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labelmatch_1_5_40k.log
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2021-11-07 07:22:11,405 - mmdet - INFO - Environment info:
------------------------------------------------------------
sys.platform: linux
Python: 3.6.5 |Anaconda, Inc.| (default, Apr 29 2018, 16:14:56) [GCC 7.2.0]
CUDA available: True
GPU 0,1,2,3,4,5,6,7: Tesla V100-SXM2-32GB
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 10.1, V10.1.243
GCC: gcc (Ubuntu 5.4.0-6ubuntu1~16.04.12) 5.4.0 20160609
PyTorch: 1.5.0+cu101
PyTorch compiling details: PyTorch built with:
- GCC 7.3
- C++ Version: 201402
- Intel(R) Math Kernel Library Version 2019.0.5 Product Build 20190808 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v0.21.1 (Git Hash 7d2fd500bc78936d1d648ca713b901012f470dbc)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- NNPACK is enabled
- CPU capability usage: AVX2
- CUDA Runtime 10.1
- 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_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_37,code=compute_37
- CuDNN 7.6.3
- Magma 2.5.2
- Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_INTERNAL_THREADPOOL_IMPL -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-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -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, USE_STATIC_DISPATCH=OFF,
TorchVision: 0.6.0+cu101
OpenCV: 4.5.1
MMCV: 1.2.7
MMCV Compiler: GCC 5.4
MMCV CUDA Compiler: 10.1
MMDetection: 2.10.0+unknown
------------------------------------------------------------
2021-11-07 07:22:14,370 - mmdet - INFO - Distributed training: True
2021-11-07 07:22:17,342 - mmdet - INFO - Config:
seed = 1
percent = 5
gpu = 8
score = 0.9
samples_per_gpu = 4
total_iter = 40000
update_interval = 1000
test_interval = 2000
save_interval = 10000
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
image_size = (1024, 1024)
pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='Resize',
img_scale=(1024, 1024),
ratio_range=(0.5, 1.5),
keep_ratio=True),
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='AugmentationUT', use_re=False),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
]
pipeline_u_share = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='RandomFlip', flip_ratio=0.5)
]
pipeline_u = [
dict(type='AddBBoxTransform'),
dict(
type='ResizeBox',
img_scale=[(1333, 500), (1333, 800)],
keep_ratio=True),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(
type='Collect',
keys=['img', 'gt_bboxes', 'gt_labels'],
meta_keys=('filename', 'ori_filename', 'ori_shape', 'img_shape',
'pad_shape', 'scale_factor', 'flip', 'flip_direction',
'img_norm_cfg', 'bbox_transform'))
]
pipeline_u_1 = [
dict(type='AddBBoxTransform'),
dict(
type='ResizeBox',
img_scale=(1024, 1024),
ratio_range=(0.5, 1.5),
keep_ratio=True),
dict(type='AugmentationUT', use_re=True, use_box=False),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(
type='Collect',
keys=['img', 'gt_bboxes', 'gt_labels'],
meta_keys=('filename', 'ori_filename', 'ori_shape', 'img_shape',
'pad_shape', 'scale_factor', 'flip', 'flip_direction',
'img_norm_cfg', 'bbox_transform'))
]
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(1333, 800),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]
dataset_type = 'CocoDataset'
data_root = './dataset/coco/'
data = dict(
samples_per_gpu=4,
workers_per_gpu=4,
train=dict(
type='SemiDataset',
ann_file=
'./dataset/coco/annotations/semi_supervised/[email protected]',
ann_file_u=
'./dataset/coco/annotations/semi_supervised/[email protected]',
pipeline=[
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='Resize',
img_scale=(1024, 1024),
ratio_range=(0.5, 1.5),
keep_ratio=True),
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='AugmentationUT', use_re=False),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
],
pipeline_u_share=[
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='RandomFlip', flip_ratio=0.5)
],
pipeline_u=[
dict(type='AddBBoxTransform'),
dict(
type='ResizeBox',
img_scale=[(1333, 500), (1333, 800)],
keep_ratio=True),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(
type='Collect',
keys=['img', 'gt_bboxes', 'gt_labels'],
meta_keys=('filename', 'ori_filename', 'ori_shape',
'img_shape', 'pad_shape', 'scale_factor', 'flip',
'flip_direction', 'img_norm_cfg', 'bbox_transform'))
],
pipeline_u_1=[
dict(type='AddBBoxTransform'),
dict(
type='ResizeBox',
img_scale=(1024, 1024),
ratio_range=(0.5, 1.5),
keep_ratio=True),
dict(type='AugmentationUT', use_re=True, use_box=False),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(
type='Collect',
keys=['img', 'gt_bboxes', 'gt_labels'],
meta_keys=('filename', 'ori_filename', 'ori_shape',
'img_shape', 'pad_shape', 'scale_factor', 'flip',
'flip_direction', 'img_norm_cfg', 'bbox_transform'))
],
img_prefix='./dataset/coco/train2017/',
img_prefix_u='./dataset/coco/train2017/'),
val=dict(
type='CocoDataset',
ann_file='./dataset/coco/annotations/instances_val2017.json',
img_prefix='./dataset/coco/val2017/',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(1333, 800),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]),
test=dict(
type='CocoDataset',
ann_file='./dataset/coco/annotations/instances_val2017.json',
img_prefix='./dataset/coco/val2017/',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(1333, 800),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]))
evaluation = dict(interval=2000, metric='bbox', by_epoch=False, classwise=True)
learning_rate = 0.02
optimizer = dict(type='SGD', lr=0.02, momentum=0.9, weight_decay=0.0001)
optimizer_config = dict(grad_clip=None)
lr_config = dict(
policy='step',
warmup='linear',
warmup_iters=500,
warmup_ratio=0.001,
step=[40000])
runner = dict(type='SemiIterBasedRunner', max_iters=40000)
checkpoint_config = dict(interval=10000)
log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook')])
labelmatch_hook_cfg = dict(
samples_per_gpu=4,
workers_per_gpu=4,
label_file=
'./dataset/coco/annotations/semi_supervised/[email protected]',
evaluation=dict(interval=1000, metric='bbox', by_epoch=False),
data=dict(
type='TXTDataset',
img_prefix='./dataset/coco/train2017/',
ann_file=
'./dataset/coco/annotations/semi_supervised_txt/[email protected]',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(1333, 800),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
],
manual_length=10000))
custom_hooks = [
dict(type='NumClassCheckHook'),
dict(
type='LabelMatchHook',
cfg=dict(
samples_per_gpu=4,
workers_per_gpu=4,
label_file=
'./dataset/coco/annotations/semi_supervised/[email protected]',
evaluation=dict(interval=1000, metric='bbox', by_epoch=False),
data=dict(
type='TXTDataset',
img_prefix='./dataset/coco/train2017/',
ann_file=
'./dataset/coco/annotations/semi_supervised_txt/[email protected]',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(1333, 800),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
],
manual_length=10000)))
]
dist_params = dict(backend='nccl')
log_level = 'INFO'
resume_from = None
load_from = './pretrained_model/baseline/[email protected]'
workflow = [('train', 1)]
model = dict(
type='LabelMatch',
ema_config='./configs/baseline/baseline_base.py',
ema_ckpt='./pretrained_model/baseline/[email protected]',
cfg=dict(debug=False),
pretrained='./pretrained_model/backbone/resnet50-19c8e357.pth',
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=True),
norm_eval=True,
style='pytorch'),
neck=dict(
type='FPN',
in_channels=[256, 512, 1024, 2048],
out_channels=256,
num_outs=5),
rpn_head=dict(
type='RPNHead',
in_channels=256,
feat_channels=256,
anchor_generator=dict(
type='AnchorGenerator',
scales=[8],
ratios=[0.5, 1.0, 2.0],
strides=[4, 8, 16, 32, 64]),
bbox_coder=dict(
type='DeltaXYWHBBoxCoder',
target_means=[0.0, 0.0, 0.0, 0.0],
target_stds=[1.0, 1.0, 1.0, 1.0]),
loss_cls=dict(
type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),
loss_bbox=dict(type='L1Loss', loss_weight=1.0)),
roi_head=dict(
type='StandardRoIHeadLM',
bbox_roi_extractor=dict(
type='SingleRoIExtractor',
roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=0),
out_channels=256,
featmap_strides=[4, 8, 16, 32]),
bbox_head=dict(
type='Shared2FCBBoxHeadLM',
in_channels=256,
fc_out_channels=1024,
roi_feat_size=7,
num_classes=80,
bbox_coder=dict(
type='DeltaXYWHBBoxCoder',
target_means=[0.0, 0.0, 0.0, 0.0],
target_stds=[0.1, 0.1, 0.2, 0.2]),
reg_class_agnostic=True,
loss_cls=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),
loss_bbox=dict(type='L1Loss', loss_weight=1.0))),
train_cfg=dict(
rpn=dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7,
neg_iou_thr=0.3,
min_pos_iou=0.3,
match_low_quality=True,
ignore_iof_thr=-1),
sampler=dict(
type='RandomSampler',
num=256,
pos_fraction=0.5,
neg_pos_ub=-1,
add_gt_as_proposals=False),
allowed_border=-1,
pos_weight=-1,
debug=False),
rpn_proposal=dict(
nms_pre=2000,
max_per_img=1000,
nms=dict(type='nms', iou_threshold=0.7),
min_bbox_size=0),
rcnn=dict(
assigner=dict(
type='MaxIoUAssignerLM',
pos_iou_thr=0.5,
neg_iou_thr=0.5,
min_pos_iou=0.5,
match_low_quality=False,
ignore_wrt_candidates=False,
ignore_iof_thr=0.5),
sampler=dict(
type='RandomSamplerLM',
num=512,
pos_fraction=0.25,
neg_pos_ub=-1,
add_gt_as_proposals=True),
pos_weight=-1,
ig_weight=0.0,
debug=False)),
test_cfg=dict(
rpn=dict(
nms_pre=1000,
max_per_img=1000,
nms=dict(type='nms', iou_threshold=0.7),
min_bbox_size=0),
rcnn=dict(
score_thr=0.001,
nms=dict(type='nms', iou_threshold=0.5),
max_per_img=100)))
work_dir = './work_dirs/labelmatch_0.9_1_5_8'
gpu_ids = range(0, 8)
2021-11-07 07:22:17,670 - mmdet - INFO - load model from: ./pretrained_model/backbone/resnet50-19c8e357.pth
2021-11-07 07:22:17,670 - mmdet - INFO - Use load_from_local loader
2021-11-07 07:22:17,900 - mmdet - WARNING - The model and loaded state dict do not match exactly
unexpected key in source state_dict: fc.weight, fc.bias
2021-11-07 07:22:19,494 - mmdet - INFO - load model from: ./pretrained_model/backbone/resnet50-19c8e357.pth
2021-11-07 07:22:19,494 - mmdet - INFO - Use load_from_local loader
2021-11-07 07:22:19,732 - mmdet - WARNING - The model and loaded state dict do not match exactly
unexpected key in source state_dict: fc.weight, fc.bias
2021-11-07 07:22:41,730 - mmdet - INFO - Loading 112523 images, cost 0.11752128601074219
2021-11-07 07:22:42,241 - mmdet - INFO - boxes per image (label data): 7.467904233171409
2021-11-07 07:22:42,241 - mmdet - INFO - class ratio (label data): (0.3090-person) (0.0065-bicycle) (0.0502-car) (0.0084-motorcycle) (0.0054-airplane) (0.0062-bus) (0.0058-train) (0.0124-truck) (0.0135-boat) (0.0153-traffic light) (0.0019-fire hydrant) (0.0024-stop sign) (0.0013-parking meter) (0.0112-bench) (0.0112-bird) (0.0056-cat) (0.0056-dog) (0.0074-horse) (0.0121-sheep) (0.0114-cow) (0.0060-elephant) (0.0014-bear) (0.0059-zebra) (0.0062-giraffe) (0.0108-backpack) (0.0149-umbrella) (0.0149-handbag) (0.0057-tie) (0.0072-suitcase) (0.0029-frisbee) (0.0082-skis) (0.0027-snowboard) (0.0075-sports ball) (0.0098-kite) (0.0043-baseball bat) (0.0041-baseball glove) (0.0063-skateboard) (0.0083-surfboard) (0.0052-tennis racket) (0.0266-bottle) (0.0080-wine glass) (0.0285-cup) (0.0065-fork) (0.0090-knife) (0.0079-spoon) (0.0192-bowl) (0.0116-banana) (0.0072-apple) (0.0053-sandwich) (0.0085-orange) (0.0079-broccoli) (0.0079-carrot) (0.0026-hot dog) (0.0075-pizza) (0.0089-donut) (0.0072-cake) (0.0445-chair) (0.0066-couch) (0.0088-potted plant) (0.0045-bed) (0.0173-dining table) (0.0042-toilet) (0.0066-tv) (0.0062-laptop) (0.0021-mouse) (0.0071-remote) (0.0031-keyboard) (0.0085-cell phone) (0.0018-microwave) (0.0041-oven) (0.0002-toaster) (0.0062-sink) (0.0031-refrigerator) (0.0265-book) (0.0064-clock) (0.0071-vase) (0.0018-scissors) (0.0054-teddy bear) (0.0002-hair drier) (0.0023-toothbrush)
2021-11-07 07:22:42,242 - mmdet - INFO - load checkpoint from ./pretrained_model/baseline/[email protected]
2021-11-07 07:22:42,242 - mmdet - INFO - Use load_from_local loader
