP_0.50: 0.8309, washer_AP_0.50: 0.6873, sink_AP_0.50: 0.1858, toilet_AP_0.50: 0.8179, mAP_0.50: 0.4276, sofa_rec_0.50: 0.7060, table_rec_0.50: 0.5931, chair_rec_0.50: 0.5863, cabinet_rec_0.50: 0.4124, stool_rec_0.50: 0.3548, tv_monitor_rec_0.50: 0.0071, oven_rec_0.50: 0.5065, refrigerator_rec_0.50: 0.8293, bathtub_rec_0.50: 0.9184, dishwasher_rec_0.50: 0.6800, shelf_rec_0.50: 0.2718, fireplace_rec_0.50: 0.3704, stove_rec_0.50: 0.0714, bed_rec_0.50: 0.8840, washer_rec_0.50: 0.7456, sink_rec_0.50: 0.2707, toilet_rec_0.50: 0.8264, mAR_0.50: 0.5314