2021-11-07 07:22:43,518 - mmdet - INFO - Start running, host: root@train-hz-v100-0, work_dir: /data1/mmdet_ssod/work_dirs/labelmatch_0.9_1_5_8
2021-11-07 07:22:43,519 - mmdet - INFO - workflow: [('train', 1)], max: 40000 iters
2021-11-07 07:25:13,407 - mmdet - INFO - current percent: 0.2
2021-11-07 07:25:13,407 - mmdet - INFO - update score thr (positive): (0.99-person) (0.94-bicycle) (0.96-car) (0.97-motorcycle) (0.99-airplane) (0.98-bus) (0.99-train) (0.93-truck) (0.84-boat) (0.93-traffic light) (1.00-fire hydrant) (1.00-stop sign) (0.83-parking meter) (0.87-bench) (0.93-bird) (0.99-cat) (0.97-dog) (0.98-horse) (0.98-sheep) (0.93-cow) (0.99-elephant) (0.97-bear) (1.00-zebra) (1.00-giraffe) (0.70-backpack) (0.93-umbrella) (0.55-handbag) (0.93-tie) (0.84-suitcase) (0.99-frisbee) (0.81-skis) (0.65-snowboard) (0.99-sports ball) (0.98-kite) (0.93-baseball bat) (0.96-baseball glove) (0.96-skateboard) (0.90-surfboard) (0.99-tennis racket) (0.93-bottle) (0.96-wine glass) (0.94-cup) (0.66-fork) (0.63-knife) (0.55-spoon) (0.95-bowl) (0.87-banana) (0.82-apple) (0.90-sandwich) (0.83-orange) (0.96-broccoli) (0.92-carrot) (0.88-hot dog) (0.97-pizza) (0.94-donut) (0.89-cake) (0.82-chair) (0.84-couch) (0.91-potted plant) (0.93-bed) (0.87-dining table) (1.00-toilet) (0.99-tv) (0.99-laptop) (0.98-mouse) (0.80-remote) (0.96-keyboard) (0.90-cell phone) (0.91-microwave) (0.92-oven) (0.05-toaster) (0.96-sink) (0.90-refrigerator) (0.74-book) (1.00-clock) (0.94-vase) (0.78-scissors) (0.96-teddy bear) (0.05-hair drier) (0.55-toothbrush)
2021-11-07 07:25:13,408 - mmdet - INFO - update score thr (ignore): (0.53-person) (0.56-bicycle) (0.46-car) (0.54-motorcycle) (0.74-airplane) (0.53-bus) (0.52-train) (0.50-truck) (0.33-boat) (0.34-traffic light) (0.49-fire hydrant) (0.52-stop sign) (0.23-parking meter) (0.39-bench) (0.26-bird) (0.66-cat) (0.56-dog) (0.49-horse) (0.32-sheep) (0.36-cow) (0.58-elephant) (0.51-bear) (0.57-zebra) (0.42-giraffe) (0.31-backpack) (0.37-umbrella) (0.26-handbag) (0.42-tie) (0.39-suitcase) (0.54-frisbee) (0.43-skis) (0.33-snowboard) (0.20-sports ball) (0.45-kite) (0.32-baseball bat) (0.36-baseball glove) (0.43-skateboard) (0.35-surfboard) (0.26-tennis racket) (0.37-bottle) (0.31-wine glass) (0.35-cup) (0.25-fork) (0.30-knife) (0.22-spoon) (0.46-bowl) (0.35-banana) (0.25-apple) (0.55-sandwich) (0.27-orange) (0.60-broccoli) (0.50-carrot) (0.45-hot dog) (0.42-pizza) (0.36-donut) (0.43-cake) (0.34-chair) (0.44-couch) (0.50-potted plant) (0.56-bed) (0.49-dining table) (0.74-toilet) (0.64-tv) (0.45-laptop) (0.44-mouse) (0.32-remote) (0.54-keyboard) (0.32-cell phone) (0.46-microwave) (0.47-oven) (0.05-toaster) (0.50-sink) (0.51-refrigerator) (0.43-book) (0.52-clock) (0.44-vase) (0.35-scissors) (0.52-teddy bear) (0.05-hair drier) (0.25-toothbrush)
2021-11-07 07:26:39,035 - mmdet - INFO - Iter [50/40000] lr: 1.978e-03, eta: 1 day, 13:28:39, time: 3.377, data_time: 0.022, memory: 24330, loss_rpn_cls: 0.0491, loss_rpn_bbox: 0.0581, loss_cls: 0.2602, acc: 91.6437, loss_bbox: 0.2921, loss_rpn_cls_unlabeled: 0.2161, loss_rpn_bbox_unlabeled: 0.1174, loss_cls_unlabeled: 0.2427, acc_unlabeled: 91.3063, loss_bbox_unlabeled: 0.1698, losses_cls_ig_unlabeled: 0.1863, pseudo_num: 1.5308, pseudo_num_ig: 5.5611, pseudo_num_mining: 0.5915, pseudo_num(acc): 0.8460, pseudo_num ig(acc): 0.4443, loss: 1.5917
2021-11-07 07:28:04,135 - mmdet - INFO - Iter [100/40000] lr: 3.976e-03, eta: 1 day, 4:08:26, time: 1.701, data_time: 0.028, memory: 24765, loss_rpn_cls: 0.0457, loss_rpn_bbox: 0.0578, loss_cls: 0.2601, acc: 91.4984, loss_bbox: 0.3034, loss_rpn_cls_unlabeled: 0.1286, loss_rpn_bbox_unlabeled: 0.1106, loss_cls_unlabeled: 0.2283, acc_unlabeled: 90.9784, loss_bbox_unlabeled: 0.1756, losses_cls_ig_unlabeled: 0.1845, pseudo_num: 1.4659, pseudo_num_ig: 5.5751, pseudo_num_mining: 0.5360, pseudo_num(acc): 0.8419, pseudo_num ig(acc): 0.4483, loss: 1.4946
2021-11-07 07:29:29,225 - mmdet - INFO - Iter [150/40000] lr: 5.974e-03, eta: 1 day, 1:00:59, time: 1.702, data_time: 0.031, memory: 25141, loss_rpn_cls: 0.0430, loss_rpn_bbox: 0.0559, loss_cls: 0.2597, acc: 91.5516, loss_bbox: 0.2984, loss_rpn_cls_unlabeled: 0.1186, loss_rpn_bbox_unlabeled: 0.1054, loss_cls_unlabeled: 0.2106, acc_unlabeled: 91.0226, loss_bbox_unlabeled: 0.1641, losses_cls_ig_unlabeled: 0.1833, pseudo_num: 1.4469, pseudo_num_ig: 5.5752, pseudo_num_mining: 0.5173, pseudo_num(acc): 0.8482, pseudo_num ig(acc): 0.4517, loss: 1.4390
2021-11-07 07:30:52,801 - mmdet - INFO - Iter [200/40000] lr: 7.972e-03, eta: 23:21:36, time: 1.672, data_time: 0.028, memory: 25141, loss_rpn_cls: 0.0456, loss_rpn_bbox: 0.0548, loss_cls: 0.2640, acc: 91.4485, loss_bbox: 0.3007, loss_rpn_cls_unlabeled: 0.1169, loss_rpn_bbox_unlabeled: 0.1056, loss_cls_unlabeled: 0.2139, acc_unlabeled: 91.0035, loss_bbox_unlabeled: 0.1688, losses_cls_ig_unlabeled: 0.1794, pseudo_num: 1.4325, pseudo_num_ig: 5.5617, pseudo_num_mining: 0.5002, pseudo_num(acc): 0.8487, pseudo_num ig(acc): 0.4506, loss: 1.4496
2021-11-07 07:32:18,061 - mmdet - INFO - Iter [250/40000] lr: 9.970e-03, eta: 22:26:04, time: 1.707, data_time: 0.028, memory: 25141, loss_rpn_cls: 0.0484, loss_rpn_bbox: 0.0572, loss_cls: 0.2693, acc: 91.3477, loss_bbox: 0.3004, loss_rpn_cls_unlabeled: 0.1137, loss_rpn_bbox_unlabeled: 0.1024, loss_cls_unlabeled: 0.2076, acc_unlabeled: 91.2988, loss_bbox_unlabeled: 0.1621, losses_cls_ig_unlabeled: 0.1767, pseudo_num: 1.4161, pseudo_num_ig: 5.5368, pseudo_num_mining: 0.4841, pseudo_num(acc): 0.8494, pseudo_num ig(acc): 0.4513, loss: 1.4379
2021-11-07 07:33:41,996 - mmdet - INFO - Iter [300/40000] lr: 1.197e-02, eta: 21:45:08, time: 1.676, data_time: 0.026, memory: 25141, loss_rpn_cls: 0.0486, loss_rpn_bbox: 0.0574, loss_cls: 0.2648, acc: 91.4619, loss_bbox: 0.2978, loss_rpn_cls_unlabeled: 0.1198, loss_rpn_bbox_unlabeled: 0.1069, loss_cls_unlabeled: 0.2146, acc_unlabeled: 90.9598, loss_bbox_unlabeled: 0.1643, losses_cls_ig_unlabeled: 0.1846, pseudo_num: 1.4032, pseudo_num_ig: 5.5216, pseudo_num_mining: 0.4829, pseudo_num(acc): 0.8493, pseudo_num ig(acc): 0.4552, loss: 1.4588
2021-11-07 07:35:06,676 - mmdet - INFO - Iter [350/40000] lr: 1.397e-02, eta: 21:17:12, time: 1.694, data_time: 0.028, memory: 25141, loss_rpn_cls: 0.0475, loss_rpn_bbox: 0.0590, loss_cls: 0.2723, acc: 91.2532, loss_bbox: 0.3048, loss_rpn_cls_unlabeled: 0.1166, loss_rpn_bbox_unlabeled: 0.1025, loss_cls_unlabeled: 0.2122, acc_unlabeled: 91.0820, loss_bbox_unlabeled: 0.1616, losses_cls_ig_unlabeled: 0.1817, pseudo_num: 1.3890, pseudo_num_ig: 5.5211, pseudo_num_mining: 0.4857, pseudo_num(acc): 0.8493, pseudo_num ig(acc): 0.4576, loss: 1.4582
2021-11-07 07:36:30,523 - mmdet - INFO - Iter [400/40000] lr: 1.596e-02, eta: 20:54:19, time: 1.675, data_time: 0.027, memory: 25141, loss_rpn_cls: 0.0486, loss_rpn_bbox: 0.0575, loss_cls: 0.2788, acc: 91.2075, loss_bbox: 0.3032, loss_rpn_cls_unlabeled: 0.1215, loss_rpn_bbox_unlabeled: 0.1155, loss_cls_unlabeled: 0.2264, acc_unlabeled: 90.6219, loss_bbox_unlabeled: 0.1770, losses_cls_ig_unlabeled: 0.1928, pseudo_num: 1.3911, pseudo_num_ig: 5.5299, pseudo_num_mining: 0.4888, pseudo_num(acc): 0.8481, pseudo_num ig(acc): 0.4596, loss: 1.5213
2021-11-07 07:37:54,224 - mmdet - INFO - Iter [450/40000] lr: 1.796e-02, eta: 20:36:27, time: 1.678, data_time: 0.029, memory: 25141, loss_rpn_cls: 0.0521, loss_rpn_bbox: 0.0592, loss_cls: 0.2915, acc: 90.9072, loss_bbox: 0.3096, loss_rpn_cls_unlabeled: 0.1198, loss_rpn_bbox_unlabeled: 0.1103, loss_cls_unlabeled: 0.2181, acc_unlabeled: 90.6259, loss_bbox_unlabeled: 0.1708, losses_cls_ig_unlabeled: 0.1927, pseudo_num: 1.3947, pseudo_num_ig: 5.5504, pseudo_num_mining: 0.4915, pseudo_num(acc): 0.8484, pseudo_num ig(acc): 0.4594, loss: 1.5240
2021-11-07 07:39:17,788 - mmdet - INFO - pseudo pos: 0.99(799.0-person) 1.00(18.0-bicycle) 0.95(125.0-car) 0.91(23.0-motorcycle) 1.00(12.0-airplane) 0.97(30.0-bus) 0.95(21.0-train) 0.83(29.0-truck) 0.71(31.0-boat) 0.85(48.0-traffic light) 1.00(7.0-fire hydrant) 1.00(6.0-stop sign) 0.86(7.0-parking meter) 0.65(31.0-bench) 0.88(49.0-bird) 0.86(14.0-cat) 1.00(18.0-dog) 1.00(19.0-horse) 0.93(54.0-sheep) 0.89(36.0-cow) 1.00(22.0-elephant) 1.00(6.0-bear) 1.00(13.0-zebra) 0.95(20.0-giraffe) 0.56(45.0-backpack) 0.79(38.0-umbrella) 0.51(37.0-handbag) 1.00(7.0-tie) 0.71(17.0-suitcase) 1.00(9.0-frisbee) 0.50(32.0-skis) 0.75(8.0-snowboard) 1.00(16.0-sports ball) 1.00(16.0-kite) 1.00(9.0-baseball bat) 1.00(17.0-baseball glove) 1.00(20.0-skateboard) 0.87(31.0-surfboard) 0.95(20.0-tennis racket) 0.81(79.0-bottle) 1.00(21.0-wine glass) 0.92(73.0-cup) 0.71(7.0-fork) 0.26(27.0-knife) 0.39(33.0-spoon) 0.83(48.0-bowl) 0.56(18.0-banana) 0.68(22.0-apple) 0.69(13.0-sandwich) 0.43(30.0-orange) 0.81(26.0-broccoli) 0.80(10.0-carrot) 0.75(4.0-hot dog) 0.96(23.0-pizza) 0.87(31.0-donut) 0.77(13.0-cake) 0.63(111.0-chair) 0.74(46.0-couch) 0.64(22.0-potted plant) 0.94(16.0-bed) 0.69(55.0-dining table) 0.70(10.0-toilet) 1.00(20.0-tv) 1.00(15.0-laptop) 1.00(3.0-mouse) 0.75(16.0-remote) 0.82(11.0-keyboard) 0.85(27.0-cell phone) 0.87(8.0-microwave) 0.80(15.0-oven) 0.00(0.0-toaster) 0.76(17.0-sink) 0.89(9.0-refrigerator) 0.30(56.0-book) 0.92(12.0-clock) 0.80(25.0-vase) 1.00(1.0-scissors) 0.90(20.0-teddy bear) 0.00(0.0-hair drier) 0.00(5.0-toothbrush)
2021-11-07 07:39:17,942 - mmdet - INFO - pseudo ig: 0.65(3160.0-person) 0.45(44.0-bicycle) 0.51(491.0-car) 0.49(87.0-motorcycle) 0.78(51.0-airplane) 0.50(62.0-bus) 0.69(54.0-train) 0.47(92.0-truck) 0.25(155.0-boat) 0.34(155.0-traffic light) 0.71(17.0-fire hydrant) 0.39(33.0-stop sign) 0.50(8.0-parking meter) 0.19(115.0-bench) 0.39(219.0-bird) 0.77(56.0-cat) 0.61(61.0-dog) 0.72(74.0-horse) 0.43(159.0-sheep) 0.44(131.0-cow) 0.66(90.0-elephant) 0.61(18.0-bear) 0.78(59.0-zebra) 0.77(84.0-giraffe) 0.19(154.0-backpack) 0.38(148.0-umbrella) 0.16(153.0-handbag) 0.50(40.0-tie) 0.26(61.0-suitcase) 0.69(26.0-frisbee) 0.30(136.0-skis) 0.48(27.0-snowboard) 0.38(82.0-sports ball) 0.40(126.0-kite) 0.35(60.0-baseball bat) 0.40(63.0-baseball glove) 0.51(69.0-skateboard) 0.34(99.0-surfboard) 0.45(85.0-tennis racket) 0.36(371.0-bottle) 0.41(113.0-wine glass) 0.32(309.0-cup) 0.23(70.0-fork) 0.24(67.0-knife) 0.18(74.0-spoon) 0.41(175.0-bowl) 0.28(151.0-banana) 0.25(125.0-apple) 0.32(50.0-sandwich) 0.21(294.0-orange) 0.43(96.0-broccoli) 0.41(44.0-carrot) 0.50(20.0-hot dog) 0.53(92.0-pizza) 0.27(101.0-donut) 0.53(45.0-cake) 0.31(430.0-chair) 0.27(107.0-couch) 0.41(111.0-potted plant) 0.43(44.0-bed) 0.34(196.0-dining table) 0.72(43.0-toilet) 0.73(63.0-tv) 0.51(92.0-laptop) 0.49(35.0-mouse) 0.20(90.0-remote) 0.48(44.0-keyboard) 0.23(115.0-cell phone) 0.59(22.0-microwave) 0.16(63.0-oven) 0.00(0.0-toaster) 0.33(66.0-sink) 0.47(34.0-refrigerator) 0.17(311.0-book) 0.59(87.0-clock) 0.25(69.0-vase) 0.18(11.0-scissors) 0.54(69.0-teddy bear) 0.00(0.0-hair drier) 0.14(21.0-toothbrush)
2021-11-07 07:39:17,942 - mmdet - INFO - pseudo gt: 4279.0 108.0 631.0 134.0 74.0 93.0 72.0 128.0 138.0 185.0 31.0 35.0 26.0 150.0 269.0 66.0 76.0 118.0 155.0 141.0 106.0 22.0 74.0 91.0 157.0 189.0 171.0 79.0 85.0 32.0 151.0 48.0 82.0 155.0 47.0 84.0 96.0 138.0 79.0 426.0 154.0 369.0 73.0 134.0 109.0 216.0 195.0 131.0 85.0 137.0 152.0 92.0 23.0 105.0 129.0 95.0 559.0 121.0 138.0 67.0 275.0 69.0 92.0 94.0 52.0 117.0 50.0 96.0 31.0 65.0 5.0 109.0 60.0 587.0 102.0 104.0 38.0 98.0 2.0 22.0
2021-11-07 07:39:17,942 - mmdet - INFO - pseudo mining: 597.0 2.0 46.0 2.0 8.0 6.0 4.0 0.0 1.0 10.0 2.0 13.0 0.0 0.0 3.0 6.0 2.0 9.0 14.0 3.0 19.0 1.0 24.0 27.0 0.0 4.0 0.0 3.0 0.0 7.0 0.0 0.0 26.0 16.0 2.0 2.0 1.0 0.0 4.0 17.0 2.0 11.0 0.0 0.0 0.0 2.0 1.0 0.0 0.0 3.0 8.0 1.0 0.0 6.0 3.0 0.0 0.0 0.0 4.0 0.0 1.0 11.0 20.0 3.0 9.0 1.0 2.0 1.0 0.0 0.0 0.0 3.0 2.0 0.0 44.0 0.0 0.0 1.0 0.0 0.0
2021-11-07 07:39:19,689 - mmdet - INFO - Iter [500/40000] lr: 1.996e-02, eta: 20:23:37, time: 1.705, data_time: 0.026, memory: 25141, loss_rpn_cls: 0.0508, loss_rpn_bbox: 0.0609, loss_cls: 0.2935, acc: 90.8668, loss_bbox: 0.3126, loss_rpn_cls_unlabeled: 0.1158, loss_rpn_bbox_unlabeled: 0.1092, loss_cls_unlabeled: 0.2253, acc_unlabeled: 90.7020, loss_bbox_unlabeled: 0.1748, losses_cls_ig_unlabeled: 0.1864, pseudo_num: 1.3914, pseudo_num_ig: 5.5500, pseudo_num_mining: 0.4917, pseudo_num(acc): 0.8470, pseudo_num ig(acc): 0.4598, loss: 1.5293
2021-11-07 07:40:45,308 - mmdet - INFO - Iter [550/40000] lr: 2.000e-02, eta: 20:13:27, time: 1.714, data_time: 0.035, memory: 25141, loss_rpn_cls: 0.0532, loss_rpn_bbox: 0.0606, loss_cls: 0.2920, acc: 90.9591, loss_bbox: 0.3126, loss_rpn_cls_unlabeled: 0.1258, loss_rpn_bbox_unlabeled: 0.1175, loss_cls_unlabeled: 0.2253, acc_unlabeled: 90.5449, loss_bbox_unlabeled: 0.1756, losses_cls_ig_unlabeled: 0.1959, pseudo_num: 1.3818, pseudo_num_ig: 5.5510, pseudo_num_mining: 0.4940, pseudo_num(acc): 0.8451, pseudo_num ig(acc): 0.4591, loss: 1.5585
2021-11-07 07:42:09,047 - mmdet - INFO - Iter [600/40000] lr: 2.000e-02, eta: 20:02:40, time: 1.677, data_time: 0.030, memory: 25141, loss_rpn_cls: 0.0529, loss_rpn_bbox: 0.0597, loss_cls: 0.2985, acc: 90.8079, loss_bbox: 0.3139, loss_rpn_cls_unlabeled: 0.1145, loss_rpn_bbox_unlabeled: 0.1073, loss_cls_unlabeled: 0.2180, acc_unlabeled: 90.6715, loss_bbox_unlabeled: 0.1705, losses_cls_ig_unlabeled: 0.1923, pseudo_num: 1.3761, pseudo_num_ig: 5.5796, pseudo_num_mining: 0.4975, pseudo_num(acc): 0.8443, pseudo_num ig(acc): 0.4601, loss: 1.5276
2021-11-07 07:43:32,648 - mmdet - INFO - Iter [650/40000] lr: 2.000e-02, eta: 19:53:07, time: 1.672, data_time: 0.027, memory: 25141, loss_rpn_cls: 0.0547, loss_rpn_bbox: 0.0597, loss_cls: 0.3005, acc: 90.7094, loss_bbox: 0.3119, loss_rpn_cls_unlabeled: 0.1210, loss_rpn_bbox_unlabeled: 0.1090, loss_cls_unlabeled: 0.2178, acc_unlabeled: 90.8105, loss_bbox_unlabeled: 0.1643, losses_cls_ig_unlabeled: 0.1917, pseudo_num: 1.3683, pseudo_num_ig: 5.5845, pseudo_num_mining: 0.5008, pseudo_num(acc): 0.8443, pseudo_num ig(acc): 0.4602, loss: 1.5306
2021-11-07 07:44:56,848 - mmdet - INFO - Iter [700/40000] lr: 2.000e-02, eta: 19:45:10, time: 1.682, data_time: 0.029, memory: 25141, loss_rpn_cls: 0.0551, loss_rpn_bbox: 0.0596, loss_cls: 0.2787, acc: 91.2561, loss_bbox: 0.3021, loss_rpn_cls_unlabeled: 0.1163, loss_rpn_bbox_unlabeled: 0.1103, loss_cls_unlabeled: 0.2152, acc_unlabeled: 90.6169, loss_bbox_unlabeled: 0.1619, losses_cls_ig_unlabeled: 0.1952, pseudo_num: 1.3638, pseudo_num_ig: 5.5993, pseudo_num_mining: 0.5043, pseudo_num(acc): 0.8435, pseudo_num ig(acc): 0.4597, loss: 1.4944
2021-11-07 07:46:23,134 - mmdet - INFO - Iter [750/40000] lr: 2.000e-02, eta: 19:40:05, time: 1.727, data_time: 0.028, memory: 25141, loss_rpn_cls: 0.0539, loss_rpn_bbox: 0.0609, loss_cls: 0.3005, acc: 90.7931, loss_bbox: 0.3113, loss_rpn_cls_unlabeled: 0.1161, loss_rpn_bbox_unlabeled: 0.1098, loss_cls_unlabeled: 0.2183, acc_unlabeled: 90.8044, loss_bbox_unlabeled: 0.1668, losses_cls_ig_unlabeled: 0.1897, pseudo_num: 1.3573, pseudo_num_ig: 5.6104, pseudo_num_mining: 0.5079, pseudo_num(acc): 0.8430, pseudo_num ig(acc): 0.4598, loss: 1.5272
2021-11-07 07:47:47,998 - mmdet - INFO - Iter [800/40000] lr: 2.000e-02, eta: 19:34:14, time: 1.698, data_time: 0.026, memory: 25141, loss_rpn_cls: 0.0542, loss_rpn_bbox: 0.0592, loss_cls: 0.2928, acc: 90.8533, loss_bbox: 0.3047, loss_rpn_cls_unlabeled: 0.1190, loss_rpn_bbox_unlabeled: 0.1082, loss_cls_unlabeled: 0.2149, acc_unlabeled: 90.5940, loss_bbox_unlabeled: 0.1668, losses_cls_ig_unlabeled: 0.1967, pseudo_num: 1.3527, pseudo_num_ig: 5.6213, pseudo_num_mining: 0.5121, pseudo_num(acc): 0.8422, pseudo_num ig(acc): 0.4601, loss: 1.5165
2021-11-07 07:49:13,000 - mmdet - INFO - Iter [850/40000] lr: 2.000e-02, eta: 19:29:02, time: 1.701, data_time: 0.027, memory: 25141, loss_rpn_cls: 0.0519, loss_rpn_bbox: 0.0589, loss_cls: 0.2827, acc: 91.1581, loss_bbox: 0.3049, loss_rpn_cls_unlabeled: 0.1183, loss_rpn_bbox_unlabeled: 0.1074, loss_cls_unlabeled: 0.2111, acc_unlabeled: 90.7483, loss_bbox_unlabeled: 0.1654, losses_cls_ig_unlabeled: 0.1932, pseudo_num: 1.3488, pseudo_num_ig: 5.6410, pseudo_num_mining: 0.5149, pseudo_num(acc): 0.8415, pseudo_num ig(acc): 0.4590, loss: 1.4938
2021-11-07 07:50:37,175 - mmdet - INFO - Iter [900/40000] lr: 2.000e-02, eta: 19:23:36, time: 1.683, data_time: 0.024, memory: 25141, loss_rpn_cls: 0.0515, loss_rpn_bbox: 0.0576, loss_cls: 0.2882, acc: 91.0494, loss_bbox: 0.3046, loss_rpn_cls_unlabeled: 0.1071, loss_rpn_bbox_unlabeled: 0.1066, loss_cls_unlabeled: 0.2159, acc_unlabeled: 90.6288, loss_bbox_unlabeled: 0.1745, losses_cls_ig_unlabeled: 0.1885, pseudo_num: 1.3482, pseudo_num_ig: 5.6460, pseudo_num_mining: 0.5189, pseudo_num(acc): 0.8399, pseudo_num ig(acc): 0.4582, loss: 1.4945
2021-11-07 07:52:01,808 - mmdet - INFO - Iter [950/40000] lr: 2.000e-02, eta: 19:18:51, time: 1.691, data_time: 0.034, memory: 25141, loss_rpn_cls: 0.0525, loss_rpn_bbox: 0.0586, loss_cls: 0.2902, acc: 90.9569, loss_bbox: 0.3105, loss_rpn_cls_unlabeled: 0.1192, loss_rpn_bbox_unlabeled: 0.1069, loss_cls_unlabeled: 0.2101, acc_unlabeled: 90.7516, loss_bbox_unlabeled: 0.1688, losses_cls_ig_unlabeled: 0.1907, pseudo_num: 1.3448, pseudo_num_ig: 5.6451, pseudo_num_mining: 0.5220, pseudo_num(acc): 0.8400, pseudo_num ig(acc): 0.4585, loss: 1.5075
2021-11-07 07:53:25,511 - mmdet - INFO - pseudo pos: 0.99(1482.0-person) 0.97(36.0-bicycle) 0.90(261.0-car) 0.94(52.0-motorcycle) 1.00(20.0-airplane) 0.98(55.0-bus) 0.91(35.0-train) 0.80(61.0-truck) 0.48(97.0-boat) 0.87(98.0-traffic light) 1.00(14.0-fire hydrant) 0.90(10.0-stop sign) 0.89(9.0-parking meter) 0.71(62.0-bench) 0.90(79.0-bird) 0.93(28.0-cat) 0.95(38.0-dog) 0.98(44.0-horse) 0.93(92.0-sheep) 0.90(63.0-cow) 1.00(35.0-elephant) 1.00(9.0-bear) 1.00(18.0-zebra) 0.95(22.0-giraffe) 0.47(72.0-backpack) 0.82(85.0-umbrella) 0.45(73.0-handbag) 0.91(22.0-tie) 0.66(41.0-suitcase) 0.94(17.0-frisbee) 0.49(70.0-skis) 0.75(12.0-snowboard) 1.00(27.0-sports ball) 0.97(39.0-kite) 0.85(26.0-baseball bat) 1.00(29.0-baseball glove) 1.00(45.0-skateboard) 0.79(67.0-surfboard) 0.94(32.0-tennis racket) 0.82(161.0-bottle) 0.89(37.0-wine glass) 0.85(158.0-cup) 0.67(30.0-fork) 0.29(45.0-knife) 0.32(79.0-spoon) 0.87(91.0-bowl) 0.61(31.0-banana) 0.56(45.0-apple) 0.68(38.0-sandwich) 0.46(46.0-orange) 0.80(30.0-broccoli) 0.82(11.0-carrot) 0.67(6.0-hot dog) 0.94(52.0-pizza) 0.82(85.0-donut) 0.85(20.0-cake) 0.70(260.0-chair) 0.70(99.0-couch) 0.69(49.0-potted plant) 0.96(24.0-bed) 0.67(138.0-dining table) 0.79(14.0-toilet) 1.00(23.0-tv) 1.00(28.0-laptop) 1.00(8.0-mouse) 0.53(58.0-remote) 0.87(16.0-keyboard) 0.81(48.0-cell phone) 0.91(11.0-microwave) 0.85(26.0-oven) 0.00(0.0-toaster) 0.84(38.0-sink) 0.92(13.0-refrigerator) 0.31(104.0-book) 0.95(20.0-clock) 0.86(58.0-vase) 0.50(2.0-scissors) 0.91(43.0-teddy bear) 0.00(0.0-hair drier) 0.00(5.0-toothbrush)
2021-11-07 07:53:25,511 - mmdet - INFO - pseudo ig: 0.66(6384.0-person) 0.42(85.0-bicycle) 0.49(1029.0-car) 0.53(172.0-motorcycle) 0.81(79.0-airplane) 0.47(127.0-bus) 0.63(108.0-train) 0.42(218.0-truck) 0.26(334.0-boat) 0.37(353.0-traffic light) 0.64(45.0-fire hydrant) 0.42(71.0-stop sign) 0.52(21.0-parking meter) 0.19(255.0-bench) 0.40(321.0-bird) 0.76(103.0-cat) 0.63(133.0-dog) 0.62(153.0-horse) 0.40(332.0-sheep) 0.41(321.0-cow) 0.70(174.0-elephant) 0.70(30.0-bear) 0.80(124.0-zebra) 0.74(166.0-giraffe) 0.17(276.0-backpack) 0.37(295.0-umbrella) 0.17(299.0-handbag) 0.42(99.0-tie) 0.29(126.0-suitcase) 0.56(57.0-frisbee) 0.31(240.0-skis) 0.45(44.0-snowboard) 0.41(221.0-sports ball) 0.45(249.0-kite) 0.35(125.0-baseball bat) 0.34(130.0-baseball glove) 0.49(133.0-skateboard) 0.32(206.0-surfboard) 0.49(221.0-tennis racket) 0.38(700.0-bottle) 0.39(217.0-wine glass) 0.29(724.0-cup) 0.22(163.0-fork) 0.21(144.0-knife) 0.10(217.0-spoon) 0.42(392.0-bowl) 0.29(230.0-banana) 0.19(302.0-apple) 0.34(95.0-sandwich) 0.22(548.0-orange) 0.41(176.0-broccoli) 0.43(114.0-carrot) 0.44(34.0-hot dog) 0.51(178.0-pizza) 0.21(253.0-donut) 0.49(87.0-cake) 0.28(951.0-chair) 0.27(224.0-couch) 0.38(215.0-potted plant) 0.53(68.0-bed) 0.34(375.0-dining table) 0.81(84.0-toilet) 0.67(139.0-tv) 0.56(176.0-laptop) 0.50(68.0-mouse) 0.24(182.0-remote) 0.42(74.0-keyboard) 0.22(254.0-cell phone) 0.59(46.0-microwave) 0.19(107.0-oven) 0.00(0.0-toaster) 0.36(138.0-sink) 0.44(54.0-refrigerator) 0.18(470.0-book) 0.58(176.0-clock) 0.33(149.0-vase) 0.37(19.0-scissors) 0.50(130.0-teddy bear) 0.00(0.0-hair drier) 0.19(26.0-toothbrush)
2021-11-07 07:53:25,511 - mmdet - INFO - pseudo gt: 8662.0 231.0 1292.0 263.0 142.0 174.0 139.0 307.0 330.0 368.0 68.0 67.0 49.0 352.0 456.0 130.0 205.0 218.0 331.0 271.0 201.0 43.0 144.0 156.0 297.0 390.0 376.0 170.0 150.0 66.0 274.0 96.0 215.0 336.0 108.0 148.0 200.0 236.0 176.0 871.0 297.0 727.0 194.0 255.0 210.0 459.0 302.0 245.0 163.0 262.0 255.0 278.0 45.0 225.0 247.0 223.0 1163.0 227.0 294.0 131.0 571.0 130.0 191.0 194.0 89.0 220.0 88.0 205.0 67.0 107.0 12.0 212.0 95.0 990.0 201.0 254.0 94.0 166.0 7.0 57.0
2021-11-07 07:53:25,511 - mmdet - INFO - pseudo mining: 1212.0 4.0 102.0 4.0 14.0 11.0 7.0 1.0 2.0 26.0 6.0 26.0 0.0 0.0 4.0 10.0 5.0 12.0 31.0 6.0 40.0 3.0 61.0 62.0 0.0 8.0 0.0 5.0 0.0 14.0 0.0 0.0 53.0 38.0 3.0 7.0 5.0 0.0 26.0 29.0 6.0 30.0 0.0 0.0 0.0 12.0 1.0 0.0 0.0 4.0 12.0 4.0 0.0 10.0 9.0 2.0 1.0 0.0 6.0 0.0 1.0 23.0 38.0 15.0 20.0 1.0 3.0 3.0 1.0 0.0 0.0 6.0 2.0 0.0 87.0 2.0 0.0 2.0 0.0 0.0
2021-11-07 07:54:53,914 - mmdet - INFO - current percent: 0.2
2021-11-07 07:54:53,914 - mmdet - INFO - update score thr (positive): (0.99-person) (0.94-bicycle) (0.96-car) (0.98-motorcycle) (0.98-airplane) (0.99-bus) (0.99-train) (0.86-truck) (0.87-boat) (0.94-traffic light) (1.00-fire hydrant) (1.00-stop sign) (0.82-parking meter) (0.85-bench) (0.95-bird) (0.97-cat) (0.97-dog) (0.98-horse) (0.97-sheep) (0.93-cow) (0.99-elephant) (0.95-bear) (0.99-zebra) (0.99-giraffe) (0.79-backpack) (0.93-umbrella) (0.53-handbag) (0.91-tie) (0.91-suitcase) (0.98-frisbee) (0.88-skis) (0.36-snowboard) (0.99-sports ball) (0.96-kite) (0.93-baseball bat) (0.98-baseball glove) (0.97-skateboard) (0.94-surfboard) (0.99-tennis racket) (0.95-bottle) (0.94-wine glass) (0.94-cup) (0.71-fork) (0.58-knife) (0.69-spoon) (0.93-bowl) (0.84-banana) (0.87-apple) (0.92-sandwich) (0.83-orange) (0.93-broccoli) (0.59-carrot) (0.61-hot dog) (0.97-pizza) (0.94-donut) (0.86-cake) (0.83-chair) (0.90-couch) (0.94-potted plant) (0.85-bed) (0.92-dining table) (0.99-toilet) (0.98-tv) (0.98-laptop) (0.96-mouse) (0.81-remote) (0.95-keyboard) (0.91-cell phone) (0.93-microwave) (0.94-oven) (0.05-toaster) (0.97-sink) (0.85-refrigerator) (0.70-book) (0.99-clock) (0.95-vase) (0.53-scissors) (0.98-teddy bear) (0.05-hair drier) (0.15-toothbrush)
2021-11-07 07:54:53,915 - mmdet - INFO - update score thr (ignore): (0.44-person) (0.47-bicycle) (0.46-car) (0.57-motorcycle) (0.55-airplane) (0.61-bus) (0.57-train) (0.39-truck) (0.38-boat) (0.43-traffic light) (0.54-fire hydrant) (0.83-stop sign) (0.21-parking meter) (0.37-bench) (0.30-bird) (0.49-cat) (0.57-dog) (0.45-horse) (0.41-sheep) (0.47-cow) (0.50-elephant) (0.48-bear) (0.49-zebra) (0.69-giraffe) (0.41-backpack) (0.34-umbrella) (0.23-handbag) (0.45-tie) (0.49-suitcase) (0.51-frisbee) (0.48-skis) (0.14-snowboard) (0.44-sports ball) (0.45-kite) (0.38-baseball bat) (0.52-baseball glove) (0.44-skateboard) (0.41-surfboard) (0.44-tennis racket) (0.46-bottle) (0.30-wine glass) (0.38-cup) (0.27-fork) (0.27-knife) (0.32-spoon) (0.40-bowl) (0.33-banana) (0.42-apple) (0.56-sandwich) (0.44-orange) (0.59-broccoli) (0.27-carrot) (0.23-hot dog) (0.51-pizza) (0.54-donut) (0.25-cake) (0.34-chair) (0.57-couch) (0.54-potted plant) (0.36-bed) (0.50-dining table) (0.75-toilet) (0.62-tv) (0.48-laptop) (0.52-mouse) (0.29-remote) (0.52-keyboard) (0.49-cell phone) (0.44-microwave) (0.55-oven) (0.05-toaster) (0.52-sink) (0.40-refrigerator) (0.33-book) (0.81-clock) (0.44-vase) (0.17-scissors) (0.67-teddy bear) (0.05-hair drier) (0.07-toothbrush)
2021-11-07 07:54:54,173 - mmdet - INFO - Exp name: labelmatch_0.9_1_5_8.py
2021-11-07 07:54:54,174 - mmdet - INFO - Iter [1000/40000] lr: 2.000e-02, eta: 19:14:58, time: 1.707, data_time: 0.028, memory: 25214, loss_rpn_cls: 0.0509, loss_rpn_bbox: 0.0589, loss_cls: 0.2810, acc: 91.1620, loss_bbox: 0.3026, loss_rpn_cls_unlabeled: 0.1139, loss_rpn_bbox_unlabeled: 0.1097, loss_cls_unlabeled: 0.2175, acc_unlabeled: 90.6875, loss_bbox_unlabeled: 0.1795, losses_cls_ig_unlabeled: 0.1914, pseudo_num: 1.3437, pseudo_num_ig: 5.6504, pseudo_num_mining: 0.5242, pseudo_num(acc): 0.8388, pseudo_num ig(acc): 0.4584, loss: 1.5053
2021-11-07 07:56:16,870 - mmdet - INFO - Iter [1050/40000] lr: 2.000e-02, eta: 20:03:36, time: 3.398, data_time: 1.769, memory: 25887, loss_rpn_cls: 0.0490, loss_rpn_bbox: 0.0615, loss_cls: 0.2945, acc: 90.6537, loss_bbox: 0.3138, loss_rpn_cls_unlabeled: 0.1141, loss_rpn_bbox_unlabeled: 0.1072, loss_cls_unlabeled: 0.2128, acc_unlabeled: 90.4979, loss_bbox_unlabeled: 0.1745, losses_cls_ig_unlabeled: 0.1876, pseudo_num: 1.3490, pseudo_num_ig: 5.6564, pseudo_num_mining: 0.5233, pseudo_num(acc): 0.8384, pseudo_num ig(acc): 0.4578, loss: 1.5150
2021-11-07 07:57:43,325 - mmdet - INFO - Iter [1100/40000] lr: 2.000e-02, eta: 19:58:18, time: 1.727, data_time: 0.031, memory: 25887, loss_rpn_cls: 0.0505, loss_rpn_bbox: 0.0572, loss_cls: 0.2501, acc: 91.9513, loss_bbox: 0.2856, loss_rpn_cls_unlabeled: 0.1107, loss_rpn_bbox_unlabeled: 0.1059, loss_cls_unlabeled: 0.1908, acc_unlabeled: 91.5455, loss_bbox_unlabeled: 0.1611, losses_cls_ig_unlabeled: 0.1708, pseudo_num: 1.3560, pseudo_num_ig: 5.6533, pseudo_num_mining: 0.5198, pseudo_num(acc): 0.8395, pseudo_num ig(acc): 0.4568, loss: 1.3828
2021-11-07 07:59:11,645 - mmdet - INFO - Iter [1150/40000] lr: 2.000e-02, eta: 19:54:27, time: 1.766, data_time: 0.034, memory: 25887, loss_rpn_cls: 0.0498, loss_rpn_bbox: 0.0629, loss_cls: 0.2615, acc: 91.6426, loss_bbox: 0.2963, loss_rpn_cls_unlabeled: 0.1116, loss_rpn_bbox_unlabeled: 0.1117, loss_cls_unlabeled: 0.1975, acc_unlabeled: 91.5347, loss_bbox_unlabeled: 0.1721, losses_cls_ig_unlabeled: 0.1671, pseudo_num: 1.3636, pseudo_num_ig: 5.6444, pseudo_num_mining: 0.5179, pseudo_num(acc): 0.8399, pseudo_num ig(acc): 0.4565, loss: 1.4306
2021-11-07 08:00:36,200 - mmdet - INFO - Iter [1200/40000] lr: 2.000e-02, eta: 19:48:42, time: 1.688, data_time: 0.027, memory: 25887, loss_rpn_cls: 0.0527, loss_rpn_bbox: 0.0579, loss_cls: 0.2754, acc: 91.3512, loss_bbox: 0.2987, loss_rpn_cls_unlabeled: 0.1111, loss_rpn_bbox_unlabeled: 0.1067, loss_cls_unlabeled: 0.2060, acc_unlabeled: 91.0701, loss_bbox_unlabeled: 0.1772, losses_cls_ig_unlabeled: 0.1767, pseudo_num: 1.3712, pseudo_num_ig: 5.6363, pseudo_num_mining: 0.5149, pseudo_num(acc): 0.8398, pseudo_num ig(acc): 0.4560, loss: 1.4624
2021-11-07 08:01:59,423 - mmdet - INFO - Iter [1250/40000] lr: 2.000e-02, eta: 19:42:45, time: 1.667, data_time: 0.035, memory: 25887, loss_rpn_cls: 0.0478, loss_rpn_bbox: 0.0561, loss_cls: 0.2849, acc: 91.0820, loss_bbox: 0.3067, loss_rpn_cls_unlabeled: 0.1107, loss_rpn_bbox_unlabeled: 0.1073, loss_cls_unlabeled: 0.2138, acc_unlabeled: 90.8318, loss_bbox_unlabeled: 0.1799, losses_cls_ig_unlabeled: 0.1812, pseudo_num: 1.3770, pseudo_num_ig: 5.6246, pseudo_num_mining: 0.5104, pseudo_num(acc): 0.8398, pseudo_num ig(acc): 0.4560, loss: 1.4885
2021-11-07 08:03:23,620 - mmdet - INFO - Iter [1300/40000] lr: 2.000e-02, eta: 19:37:36, time: 1.686, data_time: 0.028, memory: 25887, loss_rpn_cls: 0.0496, loss_rpn_bbox: 0.0584, loss_cls: 0.2825, acc: 91.1785, loss_bbox: 0.3018, loss_rpn_cls_unlabeled: 0.1075, loss_rpn_bbox_unlabeled: 0.1000, loss_cls_unlabeled: 0.2047, acc_unlabeled: 91.1588, loss_bbox_unlabeled: 0.1763, losses_cls_ig_unlabeled: 0.1760, pseudo_num: 1.3831, pseudo_num_ig: 5.6060, pseudo_num_mining: 0.5079, pseudo_num(acc): 0.8402, pseudo_num ig(acc): 0.4560, loss: 1.4567
2021-11-07 08:04:46,566 - mmdet - INFO - Iter [1350/40000] lr: 2.000e-02, eta: 19:32:05, time: 1.658, data_time: 0.028, memory: 25887, loss_rpn_cls: 0.0487, loss_rpn_bbox: 0.0565, loss_cls: 0.2744, acc: 91.3986, loss_bbox: 0.2948, loss_rpn_cls_unlabeled: 0.1098, loss_rpn_bbox_unlabeled: 0.1055, loss_cls_unlabeled: 0.2104, acc_unlabeled: 90.7178, loss_bbox_unlabeled: 0.1781, losses_cls_ig_unlabeled: 0.1843, pseudo_num: 1.3876, pseudo_num_ig: 5.5945, pseudo_num_mining: 0.5050, pseudo_num(acc): 0.8403, pseudo_num ig(acc): 0.4558, loss: 1.4626
2021-11-07 08:06:10,834 - mmdet - INFO - Iter [1400/40000] lr: 2.000e-02, eta: 19:27:23, time: 1.681, data_time: 0.028, memory: 25887, loss_rpn_cls: 0.0503, loss_rpn_bbox: 0.0584, loss_cls: 0.2907, acc: 90.9009, loss_bbox: 0.3105, loss_rpn_cls_unlabeled: 0.1108, loss_rpn_bbox_unlabeled: 0.1089, loss_cls_unlabeled: 0.2240, acc_unlabeled: 90.6946, loss_bbox_unlabeled: 0.1894, losses_cls_ig_unlabeled: 0.1817, pseudo_num: 1.3962, pseudo_num_ig: 5.5954, pseudo_num_mining: 0.5021, pseudo_num(acc): 0.8393, pseudo_num ig(acc): 0.4552, loss: 1.5247
2021-11-07 08:07:37,362 - mmdet - INFO - Iter [1450/40000] lr: 2.000e-02, eta: 19:24:03, time: 1.732, data_time: 0.032, memory: 25887, loss_rpn_cls: 0.0489, loss_rpn_bbox: 0.0569, loss_cls: 0.2821, acc: 91.1486, loss_bbox: 0.3051, loss_rpn_cls_unlabeled: 0.1137, loss_rpn_bbox_unlabeled: 0.1149, loss_cls_unlabeled: 0.2203, acc_unlabeled: 90.6696, loss_bbox_unlabeled: 0.1906, losses_cls_ig_unlabeled: 0.1805, pseudo_num: 1.4056, pseudo_num_ig: 5.5948, pseudo_num_mining: 0.5007, pseudo_num(acc): 0.8388, pseudo_num ig(acc): 0.4547, loss: 1.5129
2021-11-07 08:09:02,910 - mmdet - INFO - pseudo pos: 0.98(2514.0-person) 0.95(62.0-bicycle) 0.91(435.0-car) 0.92(66.0-motorcycle) 0.96(47.0-airplane) 0.99(77.0-bus) 0.93(57.0-train) 0.74(97.0-truck) 0.58(137.0-boat) 0.88(178.0-traffic light) 1.00(17.0-fire hydrant) 0.94(16.0-stop sign) 0.86(14.0-parking meter) 0.62(117.0-bench) 0.90(115.0-bird) 0.93(43.0-cat) 0.97(60.0-dog) 0.95(57.0-horse) 0.94(111.0-sheep) 0.93(83.0-cow) 1.00(60.0-elephant) 1.00(13.0-bear) 1.00(36.0-zebra) 0.97(35.0-giraffe) 0.47(111.0-backpack) 0.83(115.0-umbrella) 0.46(122.0-handbag) 0.88(41.0-tie) 0.68(57.0-suitcase) 0.96(23.0-frisbee) 0.49(91.0-skis) 0.75(20.0-snowboard) 1.00(46.0-sports ball) 0.91(69.0-kite) 0.85(40.0-baseball bat) 0.97(37.0-baseball glove) 0.99(71.0-skateboard) 0.83(92.0-surfboard) 0.96(45.0-tennis racket) 0.84(231.0-bottle) 0.92(79.0-wine glass) 0.88(234.0-cup) 0.63(46.0-fork) 0.29(62.0-knife) 0.31(93.0-spoon) 0.81(153.0-bowl) 0.63(73.0-banana) 0.52(58.0-apple) 0.77(53.0-sandwich) 0.58(60.0-orange) 0.71(66.0-broccoli) 0.51(61.0-carrot) 0.60(15.0-hot dog) 0.93(70.0-pizza) 0.84(105.0-donut) 0.84(38.0-cake) 0.69(349.0-chair) 0.72(110.0-couch) 0.68(71.0-potted plant) 0.90(40.0-bed) 0.67(224.0-dining table) 0.88(26.0-toilet) 0.98(46.0-tv) 1.00(46.0-laptop) 1.00(17.0-mouse) 0.57(72.0-remote) 0.88(26.0-keyboard) 0.81(69.0-cell phone) 0.94(17.0-microwave) 0.87(40.0-oven) 0.00(0.0-toaster) 0.83(53.0-sink) 0.76(37.0-refrigerator) 0.33(161.0-book) 0.98(42.0-clock) 0.88(78.0-vase) 0.50(8.0-scissors) 0.92(53.0-teddy bear) 0.00(0.0-hair drier) 0.20(41.0-toothbrush)
2021-11-07 08:09:02,911 - mmdet - INFO - pseudo ig: 0.64(9656.0-person) 0.42(151.0-bicycle) 0.49(1595.0-car) 0.55(292.0-motorcycle) 0.62(141.0-airplane) 0.54(189.0-bus) 0.63(153.0-train) 0.42(356.0-truck) 0.29(482.0-boat) 0.36(565.0-traffic light) 0.67(64.0-fire hydrant) 0.46(96.0-stop sign) 0.36(33.0-parking meter) 0.17(379.0-bench) 0.36(497.0-bird) 0.73(166.0-cat) 0.67(197.0-dog) 0.58(214.0-horse) 0.40(440.0-sheep) 0.44(401.0-cow) 0.71(256.0-elephant) 0.65(43.0-bear) 0.76(206.0-zebra) 0.79(226.0-giraffe) 0.19(392.0-backpack) 0.36(443.0-umbrella) 0.17(496.0-handbag) 0.37(160.0-tie) 0.34(191.0-suitcase) 0.53(96.0-frisbee) 0.32(320.0-skis) 0.32(82.0-snowboard) 0.42(281.0-sports ball) 0.43(362.0-kite) 0.32(180.0-baseball bat) 0.38(178.0-baseball glove) 0.49(196.0-skateboard) 0.34(307.0-surfboard) 0.53(277.0-tennis racket) 0.38(997.0-bottle) 0.39(345.0-wine glass) 0.31(1036.0-cup) 0.23(244.0-fork) 0.17(253.0-knife) 0.12(314.0-spoon) 0.40(622.0-bowl) 0.26(367.0-banana) 0.19(361.0-apple) 0.34(146.0-sandwich) 0.22(621.0-orange) 0.42(273.0-broccoli) 0.30(233.0-carrot) 0.34(70.0-hot dog) 0.50(260.0-pizza) 0.24(347.0-donut) 0.42(167.0-cake) 0.28(1365.0-chair) 0.28(273.0-couch) 0.36(310.0-potted plant) 0.53(124.0-bed) 0.31(602.0-dining table) 0.78(121.0-toilet) 0.60(196.0-tv) 0.56(257.0-laptop) 0.47(94.0-mouse) 0.24(255.0-remote) 0.41(109.0-keyboard) 0.24(332.0-cell phone) 0.49(74.0-microwave) 0.22(144.0-oven) 0.00(0.0-toaster) 0.40(203.0-sink) 0.35(108.0-refrigerator) 0.19(776.0-book) 0.60(242.0-clock) 0.32(232.0-vase) 0.29(31.0-scissors) 0.52(177.0-teddy bear) 0.00(0.0-hair drier) 0.09(85.0-toothbrush)
2021-11-07 08:09:02,911 - mmdet - INFO - pseudo gt: 12916.0 387.0 2032.0 409.0 224.0 293.0 220.0 490.0 508.0 661.0 96.0 99.0 63.0 513.0 643.0 194.0 310.0 285.0 453.0 394.0 306.0 59.0 243.0 250.0 442.0 521.0 590.0 285.0 269.0 102.0 401.0 151.0 317.0 479.0 169.0 229.0 312.0 340.0 253.0 1204.0 454.0 1037.0 284.0 367.0 297.0 702.0 461.0 352.0 219.0 368.0 404.0 393.0 77.0 307.0 363.0 339.0 1680.0 293.0 429.0 205.0 791.0 196.0 265.0 281.0 126.0 295.0 133.0 310.0 91.0 154.0 16.0 299.0 153.0 1300.0 309.0 342.0 110.0 229.0 13.0 79.0
2021-11-07 08:09:02,911 - mmdet - INFO - pseudo mining: 1663.0 4.0 163.0 15.0 16.0 20.0 8.0 1.0 3.0 43.0 13.0 39.0 0.0 0.0 11.0 14.0 10.0 15.0 44.0 9.0 57.0 4.0 82.0 89.0 0.0 11.0 0.0 6.0 1.0 22.0 1.0 0.0 69.0 48.0 6.0 17.0 9.0 5.0 33.0 45.0 7.0 42.0 0.0 0.0 0.0 15.0 2.0 0.0 0.0 4.0 16.0 4.0 0.0 12.0 13.0 2.0 2.0 0.0 10.0 0.0 4.0 36.0 45.0 22.0 25.0 1.0 4.0 6.0 1.0 0.0 0.0 8.0 2.0 0.0 131.0 4.0 0.0 6.0 0.0 0.0
2021-11-07 08:09:04,532 - mmdet - INFO - Iter [1500/40000] lr: 2.000e-02, eta: 19:21:09, time: 1.747, data_time: 0.029, memory: 25887, loss_rpn_cls: 0.0509, loss_rpn_bbox: 0.0576, loss_cls: 0.2852, acc: 91.0208, loss_bbox: 0.3117, loss_rpn_cls_unlabeled: 0.1122, loss_rpn_bbox_unlabeled: 0.1075, loss_cls_unlabeled: 0.2196, acc_unlabeled: 90.7452, loss_bbox_unlabeled: 0.1888, losses_cls_ig_unlabeled: 0.1776, pseudo_num: 1.4154, pseudo_num_ig: 5.5948, pseudo_num_mining: 0.4988, pseudo_num(acc): 0.8381, pseudo_num ig(acc): 0.4539, loss: 1.5112
2021-11-07 08:10:30,177 - mmdet - INFO - Iter [1550/40000] lr: 2.000e-02, eta: 19:17:37, time: 1.711, data_time: 0.036, memory: 25887, loss_rpn_cls: 0.0508, loss_rpn_bbox: 0.0606, loss_cls: 0.2798, acc: 91.0964, loss_bbox: 0.3069, loss_rpn_cls_unlabeled: 0.1146, loss_rpn_bbox_unlabeled: 0.1136, loss_cls_unlabeled: 0.2214, acc_unlabeled: 90.7286, loss_bbox_unlabeled: 0.1902, losses_cls_ig_unlabeled: 0.1784, pseudo_num: 1.4229, pseudo_num_ig: 5.5918, pseudo_num_mining: 0.4972, pseudo_num(acc): 0.8377, pseudo_num ig(acc): 0.4533, loss: 1.5163
2021-11-07 08:11:55,890 - mmdet - INFO - Iter [1600/40000] lr: 2.000e-02, eta: 19:14:18, time: 1.716, data_time: 0.028, memory: 25887, loss_rpn_cls: 0.0493, loss_rpn_bbox: 0.0594, loss_cls: 0.2831, acc: 91.0010, loss_bbox: 0.3104, loss_rpn_cls_unlabeled: 0.1107, loss_rpn_bbox_unlabeled: 0.1066, loss_cls_unlabeled: 0.2279, acc_unlabeled: 90.8553, loss_bbox_unlabeled: 0.1921, losses_cls_ig_unlabeled: 0.1745, pseudo_num: 1.4322, pseudo_num_ig: 5.5910, pseudo_num_mining: 0.4959, pseudo_num(acc): 0.8366, pseudo_num ig(acc): 0.4528, loss: 1.5140
2021-11-07 08:13:21,266 - mmdet - INFO - Iter [1650/40000] lr: 2.000e-02, eta: 19:10:56, time: 1.707, data_time: 0.027, memory: 25887, loss_rpn_cls: 0.0496, loss_rpn_bbox: 0.0589, loss_cls: 0.2784, acc: 91.1884, loss_bbox: 0.3008, loss_rpn_cls_unlabeled: 0.1079, loss_rpn_bbox_unlabeled: 0.1088, loss_cls_unlabeled: 0.2256, acc_unlabeled: 90.7118, loss_bbox_unlabeled: 0.2013, losses_cls_ig_unlabeled: 0.1752, pseudo_num: 1.4404, pseudo_num_ig: 5.5875, pseudo_num_mining: 0.4946, pseudo_num(acc): 0.8357, pseudo_num ig(acc): 0.4524, loss: 1.5066
2021-11-07 08:14:45,435 - mmdet - INFO - Iter [1700/40000] lr: 2.000e-02, eta: 19:07:11, time: 1.681, data_time: 0.025, memory: 25887, loss_rpn_cls: 0.0478, loss_rpn_bbox: 0.0562, loss_cls: 0.2750, acc: 91.2162, loss_bbox: 0.3036, loss_rpn_cls_unlabeled: 0.1091, loss_rpn_bbox_unlabeled: 0.1122, loss_cls_unlabeled: 0.2174, acc_unlabeled: 90.9843, loss_bbox_unlabeled: 0.1953, losses_cls_ig_unlabeled: 0.1724, pseudo_num: 1.4509, pseudo_num_ig: 5.5911, pseudo_num_mining: 0.4941, pseudo_num(acc): 0.8339, pseudo_num ig(acc): 0.4519, loss: 1.4889
2021-11-07 08:16:10,213 - mmdet - INFO - Iter [1750/40000] lr: 2.000e-02, eta: 19:03:51, time: 1.696, data_time: 0.028, memory: 25887, loss_rpn_cls: 0.0491, loss_rpn_bbox: 0.0580, loss_cls: 0.2719, acc: 91.3367, loss_bbox: 0.2984, loss_rpn_cls_unlabeled: 0.1110, loss_rpn_bbox_unlabeled: 0.1108, loss_cls_unlabeled: 0.2247, acc_unlabeled: 90.7927, loss_bbox_unlabeled: 0.1899, losses_cls_ig_unlabeled: 0.1719, pseudo_num: 1.4603, pseudo_num_ig: 5.5918, pseudo_num_mining: 0.4931, pseudo_num(acc): 0.8320, pseudo_num ig(acc): 0.4513, loss: 1.4858
2021-11-07 08:17:36,146 - mmdet - INFO - Iter [1800/40000] lr: 2.000e-02, eta: 19:01:03, time: 1.720, data_time: 0.029, memory: 25887, loss_rpn_cls: 0.0510, loss_rpn_bbox: 0.0571, loss_cls: 0.2740, acc: 91.2727, loss_bbox: 0.3024, loss_rpn_cls_unlabeled: 0.1223, loss_rpn_bbox_unlabeled: 0.1155, loss_cls_unlabeled: 0.2360, acc_unlabeled: 90.5905, loss_bbox_unlabeled: 0.2036, losses_cls_ig_unlabeled: 0.1727, pseudo_num: 1.4684, pseudo_num_ig: 5.5946, pseudo_num_mining: 0.4924, pseudo_num(acc): 0.8299, pseudo_num ig(acc): 0.4503, loss: 1.5346
2021-11-07 08:19:00,812 - mmdet - INFO - Iter [1850/40000] lr: 2.000e-02, eta: 18:57:51, time: 1.693, data_time: 0.026, memory: 25887, loss_rpn_cls: 0.0488, loss_rpn_bbox: 0.0602, loss_cls: 0.2843, acc: 91.0302, loss_bbox: 0.3090, loss_rpn_cls_unlabeled: 0.1154, loss_rpn_bbox_unlabeled: 0.1105, loss_cls_unlabeled: 0.2288, acc_unlabeled: 90.6296, loss_bbox_unlabeled: 0.2003, losses_cls_ig_unlabeled: 0.1731, pseudo_num: 1.4804, pseudo_num_ig: 5.5967, pseudo_num_mining: 0.4913, pseudo_num(acc): 0.8273, pseudo_num ig(acc): 0.4495, loss: 1.5305
2021-11-07 08:20:25,015 - mmdet - INFO - Iter [1900/40000] lr: 2.000e-02, eta: 18:54:35, time: 1.683, data_time: 0.028, memory: 25887, loss_rpn_cls: 0.0488, loss_rpn_bbox: 0.0598, loss_cls: 0.2832, acc: 91.1180, loss_bbox: 0.3096, loss_rpn_cls_unlabeled: 0.1280, loss_rpn_bbox_unlabeled: 0.1236, loss_cls_unlabeled: 0.2568, acc_unlabeled: 90.1644, loss_bbox_unlabeled: 0.2191, losses_cls_ig_unlabeled: 0.1798, pseudo_num: 1.4911, pseudo_num_ig: 5.6019, pseudo_num_mining: 0.4907, pseudo_num(acc): 0.8243, pseudo_num ig(acc): 0.4487, loss: 1.6086
2021-11-07 08:21:50,935 - mmdet - INFO - Iter [1950/40000] lr: 2.000e-02, eta: 18:51:59, time: 1.718, data_time: 0.028, memory: 25887, loss_rpn_cls: 0.0515, loss_rpn_bbox: 0.0597, loss_cls: 0.2815, acc: 91.1669, loss_bbox: 0.3025, loss_rpn_cls_unlabeled: 0.1211, loss_rpn_bbox_unlabeled: 0.1151, loss_cls_unlabeled: 0.2414, acc_unlabeled: 90.6007, loss_bbox_unlabeled: 0.2112, losses_cls_ig_unlabeled: 0.1711, pseudo_num: 1.5032, pseudo_num_ig: 5.6090, pseudo_num_mining: 0.4900, pseudo_num(acc): 0.8207, pseudo_num ig(acc): 0.4478, loss: 1.5551
2021-11-07 08:23:15,463 - mmdet - INFO - pseudo pos: 0.98(3660.0-person) 0.95(78.0-bicycle) 0.91(579.0-car) 0.94(85.0-motorcycle) 0.97(75.0-airplane) 0.99(93.0-bus) 0.94(71.0-train) 0.70(145.0-truck) 0.61(195.0-boat) 0.88(236.0-traffic light) 1.00(29.0-fire hydrant) 0.96(26.0-stop sign) 0.90(21.0-parking meter) 0.61(157.0-bench) 0.91(151.0-bird) 0.94(66.0-cat) 0.97(69.0-dog) 0.96(77.0-horse) 0.94(161.0-sheep) 0.94(113.0-cow) 1.00(84.0-elephant) 1.00(22.0-bear) 0.95(43.0-zebra) 0.98(58.0-giraffe) 0.45(129.0-backpack) 0.81(162.0-umbrella) 0.38(210.0-handbag) 0.90(69.0-tie) 0.71(72.0-suitcase) 0.96(28.0-frisbee) 0.49(108.0-skis) 0.61(36.0-snowboard) 0.98(66.0-sports ball) 0.92(96.0-kite) 0.84(50.0-baseball bat) 0.96(47.0-baseball glove) 0.98(99.0-skateboard) 0.82(115.0-surfboard) 0.95(63.0-tennis racket) 0.85(333.0-bottle) 0.92(103.0-wine glass) 0.87(310.0-cup) 0.60(62.0-fork) 0.35(94.0-knife) 0.32(114.0-spoon) 0.83(232.0-bowl) 0.65(103.0-banana) 0.48(73.0-apple) 0.78(67.0-sandwich) 0.57(74.0-orange) 0.71(100.0-broccoli) 0.37(164.0-carrot) 0.56(32.0-hot dog) 0.94(101.0-pizza) 0.80(125.0-donut) 0.84(50.0-cake) 0.69(493.0-chair) 0.73(132.0-couch) 0.73(103.0-potted plant) 0.90(60.0-bed) 0.67(306.0-dining table) 0.85(41.0-toilet) 0.94(68.0-tv) 1.00(62.0-laptop) 0.97(30.0-mouse) 0.62(95.0-remote) 0.89(38.0-keyboard) 0.81(88.0-cell phone) 0.95(19.0-microwave) 0.84(58.0-oven) 0.00(0.0-toaster) 0.77(79.0-sink) 0.76(54.0-refrigerator) 0.32(265.0-book) 0.98(48.0-clock) 0.88(100.0-vase) 0.40(15.0-scissors) 0.94(69.0-teddy bear) 0.00(0.0-hair drier) 0.06(336.0-toothbrush)
2021-11-07 08:23:15,463 - mmdet - INFO - pseudo ig: 0.63(13004.0-person) 0.43(223.0-bicycle) 0.49(2150.0-car) 0.60(396.0-motorcycle) 0.61(195.0-airplane) 0.61(270.0-bus) 0.63(191.0-train) 0.42(462.0-truck) 0.28(642.0-boat) 0.36(723.0-traffic light) 0.69(85.0-fire hydrant) 0.49(123.0-stop sign) 0.37(43.0-parking meter) 0.16(500.0-bench) 0.37(624.0-bird) 0.71(231.0-cat) 0.70(244.0-dog) 0.61(276.0-horse) 0.43(562.0-sheep) 0.42(497.0-cow) 0.75(349.0-elephant) 0.63(60.0-bear) 0.75(278.0-zebra) 0.81(294.0-giraffe) 0.21(474.0-backpack) 0.32(664.0-umbrella) 0.16(708.0-handbag) 0.37(230.0-tie) 0.33(243.0-suitcase) 0.57(136.0-frisbee) 0.32(400.0-skis) 0.25(132.0-snowboard) 0.44(342.0-sports ball) 0.44(458.0-kite) 0.30(231.0-baseball bat) 0.37(206.0-baseball glove) 0.50(268.0-skateboard) 0.33(404.0-surfboard) 0.54(331.0-tennis racket) 0.38(1254.0-bottle) 0.39(432.0-wine glass) 0.33(1369.0-cup) 0.24(335.0-fork) 0.16(348.0-knife) 0.15(381.0-spoon) 0.38(900.0-bowl) 0.25(468.0-banana) 0.19(433.0-apple) 0.37(180.0-sandwich) 0.22(715.0-orange) 0.43(367.0-broccoli) 0.21(460.0-carrot) 0.31(109.0-hot dog) 0.47(339.0-pizza) 0.25(437.0-donut) 0.37(270.0-cake) 0.29(1872.0-chair) 0.30(338.0-couch) 0.37(410.0-potted plant) 0.45(182.0-bed) 0.30(813.0-dining table) 0.79(164.0-toilet) 0.55(258.0-tv) 0.55(322.0-laptop) 0.47(120.0-mouse) 0.24(329.0-remote) 0.41(143.0-keyboard) 0.26(411.0-cell phone) 0.46(104.0-microwave) 0.25(186.0-oven) 0.00(0.0-toaster) 0.43(277.0-sink) 0.34(152.0-refrigerator) 0.18(1163.0-book) 0.63(319.0-clock) 0.31(323.0-vase) 0.29(51.0-scissors) 0.54(219.0-teddy bear) 0.00(0.0-hair drier) 0.03(420.0-toothbrush)
2021-11-07 08:23:15,464 - mmdet - INFO - pseudo gt: 17257.0 530.0 2779.0 577.0 319.0 431.0 279.0 679.0 701.0 860.0 131.0 147.0 94.0 648.0 820.0 266.0 407.0 386.0 633.0 478.0 444.0 85.0 308.0 349.0 583.0 699.0 806.0 398.0 361.0 156.0 513.0 214.0 402.0 600.0 223.0 272.0 437.0 421.0 345.0 1614.0 552.0 1424.0 380.0 471.0 410.0 964.0 618.0 467.0 295.0 469.0 536.0 519.0 114.0 400.0 452.0 476.0 2296.0 386.0 572.0 263.0 1017.0 257.0 352.0 356.0 165.0 393.0 181.0 404.0 115.0 208.0 23.0 389.0 204.0 1618.0 409.0 452.0 146.0 291.0 17.0 110.0
2021-11-07 08:23:15,464 - mmdet - INFO - pseudo mining: 2145.0 4.0 214.0 26.0 18.0 37.0 9.0 1.0 6.0 52.0 20.0 51.0 0.0 0.0 15.0 16.0 12.0 21.0 57.0 10.0 80.0 4.0 108.0 113.0 1.0 14.0 0.0 10.0 1.0 32.0 3.0 0.0 89.0 57.0 8.0 21.0 14.0 7.0 49.0 67.0 8.0 58.0 0.0 0.0 0.0 18.0 2.0 1.0 0.0 4.0 20.0 4.0 0.0 12.0 20.0 2.0 4.0 0.0 12.0 1.0 5.0 58.0 52.0 29.0 26.0 2.0 4.0 6.0 1.0 1.0 0.0 14.0 2.0 0.0 189.0 7.0 0.0 8.0 0.0 0.0
2021-11-07 08:24:11,255 - mmdet - INFO - Evaluating bbox...
2021-11-07 08:25:21,926 - mmdet - INFO -
+---------------+-------+--------------+-------+----------------+-------+
| category | AP | category | AP | category | AP |
+---------------+-------+--------------+-------+----------------+-------+
| person | 0.388 | bicycle | 0.160 | car | 0.290 |
| motorcycle | 0.219 | airplane | 0.338 | bus | 0.409 |
| train | 0.346 | truck | 0.162 | boat | 0.107 |
| traffic light | 0.164 | fire hydrant | 0.397 | stop sign | 0.448 |
| parking meter | 0.261 | bench | 0.091 | bird | 0.177 |
| cat | 0.382 | dog | 0.347 | horse | 0.298 |
| sheep | 0.289 | cow | 0.316 | elephant | 0.388 |
| bear | 0.463 | zebra | 0.410 | giraffe | 0.456 |
| backpack | 0.042 | umbrella | 0.156 | handbag | 0.038 |
| tie | 0.121 | suitcase | 0.097 | frisbee | 0.393 |
| skis | 0.077 | snowboard | 0.073 | sports ball | 0.331 |
| kite | 0.241 | baseball bat | 0.106 | baseball glove | 0.208 |
| skateboard | 0.200 | surfboard | 0.125 | tennis racket | 0.226 |
| bottle | 0.235 | wine glass | 0.173 | cup | 0.239 |
| fork | 0.048 | knife | 0.023 | spoon | 0.037 |
| bowl | 0.265 | banana | 0.091 | apple | 0.076 |
| sandwich | 0.138 | orange | 0.162 | broccoli | 0.134 |
| carrot | 0.067 | hot dog | 0.096 | pizza | 0.291 |
| donut | 0.208 | cake | 0.115 | chair | 0.103 |
| couch | 0.192 | potted plant | 0.102 | bed | 0.230 |
| dining table | 0.125 | toilet | 0.353 | tv | 0.349 |
| laptop | 0.329 | mouse | 0.352 | remote | 0.080 |
| keyboard | 0.192 | cell phone | 0.129 | microwave | 0.264 |
| oven | 0.152 | toaster | 0.000 | sink | 0.191 |
| refrigerator | 0.198 | book | 0.039 | clock | 0.354 |
| vase | 0.190 | scissors | 0.074 | teddy bear | 0.228 |
| hair drier | 0.000 | toothbrush | 0.015 | None | None |
+---------------+-------+--------------+-------+----------------+-------+
2021-11-07 08:26:18,561 - mmdet - INFO - Evaluating bbox...
2021-11-07 08:27:30,301 - mmdet - INFO -
+---------------+-------+--------------+-------+----------------+-------+
| category | AP | category | AP | category | AP |
+---------------+-------+--------------+-------+----------------+-------+
| person | 0.418 | bicycle | 0.172 | car | 0.312 |
| motorcycle | 0.244 | airplane | 0.400 | bus | 0.448 |
| train | 0.386 | truck | 0.184 | boat | 0.131 |
| traffic light | 0.199 | fire hydrant | 0.468 | stop sign | 0.494 |
| parking meter | 0.304 | bench | 0.121 | bird | 0.204 |
| cat | 0.413 | dog | 0.389 | horse | 0.360 |
| sheep | 0.319 | cow | 0.373 | elephant | 0.446 |
| bear | 0.506 | zebra | 0.490 | giraffe | 0.510 |
| backpack | 0.056 | umbrella | 0.190 | handbag | 0.039 |
| tie | 0.147 | suitcase | 0.135 | frisbee | 0.449 |
| skis | 0.086 | snowboard | 0.082 | sports ball | 0.359 |
| kite | 0.270 | baseball bat | 0.140 | baseball glove | 0.221 |
| skateboard | 0.256 | surfboard | 0.163 | tennis racket | 0.272 |
| bottle | 0.263 | wine glass | 0.207 | cup | 0.281 |
| fork | 0.062 | knife | 0.039 | spoon | 0.045 |
| bowl | 0.301 | banana | 0.116 | apple | 0.109 |
| sandwich | 0.181 | orange | 0.201 | broccoli | 0.157 |
| carrot | 0.077 | hot dog | 0.109 | pizza | 0.334 |
| donut | 0.258 | cake | 0.165 | chair | 0.127 |
| couch | 0.209 | potted plant | 0.129 | bed | 0.229 |
| dining table | 0.128 | toilet | 0.379 | tv | 0.388 |
| laptop | 0.388 | mouse | 0.410 | remote | 0.119 |
| keyboard | 0.272 | cell phone | 0.189 | microwave | 0.320 |
| oven | 0.180 | toaster | 0.107 | sink | 0.177 |
| refrigerator | 0.282 | book | 0.050 | clock | 0.371 |
| vase | 0.238 | scissors | 0.061 | teddy bear | 0.252 |
| hair drier | 0.000 | toothbrush | 0.034 | None | None |
+---------------+-------+--------------+-------+----------------+-------+
2021-11-07 08:28:53,791 - mmdet - INFO - current percent: 0.2
2021-11-07 08:28:53,792 - mmdet - INFO - update score thr (positive): (0.99-person) (0.97-bicycle) (0.97-car) (0.98-motorcycle) (0.99-airplane) (0.99-bus) (0.98-train) (0.90-truck) (0.92-boat) (0.97-traffic light) (1.00-fire hydrant) (1.00-stop sign) (0.97-parking meter) (0.91-bench) (0.94-bird) (0.98-cat) (0.97-dog) (0.98-horse) (0.96-sheep) (0.94-cow) (0.99-elephant) (0.99-bear) (0.99-zebra) (0.99-giraffe) (0.69-backpack) (0.96-umbrella) (0.77-handbag) (0.95-tie) (0.89-suitcase) (0.98-frisbee) (0.86-skis) (0.69-snowboard) (0.99-sports ball) (0.97-kite) (0.91-baseball bat) (0.98-baseball glove) (0.98-skateboard) (0.92-surfboard) (0.99-tennis racket) (0.96-bottle) (0.98-wine glass) (0.94-cup) (0.82-fork) (0.63-knife) (0.63-spoon) (0.93-bowl) (0.93-banana) (0.72-apple) (0.94-sandwich) (0.74-orange) (0.95-broccoli) (0.86-carrot) (0.76-hot dog) (0.97-pizza) (0.94-donut) (0.81-cake) (0.85-chair) (0.89-couch) (0.95-potted plant) (0.92-bed) (0.93-dining table) (0.99-toilet) (0.98-tv) (0.98-laptop) (0.98-mouse) (0.81-remote) (0.96-keyboard) (0.90-cell phone) (0.94-microwave) (0.95-oven) (0.05-toaster) (0.98-sink) (0.93-refrigerator) (0.78-book) (0.99-clock) (0.96-vase) (0.54-scissors) (0.99-teddy bear) (0.05-hair drier) (0.85-toothbrush)
2021-11-07 08:28:53,793 - mmdet - INFO - update score thr (ignore): (0.42-person) (0.55-bicycle) (0.47-car) (0.44-motorcycle) (0.64-airplane) (0.61-bus) (0.49-train) (0.43-truck) (0.43-boat) (0.54-traffic light) (0.59-fire hydrant) (0.78-stop sign) (0.29-parking meter) (0.43-bench) (0.24-bird) (0.59-cat) (0.50-dog) (0.34-horse) (0.36-sheep) (0.46-cow) (0.56-elephant) (0.73-bear) (0.54-zebra) (0.63-giraffe) (0.30-backpack) (0.35-umbrella) (0.35-handbag) (0.47-tie) (0.42-suitcase) (0.54-frisbee) (0.43-skis) (0.33-snowboard) (0.33-sports ball) (0.46-kite) (0.35-baseball bat) (0.47-baseball glove) (0.48-skateboard) (0.40-surfboard) (0.36-tennis racket) (0.49-bottle) (0.36-wine glass) (0.36-cup) (0.32-fork) (0.28-knife) (0.26-spoon) (0.39-bowl) (0.42-banana) (0.27-apple) (0.58-sandwich) (0.36-orange) (0.68-broccoli) (0.55-carrot) (0.30-hot dog) (0.44-pizza) (0.44-donut) (0.24-cake) (0.35-chair) (0.48-couch) (0.54-potted plant) (0.45-bed) (0.48-dining table) (0.78-toilet) (0.63-tv) (0.49-laptop) (0.58-mouse) (0.28-remote) (0.56-keyboard) (0.37-cell phone) (0.54-microwave) (0.54-oven) (0.05-toaster) (0.56-sink) (0.53-refrigerator) (0.38-book) (0.75-clock) (0.50-vase) (0.18-scissors) (0.63-teddy bear) (0.05-hair drier) (0.68-toothbrush)
2021-11-07 08:28:54,093 - mmdet - INFO - Exp name: labelmatch_0.9_1_5_8.py
2021-11-07 08:28:54,093 - mmdet - INFO - Iter [2000/40000] lr: 2.000e-02, eta: 18:49:27, time: 1.720, data_time: 0.026, memory: 25887, bbox_mAP: 0.2390, bbox_mAP_50: 0.4300, bbox_mAP_75: 0.2400, bbox_mAP_s: 0.1320, bbox_mAP_m: 0.2670, bbox_mAP_l: 0.3040, bbox_mAP_copypaste: 0.239 0.430 0.240 0.132 0.267 0.304, loss_rpn_cls: 0.0488, loss_rpn_bbox: 0.0576, loss_cls: 0.2623, acc: 91.5762, loss_bbox: 0.2902, loss_rpn_cls_unlabeled: 0.1329, loss_rpn_bbox_unlabeled: 0.1242, loss_cls_unlabeled: 0.2368, acc_unlabeled: 90.5634, loss_bbox_unlabeled: 0.2137, losses_cls_ig_unlabeled: 0.1721, pseudo_num: 1.5166, pseudo_num_ig: 5.6184, pseudo_num_mining: 0.4901, pseudo_num(acc): 0.8165, pseudo_num ig(acc): 0.4466, loss: 1.5386
2021-11-07 08:30:19,402 - mmdet - INFO - Iter [2050/40000] lr: 2.000e-02, eta: 20:30:48, time: 8.449, data_time: 6.772, memory: 25887, loss_rpn_cls: 0.0478, loss_rpn_bbox: 0.0580, loss_cls: 0.2673, acc: 91.4728, loss_bbox: 0.2980, loss_rpn_cls_unlabeled: 0.1088, loss_rpn_bbox_unlabeled: 0.1088, loss_cls_unlabeled: 0.1917, acc_unlabeled: 91.3004, loss_bbox_unlabeled: 0.1718, losses_cls_ig_unlabeled: 0.1724, pseudo_num: 1.5229, pseudo_num_ig: 5.6230, pseudo_num_mining: 0.4919, pseudo_num(acc): 0.8150, pseudo_num ig(acc): 0.4462, loss: 1.4246
2021-11-07 08:31:43,124 - mmdet - INFO - Iter [2100/40000] lr: 2.000e-02, eta: 20:25:07, time: 1.675, data_time: 0.028, memory: 25887, loss_rpn_cls: 0.0475, loss_rpn_bbox: 0.0577, loss_cls: 0.2735, acc: 91.2119, loss_bbox: 0.3057, loss_rpn_cls_unlabeled: 0.1078, loss_rpn_bbox_unlabeled: 0.1056, loss_cls_unlabeled: 0.1997, acc_unlabeled: 90.9750, loss_bbox_unlabeled: 0.1760, losses_cls_ig_unlabeled: 0.1824, pseudo_num: 1.5229, pseudo_num_ig: 5.6219, pseudo_num_mining: 0.4931, pseudo_num(acc): 0.8162, pseudo_num ig(acc): 0.4462, loss: 1.4557
2021-11-07 08:33:07,962 - mmdet - INFO - Iter [2150/40000] lr: 2.000e-02, eta: 20:19:56, time: 1.697, data_time: 0.029, memory: 25887, loss_rpn_cls: 0.0501, loss_rpn_bbox: 0.0572, loss_cls: 0.2740, acc: 91.2775, loss_bbox: 0.2961, loss_rpn_cls_unlabeled: 0.0996, loss_rpn_bbox_unlabeled: 0.1013, loss_cls_unlabeled: 0.1988, acc_unlabeled: 91.1283, loss_bbox_unlabeled: 0.1729, losses_cls_ig_unlabeled: 0.1727, pseudo_num: 1.5227, pseudo_num_ig: 5.6226, pseudo_num_mining: 0.4946, pseudo_num(acc): 0.8171, pseudo_num ig(acc): 0.4463, loss: 1.4227
2021-11-07 08:34:33,230 - mmdet - INFO - Iter [2200/40000] lr: 2.000e-02, eta: 20:15:03, time: 1.705, data_time: 0.028, memory: 25887, loss_rpn_cls: 0.0475, loss_rpn_bbox: 0.0589, loss_cls: 0.2757, acc: 91.1378, loss_bbox: 0.3061, loss_rpn_cls_unlabeled: 0.1140, loss_rpn_bbox_unlabeled: 0.1125, loss_cls_unlabeled: 0.2113, acc_unlabeled: 90.7391, loss_bbox_unlabeled: 0.1846, losses_cls_ig_unlabeled: 0.1817, pseudo_num: 1.5234, pseudo_num_ig: 5.6219, pseudo_num_mining: 0.4949, pseudo_num(acc): 0.8179, pseudo_num ig(acc): 0.4462, loss: 1.4923
2021-11-07 08:35:58,095 - mmdet - INFO - Iter [2250/40000] lr: 2.000e-02, eta: 20:10:13, time: 1.698, data_time: 0.026, memory: 25887, loss_rpn_cls: 0.0472, loss_rpn_bbox: 0.0566, loss_cls: 0.2756, acc: 91.1544, loss_bbox: 0.3109, loss_rpn_cls_unlabeled: 0.1025, loss_rpn_bbox_unlabeled: 0.1047, loss_cls_unlabeled: 0.2053, acc_unlabeled: 90.9049, loss_bbox_unlabeled: 0.1812, losses_cls_ig_unlabeled: 0.1782, pseudo_num: 1.5253, pseudo_num_ig: 5.6243, pseudo_num_mining: 0.4960, pseudo_num(acc): 0.8184, pseudo_num ig(acc): 0.4463, loss: 1.4623
2021-11-07 08:37:23,265 - mmdet - INFO - Iter [2300/40000] lr: 2.000e-02, eta: 20:05:33, time: 1.699, data_time: 0.026, memory: 25887, loss_rpn_cls: 0.0506, loss_rpn_bbox: 0.0568, loss_cls: 0.2683, acc: 91.5133, loss_bbox: 0.2967, loss_rpn_cls_unlabeled: 0.1016, loss_rpn_bbox_unlabeled: 0.1024, loss_cls_unlabeled: 0.1997, acc_unlabeled: 90.9253, loss_bbox_unlabeled: 0.1783, losses_cls_ig_unlabeled: 0.1796, pseudo_num: 1.5260, pseudo_num_ig: 5.6222, pseudo_num_mining: 0.4956, pseudo_num(acc): 0.8190, pseudo_num ig(acc): 0.4463, loss: 1.4341
2021-11-07 08:38:47,482 - mmdet - INFO - Iter [2350/40000] lr: 2.000e-02, eta: 20:00:53, time: 1.689, data_time: 0.032, memory: 25887, loss_rpn_cls: 0.0472, loss_rpn_bbox: 0.0588, loss_cls: 0.2780, acc: 91.0786, loss_bbox: 0.3074, loss_rpn_cls_unlabeled: 0.1003, loss_rpn_bbox_unlabeled: 0.1055, loss_cls_unlabeled: 0.2075, acc_unlabeled: 90.8800, loss_bbox_unlabeled: 0.1790, losses_cls_ig_unlabeled: 0.1789, pseudo_num: 1.5258, pseudo_num_ig: 5.6223, pseudo_num_mining: 0.4959, pseudo_num(acc): 0.8198, pseudo_num ig(acc): 0.4463, loss: 1.4627
2021-11-07 08:40:11,866 - mmdet - INFO - Iter [2400/40000] lr: 2.000e-02, eta: 19:56:20, time: 1.688, data_time: 0.029, memory: 25887, loss_rpn_cls: 0.0473, loss_rpn_bbox: 0.0585, loss_cls: 0.2709, acc: 91.3165, loss_bbox: 0.2985, loss_rpn_cls_unlabeled: 0.1069, loss_rpn_bbox_unlabeled: 0.1057, loss_cls_unlabeled: 0.1956, acc_unlabeled: 91.2068, loss_bbox_unlabeled: 0.1753, losses_cls_ig_unlabeled: 0.1737, pseudo_num: 1.5266, pseudo_num_ig: 5.6222, pseudo_num_mining: 0.4962, pseudo_num(acc): 0.8206, pseudo_num ig(acc): 0.4463, loss: 1.4324
2021-11-07 08:41:37,757 - mmdet - INFO - Iter [2450/40000] lr: 2.000e-02, eta: 19:52:18, time: 1.718, data_time: 0.026, memory: 25887, loss_rpn_cls: 0.0454, loss_rpn_bbox: 0.0540, loss_cls: 0.2659, acc: 91.4413, loss_bbox: 0.2968, loss_rpn_cls_unlabeled: 0.0997, loss_rpn_bbox_unlabeled: 0.1046, loss_cls_unlabeled: 0.2027, acc_unlabeled: 90.9647, loss_bbox_unlabeled: 0.1810, losses_cls_ig_unlabeled: 0.1760, pseudo_num: 1.5279, pseudo_num_ig: 5.6224, pseudo_num_mining: 0.4959, pseudo_num(acc): 0.8211, pseudo_num ig(acc): 0.4461, loss: 1.4261
2021-11-07 08:43:00,898 - mmdet - INFO - pseudo pos: 0.98(4724.0-person) 0.93(92.0-bicycle) 0.91(729.0-car) 0.95(107.0-motorcycle) 0.97(93.0-airplane) 0.99(113.0-bus) 0.95(96.0-train) 0.69(185.0-truck) 0.62(240.0-boat) 0.90(279.0-traffic light) 1.00(32.0-fire hydrant) 0.97(36.0-stop sign) 0.88(25.0-parking meter) 0.63(179.0-bench) 0.91(175.0-bird) 0.95(84.0-cat) 0.96(85.0-dog) 0.97(105.0-horse) 0.93(245.0-sheep) 0.93(129.0-cow) 1.00(100.0-elephant) 1.00(31.0-bear) 0.96(56.0-zebra) 0.99(71.0-giraffe) 0.48(167.0-backpack) 0.82(193.0-umbrella) 0.39(237.0-handbag) 0.91(80.0-tie) 0.73(97.0-suitcase) 0.95(39.0-frisbee) 0.51(134.0-skis) 0.61(44.0-snowboard) 0.99(88.0-sports ball) 0.92(116.0-kite) 0.84(69.0-baseball bat) 0.95(60.0-baseball glove) 0.98(110.0-skateboard) 0.81(130.0-surfboard) 0.96(76.0-tennis racket) 0.85(402.0-bottle) 0.92(118.0-wine glass) 0.88(389.0-cup) 0.64(73.0-fork) 0.34(123.0-knife) 0.33(137.0-spoon) 0.80(317.0-bowl) 0.66(163.0-banana) 0.42(96.0-apple) 0.77(87.0-sandwich) 0.60(110.0-orange) 0.71(112.0-broccoli) 0.39(180.0-carrot) 0.64(45.0-hot dog) 0.94(122.0-pizza) 0.83(169.0-donut) 0.78(88.0-cake) 0.69(621.0-chair) 0.75(149.0-couch) 0.72(123.0-potted plant) 0.92(76.0-bed) 0.68(378.0-dining table) 0.87(54.0-toilet) 0.94(88.0-tv) 0.99(77.0-laptop) 0.97(37.0-mouse) 0.63(121.0-remote) 0.87(45.0-keyboard) 0.81(112.0-cell phone) 0.95(22.0-microwave) 0.83(71.0-oven) 0.00(0.0-toaster) 0.79(100.0-sink) 0.79(61.0-refrigerator) 0.33(337.0-book) 0.98(64.0-clock) 0.88(127.0-vase) 0.43(30.0-scissors) 0.94(78.0-teddy bear) 0.00(0.0-hair drier) 0.06(338.0-toothbrush)
2021-11-07 08:43:00,899 - mmdet - INFO - pseudo ig: 0.62(16706.0-person) 0.45(280.0-bicycle) 0.48(2689.0-car) 0.59(497.0-motorcycle) 0.61(231.0-airplane) 0.63(322.0-bus) 0.63(254.0-train) 0.40(579.0-truck) 0.30(804.0-boat) 0.38(855.0-traffic light) 0.72(105.0-fire hydrant) 0.48(142.0-stop sign) 0.35(51.0-parking meter) 0.17(608.0-bench) 0.36(756.0-bird) 0.71(294.0-cat) 0.69(297.0-dog) 0.57(395.0-horse) 0.45(780.0-sheep) 0.42(610.0-cow) 0.75(421.0-elephant) 0.67(76.0-bear) 0.75(329.0-zebra) 0.82(346.0-giraffe) 0.21(597.0-backpack) 0.33(789.0-umbrella) 0.17(849.0-handbag) 0.41(281.0-tie) 0.32(310.0-suitcase) 0.55(160.0-frisbee) 0.32(493.0-skis) 0.27(153.0-snowboard) 0.43(454.0-sports ball) 0.42(554.0-kite) 0.31(287.0-baseball bat) 0.38(264.0-baseball glove) 0.48(322.0-skateboard) 0.32(492.0-surfboard) 0.54(410.0-tennis racket) 0.39(1566.0-bottle) 0.41(527.0-wine glass) 0.32(1716.0-cup) 0.24(389.0-fork) 0.16(428.0-knife) 0.14(491.0-spoon) 0.38(1199.0-bowl) 0.25(709.0-banana) 0.18(516.0-apple) 0.37(227.0-sandwich) 0.22(870.0-orange) 0.43(441.0-broccoli) 0.24(552.0-carrot) 0.28(143.0-hot dog) 0.46(416.0-pizza) 0.27(557.0-donut) 0.37(392.0-cake) 0.29(2311.0-chair) 0.30(393.0-couch) 0.38(503.0-potted plant) 0.44(234.0-bed) 0.30(1057.0-dining table) 0.78(223.0-toilet) 0.54(324.0-tv) 0.56(382.0-laptop) 0.48(138.0-mouse) 0.23(434.0-remote) 0.42(172.0-keyboard) 0.28(507.0-cell phone) 0.45(122.0-microwave) 0.26(218.0-oven) 0.00(0.0-toaster) 0.44(351.0-sink) 0.33(178.0-refrigerator) 0.17(1427.0-book) 0.64(372.0-clock) 0.32(402.0-vase) 0.26(74.0-scissors) 0.55(252.0-teddy bear) 0.00(0.0-hair drier) 0.03(425.0-toothbrush)
2021-11-07 08:43:01,054 - mmdet - INFO - pseudo gt: 21921.0 631.0 3427.0 725.0 385.0 526.0 370.0 820.0 903.0 1102.0 168.0 177.0 122.0 800.0 1015.0 346.0 480.0 535.0 925.0 593.0 543.0 113.0 381.0 416.0 731.0 869.0 1013.0 497.0 472.0 194.0 625.0 271.0 534.0 711.0 280.0 350.0 540.0 498.0 437.0 2052.0 694.0 1784.0 463.0 566.0 513.0 1234.0 876.0 577.0 372.0 594.0 643.0 704.0 160.0 477.0 616.0 628.0 2971.0 475.0 716.0 315.0 1280.0 358.0 439.0 452.0 193.0 493.0 218.0 531.0 138.0 262.0 27.0 493.0 256.0 1980.0 489.0 587.0 175.0 339.0 18.0 148.0
2021-11-07 08:43:01,054 - mmdet - INFO - pseudo mining: 2721.0 5.0 268.0 31.0 22.0 50.0 12.0 2.0 14.0 80.0 28.0 61.0 0.0 1.0 16.0 24.0 12.0 30.0 74.0 17.0 99.0 11.0 126.0 137.0 1.0 19.0 0.0 11.0 1.0 34.0 5.0 0.0 116.0 64.0 8.0 30.0 16.0 9.0 64.0 93.0 14.0 74.0 0.0 0.0 0.0 23.0 4.0 1.0 0.0 4.0 25.0 6.0 0.0 17.0 28.0 2.0 5.0 1.0 20.0 1.0 7.0 75.0 65.0 36.0 31.0 4.0 6.0 8.0 2.0 1.0 0.0 18.0 4.0 0.0 220.0 12.0 0.0 9.0 0.0 0.0
2021-11-07 08:43:02,330 - mmdet - INFO - Iter [2500/40000] lr: 2.000e-02, eta: 19:48:03, time: 1.691, data_time: 0.027, memory: 25887, loss_rpn_cls: 0.0455, loss_rpn_bbox: 0.0572, loss_cls: 0.2674, acc: 91.2208, loss_bbox: 0.3081, loss_rpn_cls_unlabeled: 0.1019, loss_rpn_bbox_unlabeled: 0.1063, loss_cls_unlabeled: 0.2033, acc_unlabeled: 91.0767, loss_bbox_unlabeled: 0.1811, losses_cls_ig_unlabeled: 0.1763, pseudo_num: 1.5294, pseudo_num_ig: 5.6224, pseudo_num_mining: 0.4963, pseudo_num(acc): 0.8219, pseudo_num ig(acc): 0.4460, loss: 1.4471
2021-11-07 08:44:27,104 - mmdet - INFO - Iter [2550/40000] lr: 2.000e-02, eta: 19:43:57, time: 1.696, data_time: 0.029, memory: 25887, loss_rpn_cls: 0.0480, loss_rpn_bbox: 0.0588, loss_cls: 0.2762, acc: 91.1173, loss_bbox: 0.3081, loss_rpn_cls_unlabeled: 0.1034, loss_rpn_bbox_unlabeled: 0.1024, loss_cls_unlabeled: 0.2015, acc_unlabeled: 91.2849, loss_bbox_unlabeled: 0.1825, losses_cls_ig_unlabeled: 0.1689, pseudo_num: 1.5307, pseudo_num_ig: 5.6175, pseudo_num_mining: 0.4959, pseudo_num(acc): 0.8226, pseudo_num ig(acc): 0.4460, loss: 1.4498
2021-11-07 08:45:52,336 - mmdet - INFO - Iter [2600/40000] lr: 2.000e-02, eta: 19:40:02, time: 1.702, data_time: 0.025, memory: 25887, loss_rpn_cls: 0.0486, loss_rpn_bbox: 0.0585, loss_cls: 0.2684, acc: 91.3514, loss_bbox: 0.3003, loss_rpn_cls_unlabeled: 0.0985, loss_rpn_bbox_unlabeled: 0.1001, loss_cls_unlabeled: 0.2008, acc_unlabeled: 91.3536, loss_bbox_unlabeled: 0.1779, losses_cls_ig_unlabeled: 0.1689, pseudo_num: 1.5311, pseudo_num_ig: 5.6138, pseudo_num_mining: 0.4961, pseudo_num(acc): 0.8232, pseudo_num ig(acc): 0.4460, loss: 1.4219
2021-11-07 08:47:16,517 - mmdet - INFO - Iter [2650/40000] lr: 2.000e-02, eta: 19:36:00, time: 1.685, data_time: 0.030, memory: 25887, loss_rpn_cls: 0.0455, loss_rpn_bbox: 0.0579, loss_cls: 0.2655, acc: 91.3702, loss_bbox: 0.3020, loss_rpn_cls_unlabeled: 0.1029, loss_rpn_bbox_unlabeled: 0.1047, loss_cls_unlabeled: 0.2071, acc_unlabeled: 91.1180, loss_bbox_unlabeled: 0.1893, losses_cls_ig_unlabeled: 0.1696, pseudo_num: 1.5327, pseudo_num_ig: 5.6071, pseudo_num_mining: 0.4963, pseudo_num(acc): 0.8236, pseudo_num ig(acc): 0.4460, loss: 1.4445
2021-11-07 08:48:40,109 - mmdet - INFO - Iter [2700/40000] lr: 2.000e-02, eta: 19:31:55, time: 1.671, data_time: 0.029, memory: 25887, loss_rpn_cls: 0.0456, loss_rpn_bbox: 0.0563, loss_cls: 0.2709, acc: 91.2527, loss_bbox: 0.3027, loss_rpn_cls_unlabeled: 0.1029, loss_rpn_bbox_unlabeled: 0.1036, loss_cls_unlabeled: 0.1988, acc_unlabeled: 91.1689, loss_bbox_unlabeled: 0.1725, losses_cls_ig_unlabeled: 0.1726, pseudo_num: 1.5338, pseudo_num_ig: 5.6063, pseudo_num_mining: 0.4964, pseudo_num(acc): 0.8240, pseudo_num ig(acc): 0.4460, loss: 1.4259
2021-11-07 08:50:03,418 - mmdet - INFO - Iter [2750/40000] lr: 2.000e-02, eta: 19:27:54, time: 1.668, data_time: 0.028, memory: 25887, loss_rpn_cls: 0.0471, loss_rpn_bbox: 0.0560, loss_cls: 0.2696, acc: 91.3738, loss_bbox: 0.2974, loss_rpn_cls_unlabeled: 0.1004, loss_rpn_bbox_unlabeled: 0.1010, loss_cls_unlabeled: 0.2060, acc_unlabeled: 91.2345, loss_bbox_unlabeled: 0.1829, losses_cls_ig_unlabeled: 0.1715, pseudo_num: 1.5351, pseudo_num_ig: 5.6056, pseudo_num_mining: 0.4963, pseudo_num(acc): 0.8244, pseudo_num ig(acc): 0.4458, loss: 1.4319
2021-11-07 08:51:28,230 - mmdet - INFO - Iter [2800/40000] lr: 2.000e-02, eta: 19:24:16, time: 1.694, data_time: 0.026, memory: 25887, loss_rpn_cls: 0.0465, loss_rpn_bbox: 0.0571, loss_cls: 0.2708, acc: 91.2483, loss_bbox: 0.2993, loss_rpn_cls_unlabeled: 0.1084, loss_rpn_bbox_unlabeled: 0.1069, loss_cls_unlabeled: 0.2137, acc_unlabeled: 91.0117, loss_bbox_unlabeled: 0.1873, losses_cls_ig_unlabeled: 0.1741, pseudo_num: 1.5379, pseudo_num_ig: 5.6068, pseudo_num_mining: 0.4970, pseudo_num(acc): 0.8251, pseudo_num ig(acc): 0.4459, loss: 1.4642
2021-11-07 08:52:52,387 - mmdet - INFO - Iter [2850/40000] lr: 2.000e-02, eta: 19:20:35, time: 1.683, data_time: 0.028, memory: 25887, loss_rpn_cls: 0.0444, loss_rpn_bbox: 0.0548, loss_cls: 0.2595, acc: 91.4895, loss_bbox: 0.2944, loss_rpn_cls_unlabeled: 0.1050, loss_rpn_bbox_unlabeled: 0.1049, loss_cls_unlabeled: 0.2108, acc_unlabeled: 91.2161, loss_bbox_unlabeled: 0.1906, losses_cls_ig_unlabeled: 0.1663, pseudo_num: 1.5403, pseudo_num_ig: 5.6055, pseudo_num_mining: 0.4976, pseudo_num(acc): 0.8255, pseudo_num ig(acc): 0.4459, loss: 1.4308
2021-11-07 08:54:17,140 - mmdet - INFO - Iter [2900/40000] lr: 2.000e-02, eta: 19:17:07, time: 1.695, data_time: 0.028, memory: 25887, loss_rpn_cls: 0.0445, loss_rpn_bbox: 0.0571, loss_cls: 0.2648, acc: 91.3785, loss_bbox: 0.3020, loss_rpn_cls_unlabeled: 0.0971, loss_rpn_bbox_unlabeled: 0.0988, loss_cls_unlabeled: 0.1988, acc_unlabeled: 91.4397, loss_bbox_unlabeled: 0.1747, losses_cls_ig_unlabeled: 0.1667, pseudo_num: 1.5424, pseudo_num_ig: 5.6023, pseudo_num_mining: 0.4980, pseudo_num(acc): 0.8261, pseudo_num ig(acc): 0.4460, loss: 1.4044
2021-11-07 08:55:40,967 - mmdet - INFO - Iter [2950/40000] lr: 2.000e-02, eta: 19:13:31, time: 1.677, data_time: 0.029, memory: 25887, loss_rpn_cls: 0.0420, loss_rpn_bbox: 0.0540, loss_cls: 0.2668, acc: 91.4148, loss_bbox: 0.2994, loss_rpn_cls_unlabeled: 0.1004, loss_rpn_bbox_unlabeled: 0.1021, loss_cls_unlabeled: 0.2007, acc_unlabeled: 91.2747, loss_bbox_unlabeled: 0.1880, losses_cls_ig_unlabeled: 0.1669, pseudo_num: 1.5437, pseudo_num_ig: 5.5985, pseudo_num_mining: 0.4978, pseudo_num(acc): 0.8268, pseudo_num ig(acc): 0.4461, loss: 1.4203
2021-11-07 08:57:04,581 - mmdet - INFO - pseudo pos: 0.98(5768.0-person) 0.94(105.0-bicycle) 0.92(876.0-car) 0.95(131.0-motorcycle) 0.97(111.0-airplane) 0.99(130.0-bus) 0.96(127.0-train) 0.70(219.0-truck) 0.65(271.0-boat) 0.90(311.0-traffic light) 1.00(37.0-fire hydrant) 0.95(38.0-stop sign) 0.90(30.0-parking meter) 0.64(209.0-bench) 0.92(222.0-bird) 0.95(104.0-cat) 0.97(108.0-dog) 0.98(126.0-horse) 0.93(294.0-sheep) 0.94(146.0-cow) 1.00(122.0-elephant) 1.00(36.0-bear) 0.98(85.0-zebra) 0.98(91.0-giraffe) 0.46(211.0-backpack) 0.82(240.0-umbrella) 0.41(261.0-handbag) 0.92(90.0-tie) 0.75(123.0-suitcase) 0.96(50.0-frisbee) 0.53(159.0-skis) 0.57(49.0-snowboard) 0.99(99.0-sports ball) 0.91(161.0-kite) 0.82(96.0-baseball bat) 0.95(77.0-baseball glove) 0.98(128.0-skateboard) 0.82(161.0-surfboard) 0.96(85.0-tennis racket) 0.85(464.0-bottle) 0.93(138.0-wine glass) 0.87(475.0-cup) 0.67(84.0-fork) 0.36(159.0-knife) 0.33(187.0-spoon) 0.80(393.0-bowl) 0.64(188.0-banana) 0.45(141.0-apple) 0.78(102.0-sandwich) 0.58(139.0-orange) 0.72(127.0-broccoli) 0.42(198.0-carrot) 0.65(55.0-hot dog) 0.95(148.0-pizza) 0.85(194.0-donut) 0.73(136.0-cake) 0.69(796.0-chair) 0.76(173.0-couch) 0.72(152.0-potted plant) 0.91(97.0-bed) 0.68(459.0-dining table) 0.86(64.0-toilet) 0.95(109.0-tv) 0.99(97.0-laptop) 0.98(44.0-mouse) 0.66(140.0-remote) 0.89(55.0-keyboard) 0.82(146.0-cell phone) 0.94(34.0-microwave) 0.86(83.0-oven) 0.00(0.0-toaster) 0.80(121.0-sink) 0.82(71.0-refrigerator) 0.31(416.0-book) 0.98(90.0-clock) 0.89(144.0-vase) 0.50(46.0-scissors) 0.93(89.0-teddy bear) 0.00(0.0-hair drier) 0.06(338.0-toothbrush)
2021-11-07 08:57:04,582 - mmdet - INFO - pseudo ig: 0.61(20055.0-person) 0.48(371.0-bicycle) 0.47(3231.0-car) 0.59(595.0-motorcycle) 0.65(290.0-airplane) 0.66(398.0-bus) 0.61(309.0-train) 0.39(741.0-truck) 0.31(908.0-boat) 0.41(974.0-traffic light) 0.73(130.0-fire hydrant) 0.52(172.0-stop sign) 0.33(58.0-parking meter) 0.18(742.0-bench) 0.36(885.0-bird) 0.72(357.0-cat) 0.70(350.0-dog) 0.55(490.0-horse) 0.44(972.0-sheep) 0.42(687.0-cow) 0.75(459.0-elephant) 0.64(89.0-bear) 0.76(388.0-zebra) 0.83(429.0-giraffe) 0.22(754.0-backpack) 0.34(981.0-umbrella) 0.18(964.0-handbag) 0.41(321.0-tie) 0.32(400.0-suitcase) 0.56(192.0-frisbee) 0.31(575.0-skis) 0.29(177.0-snowboard) 0.43(520.0-sports ball) 0.41(657.0-kite) 0.31(346.0-baseball bat) 0.37(307.0-baseball glove) 0.47(366.0-skateboard) 0.32(579.0-surfboard) 0.55(486.0-tennis racket) 0.38(1811.0-bottle) 0.43(618.0-wine glass) 0.32(2076.0-cup) 0.25(449.0-fork) 0.17(564.0-knife) 0.14(589.0-spoon) 0.36(1474.0-bowl) 0.27(855.0-banana) 0.19(627.0-apple) 0.37(275.0-sandwich) 0.21(956.0-orange) 0.43(502.0-broccoli) 0.24(603.0-carrot) 0.30(183.0-hot dog) 0.44(511.0-pizza) 0.29(664.0-donut) 0.34(501.0-cake) 0.29(2830.0-chair) 0.32(474.0-couch) 0.39(622.0-potted plant) 0.45(271.0-bed) 0.30(1269.0-dining table) 0.76(266.0-toilet) 0.53(384.0-tv) 0.56(433.0-laptop) 0.47(160.0-mouse) 0.24(524.0-remote) 0.40(201.0-keyboard) 0.26(602.0-cell phone) 0.43(142.0-microwave) 0.27(262.0-oven) 0.00(0.0-toaster) 0.44(419.0-sink) 0.33(196.0-refrigerator) 0.17(1693.0-book) 0.62(434.0-clock) 0.33(464.0-vase) 0.24(101.0-scissors) 0.56(280.0-teddy bear) 0.00(0.0-hair drier) 0.03(427.0-toothbrush)
2021-11-07 08:57:04,582 - mmdet - INFO - pseudo gt: 26187.0 823.0 4145.0 846.0 493.0 653.0 453.0 1018.0 1051.0 1325.0 202.0 207.0 140.0 978.0 1232.0 422.0 577.0 629.0 1106.0 678.0 621.0 127.0 467.0 518.0 880.0 1073.0 1229.0 613.0 592.0 238.0 731.0 317.0 611.0 839.0 339.0 418.0 616.0 620.0 523.0 2375.0 833.0 2166.0 555.0 749.0 617.0 1497.0 1110.0 675.0 453.0 646.0 768.0 843.0 212.0 568.0 725.0 746.0 3693.0 592.0 898.0 381.0 1585.0 431.0 517.0 519.0 217.0 573.0 251.0 637.0 168.0 323.0 28.0 600.0 294.0 2459.0 599.0 717.0 205.0 382.0 23.0 170.0
2021-11-07 08:57:04,582 - mmdet - INFO - pseudo mining: 3276.0 7.0 322.0 34.0 27.0 65.0 13.0 5.0 15.0 97.0 36.0 80.0 0.0 2.0 17.0 27.0 17.0 36.0 87.0 20.0 112.0 13.0 147.0 174.0 1.0 28.0 0.0 16.0 1.0 42.0 5.0 0.0 139.0 72.0 8.0 32.0 20.0 9.0 76.0 114.0 21.0 82.0 0.0 0.0 0.0 28.0 5.0 1.0 1.0 4.0 27.0 7.0 0.0 22.0 30.0 3.0 7.0 1.0 21.0 1.0 9.0 88.0 78.0 38.0 36.0 6.0 6.0 9.0 2.0 2.0 0.0 28.0 4.0 0.0 245.0 15.0 0.0 11.0 0.0 0.0
2021-11-07 08:58:30,380 - mmdet - INFO - current percent: 0.2
2021-11-07 08:58:30,381 - mmdet - INFO - update score thr (positive): (0.99-person) (0.97-bicycle) (0.97-car) (0.98-motorcycle) (0.99-airplane) (0.99-bus) (0.99-train) (0.89-truck) (0.92-boat) (0.96-traffic light) (1.00-fire hydrant) (1.00-stop sign) (0.96-parking meter) (0.87-bench) (0.94-bird) (0.98-cat) (0.97-dog) (0.98-horse) (0.98-sheep) (0.95-cow) (1.00-elephant) (0.99-bear) (0.99-zebra) (0.99-giraffe) (0.77-backpack) (0.96-umbrella) (0.65-handbag) (0.95-tie) (0.93-suitcase) (0.99-frisbee) (0.89-skis) (0.62-snowboard) (0.99-sports ball) (0.98-kite) (0.97-baseball bat) (0.99-baseball glove) (0.98-skateboard) (0.95-surfboard) (0.99-tennis racket) (0.96-bottle) (0.98-wine glass) (0.96-cup) (0.85-fork) (0.71-knife) (0.79-spoon) (0.96-bowl) (0.90-banana) (0.84-apple) (0.96-sandwich) (0.86-orange) (0.92-broccoli) (0.75-carrot) (0.81-hot dog) (0.98-pizza) (0.96-donut) (0.95-cake) (0.89-chair) (0.88-couch) (0.96-potted plant) (0.92-bed) (0.95-dining table) (0.99-toilet) (0.99-tv) (0.99-laptop) (0.99-mouse) (0.93-remote) (0.97-keyboard) (0.92-cell phone) (0.93-microwave) (0.95-oven) (0.05-toaster) (0.98-sink) (0.93-refrigerator) (0.76-book) (0.99-clock) (0.95-vase) (0.87-scissors) (0.99-teddy bear) (0.05-hair drier) (0.27-toothbrush)
2021-11-07 08:58:30,382 - mmdet - INFO - update score thr (ignore): (0.42-person) (0.48-bicycle) (0.50-car) (0.44-motorcycle) (0.53-airplane) (0.55-bus) (0.47-train) (0.40-truck) (0.36-boat) (0.35-traffic light) (0.59-fire hydrant) (0.77-stop sign) (0.18-parking meter) (0.37-bench) (0.22-bird) (0.58-cat) (0.51-dog) (0.38-horse) (0.42-sheep) (0.40-cow) (0.64-elephant) (0.57-bear) (0.70-zebra) (0.31-giraffe) (0.36-backpack) (0.42-umbrella) (0.23-handbag) (0.48-tie) (0.42-suitcase) (0.49-frisbee) (0.44-skis) (0.23-snowboard) (0.35-sports ball) (0.64-kite) (0.47-baseball bat) (0.53-baseball glove) (0.44-skateboard) (0.44-surfboard) (0.34-tennis racket) (0.43-bottle) (0.40-wine glass) (0.37-cup) (0.31-fork) (0.31-knife) (0.37-spoon) (0.46-bowl) (0.34-banana) (0.45-apple) (0.59-sandwich) (0.48-orange) (0.55-broccoli) (0.38-carrot) (0.36-hot dog) (0.52-pizza) (0.46-donut) (0.42-cake) (0.35-chair) (0.43-couch) (0.55-potted plant) (0.41-bed) (0.50-dining table) (0.70-toilet) (0.57-tv) (0.47-laptop) (0.60-mouse) (0.37-remote) (0.50-keyboard) (0.40-cell phone) (0.53-microwave) (0.48-oven) (0.05-toaster) (0.54-sink) (0.46-refrigerator) (0.31-book) (0.67-clock) (0.39-vase) (0.32-scissors) (0.63-teddy bear) (0.05-hair drier) (0.11-toothbrush)
2021-11-07 08:58:30,813 - mmdet - INFO - Exp name: labelmatch_0.9_1_5_8.py
2021-11-07 08:58:30,813 - mmdet - INFO - Iter [3000/40000] lr: 2.000e-02, eta: 19:10:18, time: 1.705, data_time: 0.030, memory: 26253, loss_rpn_cls: 0.0443, loss_rpn_bbox: 0.0564, loss_cls: 0.2684, acc: 91.3448, loss_bbox: 0.2997, loss_rpn_cls_unlabeled: 0.1008, loss_rpn_bbox_unlabeled: 0.0979, loss_cls_unlabeled: 0.2133, acc_unlabeled: 91.1876, loss_bbox_unlabeled: 0.1888, losses_cls_ig_unlabeled: 0.1686, pseudo_num: 1.5458, pseudo_num_ig: 5.5955, pseudo_num_mining: 0.4982, pseudo_num(acc): 0.8273, pseudo_num ig(acc): 0.4462, loss: 1.4381
2021-11-07 08:59:54,444 - mmdet - INFO - Iter [3050/40000] lr: 2.000e-02, eta: 19:23:53, time: 3.365, data_time: 1.718, memory: 26253, loss_rpn_cls: 0.0443, loss_rpn_bbox: 0.0534, loss_cls: 0.2546, acc: 91.7114, loss_bbox: 0.2895, loss_rpn_cls_unlabeled: 0.0977, loss_rpn_bbox_unlabeled: 0.1015, loss_cls_unlabeled: 0.1939, acc_unlabeled: 91.2275, loss_bbox_unlabeled: 0.1793, losses_cls_ig_unlabeled: 0.1690, pseudo_num: 1.5470, pseudo_num_ig: 5.5907, pseudo_num_mining: 0.4991, pseudo_num(acc): 0.8277, pseudo_num ig(acc): 0.4464, loss: 1.3834
2021-11-07 09:01:18,785 - mmdet - INFO - Iter [3100/40000] lr: 2.000e-02, eta: 19:20:16, time: 1.685, data_time: 0.026, memory: 26253, loss_rpn_cls: 0.0419, loss_rpn_bbox: 0.0551, loss_cls: 0.2603, acc: 91.5280, loss_bbox: 0.2995, loss_rpn_cls_unlabeled: 0.0980, loss_rpn_bbox_unlabeled: 0.0967, loss_cls_unlabeled: 0.1882, acc_unlabeled: 91.1586, loss_bbox_unlabeled: 0.1655, losses_cls_ig_unlabeled: 0.1793, pseudo_num: 1.5452, pseudo_num_ig: 5.5903, pseudo_num_mining: 0.5006, pseudo_num(acc): 0.8283, pseudo_num ig(acc): 0.4468, loss: 1.3843
2021-11-07 09:02:43,419 - mmdet - INFO - Iter [3150/40000] lr: 2.000e-02, eta: 19:16:50, time: 1.694, data_time: 0.030, memory: 26253, loss_rpn_cls: 0.0429, loss_rpn_bbox: 0.0523, loss_cls: 0.2617, acc: 91.4756, loss_bbox: 0.3019, loss_rpn_cls_unlabeled: 0.0952, loss_rpn_bbox_unlabeled: 0.1023, loss_cls_unlabeled: 0.1959, acc_unlabeled: 91.3567, loss_bbox_unlabeled: 0.1747, losses_cls_ig_unlabeled: 0.1684, pseudo_num: 1.5433, pseudo_num_ig: 5.5895, pseudo_num_mining: 0.5023, pseudo_num(acc): 0.8286, pseudo_num ig(acc): 0.4471, loss: 1.3953
2021-11-07 09:04:08,089 - mmdet - INFO - Iter [3200/40000] lr: 2.000e-02, eta: 19:13:24, time: 1.690, data_time: 0.025, memory: 26253, loss_rpn_cls: 0.0437, loss_rpn_bbox: 0.0563, loss_cls: 0.2588, acc: 91.6100, loss_bbox: 0.2907, loss_rpn_cls_unlabeled: 0.0973, loss_rpn_bbox_unlabeled: 0.0999, loss_cls_unlabeled: 0.1901, acc_unlabeled: 91.3024, loss_bbox_unlabeled: 0.1741, losses_cls_ig_unlabeled: 0.1707, pseudo_num: 1.5425, pseudo_num_ig: 5.5879, pseudo_num_mining: 0.5041, pseudo_num(acc): 0.8290, pseudo_num ig(acc): 0.4474, loss: 1.3816
2021-11-07 09:05:33,253 - mmdet - INFO - Iter [3250/40000] lr: 2.000e-02, eta: 19:10:11, time: 1.706, data_time: 0.030, memory: 26253, loss_rpn_cls: 0.0443, loss_rpn_bbox: 0.0558, loss_cls: 0.2570, acc: 91.5359, loss_bbox: 0.2994, loss_rpn_cls_unlabeled: 0.0986, loss_rpn_bbox_unlabeled: 0.1056, loss_cls_unlabeled: 0.1980, acc_unlabeled: 91.0699, loss_bbox_unlabeled: 0.1796, losses_cls_ig_unlabeled: 0.1759, pseudo_num: 1.5420, pseudo_num_ig: 5.5879, pseudo_num_mining: 0.5059, pseudo_num(acc): 0.8296, pseudo_num ig(acc): 0.4478, loss: 1.4143
2021-11-07 09:06:58,898 - mmdet - INFO - Iter [3300/40000] lr: 2.000e-02, eta: 19:07:05, time: 1.712, data_time: 0.027, memory: 26253, loss_rpn_cls: 0.0430, loss_rpn_bbox: 0.0554, loss_cls: 0.2553, acc: 91.5726, loss_bbox: 0.2992, loss_rpn_cls_unlabeled: 0.1009, loss_rpn_bbox_unlabeled: 0.0987, loss_cls_unlabeled: 0.1985, acc_unlabeled: 91.2194, loss_bbox_unlabeled: 0.1806, losses_cls_ig_unlabeled: 0.1676, pseudo_num: 1.5417, pseudo_num_ig: 5.5867, pseudo_num_mining: 0.5072, pseudo_num(acc): 0.8300, pseudo_num ig(acc): 0.4479, loss: 1.3991
2021-11-07 09:08:22,428 - mmdet - INFO - Iter [3350/40000] lr: 2.000e-02, eta: 19:03:40, time: 1.671, data_time: 0.029, memory: 26485, loss_rpn_cls: 0.0448, loss_rpn_bbox: 0.0554, loss_cls: 0.2535, acc: 91.7452, loss_bbox: 0.2900, loss_rpn_cls_unlabeled: 0.1024, loss_rpn_bbox_unlabeled: 0.1034, loss_cls_unlabeled: 0.2032, acc_unlabeled: 91.3120, loss_bbox_unlabeled: 0.1811, losses_cls_ig_unlabeled: 0.1720, pseudo_num: 1.5415, pseudo_num_ig: 5.5851, pseudo_num_mining: 0.5086, pseudo_num(acc): 0.8305, pseudo_num ig(acc): 0.4482, loss: 1.4060
2021-11-07 09:09:47,161 - mmdet - INFO - Iter [3400/40000] lr: 2.000e-02, eta: 19:00:29, time: 1.692, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0407, loss_rpn_bbox: 0.0551, loss_cls: 0.2463, acc: 91.8379, loss_bbox: 0.2890, loss_rpn_cls_unlabeled: 0.0964, loss_rpn_bbox_unlabeled: 0.1006, loss_cls_unlabeled: 0.1887, acc_unlabeled: 91.3185, loss_bbox_unlabeled: 0.1750, losses_cls_ig_unlabeled: 0.1689, pseudo_num: 1.5417, pseudo_num_ig: 5.5835, pseudo_num_mining: 0.5097, pseudo_num(acc): 0.8309, pseudo_num ig(acc): 0.4485, loss: 1.3606
2021-11-07 09:11:11,177 - mmdet - INFO - Iter [3450/40000] lr: 2.000e-02, eta: 18:57:16, time: 1.682, data_time: 0.031, memory: 26485, loss_rpn_cls: 0.0439, loss_rpn_bbox: 0.0573, loss_cls: 0.2510, acc: 91.7535, loss_bbox: 0.2912, loss_rpn_cls_unlabeled: 0.0982, loss_rpn_bbox_unlabeled: 0.0999, loss_cls_unlabeled: 0.1906, acc_unlabeled: 91.2134, loss_bbox_unlabeled: 0.1697, losses_cls_ig_unlabeled: 0.1711, pseudo_num: 1.5416, pseudo_num_ig: 5.5817, pseudo_num_mining: 0.5105, pseudo_num(acc): 0.8311, pseudo_num ig(acc): 0.4485, loss: 1.3728
2021-11-07 09:12:35,858 - mmdet - INFO - pseudo pos: 0.98(6817.0-person) 0.94(127.0-bicycle) 0.92(1035.0-car) 0.96(156.0-motorcycle) 0.98(129.0-airplane) 0.99(155.0-bus) 0.97(143.0-train) 0.70(267.0-truck) 0.65(301.0-boat) 0.91(361.0-traffic light) 1.00(40.0-fire hydrant) 0.95(44.0-stop sign) 0.91(32.0-parking meter) 0.63(238.0-bench) 0.93(259.0-bird) 0.94(127.0-cat) 0.98(125.0-dog) 0.97(142.0-horse) 0.94(326.0-sheep) 0.94(196.0-cow) 0.99(136.0-elephant) 0.98(45.0-bear) 0.98(104.0-zebra) 0.98(103.0-giraffe) 0.47(256.0-backpack) 0.82(290.0-umbrella) 0.42(320.0-handbag) 0.93(104.0-tie) 0.75(132.0-suitcase) 0.95(58.0-frisbee) 0.55(175.0-skis) 0.59(58.0-snowboard) 0.98(118.0-sports ball) 0.92(193.0-kite) 0.83(104.0-baseball bat) 0.95(88.0-baseball glove) 0.97(148.0-skateboard) 0.81(193.0-surfboard) 0.97(101.0-tennis racket) 0.85(558.0-bottle) 0.93(149.0-wine glass) 0.87(549.0-cup) 0.68(99.0-fork) 0.40(191.0-knife) 0.34(197.0-spoon) 0.81(439.0-bowl) 0.64(209.0-banana) 0.45(153.0-apple) 0.78(114.0-sandwich) 0.59(158.0-orange) 0.73(139.0-broccoli) 0.41(226.0-carrot) 0.66(61.0-hot dog) 0.94(175.0-pizza) 0.85(197.0-donut) 0.73(149.0-cake) 0.71(950.0-chair) 0.76(197.0-couch) 0.71(174.0-potted plant) 0.90(112.0-bed) 0.69(514.0-dining table) 0.86(70.0-toilet) 0.97(143.0-tv) 0.98(118.0-laptop) 0.98(53.0-mouse) 0.67(155.0-remote) 0.90(70.0-keyboard) 0.82(160.0-cell phone) 0.95(44.0-microwave) 0.84(92.0-oven) 0.00(0.0-toaster) 0.77(146.0-sink) 0.82(78.0-refrigerator) 0.30(495.0-book) 0.98(107.0-clock) 0.90(168.0-vase) 0.53(49.0-scissors) 0.93(97.0-teddy bear) 0.00(0.0-hair drier) 0.06(354.0-toothbrush)
2021-11-07 09:12:35,859 - mmdet - INFO - pseudo ig: 0.61(23556.0-person) 0.48(458.0-bicycle) 0.48(3850.0-car) 0.58(715.0-motorcycle) 0.64(329.0-airplane) 0.66(461.0-bus) 0.62(365.0-train) 0.38(894.0-truck) 0.31(1031.0-boat) 0.40(1146.0-traffic light) 0.74(146.0-fire hydrant) 0.52(195.0-stop sign) 0.36(66.0-parking meter) 0.19(860.0-bench) 0.36(1025.0-bird) 0.71(428.0-cat) 0.70(410.0-dog) 0.55(546.0-horse) 0.45(1120.0-sheep) 0.43(827.0-cow) 0.74(557.0-elephant) 0.68(110.0-bear) 0.78(443.0-zebra) 0.81(503.0-giraffe) 0.20(899.0-backpack) 0.36(1133.0-umbrella) 0.18(1164.0-handbag) 0.44(385.0-tie) 0.33(485.0-suitcase) 0.53(239.0-frisbee) 0.30(661.0-skis) 0.29(209.0-snowboard) 0.43(599.0-sports ball) 0.45(779.0-kite) 0.30(391.0-baseball bat) 0.38(352.0-baseball glove) 0.47(427.0-skateboard) 0.33(714.0-surfboard) 0.55(550.0-tennis racket) 0.38(2119.0-bottle) 0.43(668.0-wine glass) 0.32(2397.0-cup) 0.25(504.0-fork) 0.19(657.0-knife) 0.15(645.0-spoon) 0.36(1694.0-bowl) 0.27(922.0-banana) 0.19(677.0-apple) 0.37(310.0-sandwich) 0.21(989.0-orange) 0.42(570.0-broccoli) 0.24(677.0-carrot) 0.31(212.0-hot dog) 0.43(578.0-pizza) 0.30(728.0-donut) 0.33(539.0-cake) 0.30(3378.0-chair) 0.34(549.0-couch) 0.38(722.0-potted plant) 0.44(322.0-bed) 0.31(1458.0-dining table) 0.75(297.0-toilet) 0.52(454.0-tv) 0.55(512.0-laptop) 0.46(201.0-mouse) 0.26(616.0-remote) 0.41(238.0-keyboard) 0.26(698.0-cell phone) 0.42(161.0-microwave) 0.29(320.0-oven) 0.00(0.0-toaster) 0.45(477.0-sink) 0.32(240.0-refrigerator) 0.16(2037.0-book) 0.63(505.0-clock) 0.35(525.0-vase) 0.22(114.0-scissors) 0.56(346.0-teddy bear) 0.00(0.0-hair drier) 0.04(482.0-toothbrush)
2021-11-07 09:12:35,859 - mmdet - INFO - pseudo gt: 30702.0 999.0 4989.0 1003.0 564.0 742.0 521.0 1201.0 1191.0 1517.0 221.0 231.0 167.0 1154.0 1375.0 508.0 660.0 706.0 1273.0 846.0 727.0 160.0 548.0 592.0 1042.0 1313.0 1465.0 740.0 705.0 271.0 855.0 351.0 733.0 1013.0 398.0 490.0 698.0 735.0 594.0 2804.0 910.0 2481.0 639.0 877.0 723.0 1723.0 1222.0 714.0 530.0 713.0 866.0 981.0 248.0 634.0 837.0 856.0 4470.0 693.0 1017.0 452.0 1859.0 484.0 629.0 614.0 274.0 684.0 308.0 742.0 197.0 381.0 30.0 684.0 337.0 2867.0 711.0 821.0 217.0 477.0 28.0 227.0
2021-11-07 09:12:35,859 - mmdet - INFO - pseudo mining: 3894.0 7.0 417.0 44.0 33.0 74.0 20.0 5.0 15.0 113.0 41.0 91.0 0.0 4.0 18.0 35.0 19.0 41.0 109.0 24.0 144.0 25.0 178.0 203.0 1.0 37.0 0.0 19.0 3.0 55.0 7.0 0.0 162.0 99.0 12.0 38.0 24.0 14.0 91.0 130.0 22.0 103.0 1.0 0.0 0.0 34.0 5.0 1.0 1.0 4.0 29.0 8.0 0.0 24.0 33.0 4.0 11.0 1.0 23.0 1.0 10.0 100.0 92.0 49.0 47.0 6.0 9.0 9.0 2.0 2.0 0.0 33.0 4.0 0.0 292.0 17.0 0.0 16.0 0.0 0.0
2021-11-07 09:12:37,427 - mmdet - INFO - Iter [3500/40000] lr: 2.000e-02, eta: 18:54:30, time: 1.727, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0447, loss_rpn_bbox: 0.0573, loss_cls: 0.2589, acc: 91.4700, loss_bbox: 0.2965, loss_rpn_cls_unlabeled: 0.1074, loss_rpn_bbox_unlabeled: 0.1065, loss_cls_unlabeled: 0.2009, acc_unlabeled: 91.0922, loss_bbox_unlabeled: 0.1720, losses_cls_ig_unlabeled: 0.1777, pseudo_num: 1.5405, pseudo_num_ig: 5.5811, pseudo_num_mining: 0.5118, pseudo_num(acc): 0.8317, pseudo_num ig(acc): 0.4489, loss: 1.4219
2021-11-07 09:15:17,750 - mmdet - INFO - Iter [3550/40000] lr: 2.000e-02, eta: 19:04:25, time: 3.206, data_time: 0.025, memory: 26485, loss_rpn_cls: 0.0449, loss_rpn_bbox: 0.0557, loss_cls: 0.2539, acc: 91.6356, loss_bbox: 0.2916, loss_rpn_cls_unlabeled: 0.0986, loss_rpn_bbox_unlabeled: 0.0999, loss_cls_unlabeled: 0.1998, acc_unlabeled: 91.2864, loss_bbox_unlabeled: 0.1783, losses_cls_ig_unlabeled: 0.1718, pseudo_num: 1.5401, pseudo_num_ig: 5.5804, pseudo_num_mining: 0.5132, pseudo_num(acc): 0.8321, pseudo_num ig(acc): 0.4490, loss: 1.3945
2021-11-07 09:16:42,307 - mmdet - INFO - Iter [3600/40000] lr: 2.000e-02, eta: 19:01:12, time: 1.688, data_time: 0.025, memory: 26485, loss_rpn_cls: 0.0424, loss_rpn_bbox: 0.0569, loss_cls: 0.2591, acc: 91.4199, loss_bbox: 0.2993, loss_rpn_cls_unlabeled: 0.0984, loss_rpn_bbox_unlabeled: 0.1007, loss_cls_unlabeled: 0.2024, acc_unlabeled: 91.4788, loss_bbox_unlabeled: 0.1895, losses_cls_ig_unlabeled: 0.1583, pseudo_num: 1.5405, pseudo_num_ig: 5.5776, pseudo_num_mining: 0.5144, pseudo_num(acc): 0.8323, pseudo_num ig(acc): 0.4491, loss: 1.4069
2021-11-07 09:18:05,649 - mmdet - INFO - Iter [3650/40000] lr: 2.000e-02, eta: 18:57:53, time: 1.670, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0443, loss_rpn_bbox: 0.0581, loss_cls: 0.2577, acc: 91.4758, loss_bbox: 0.2974, loss_rpn_cls_unlabeled: 0.1081, loss_rpn_bbox_unlabeled: 0.1086, loss_cls_unlabeled: 0.1996, acc_unlabeled: 90.9573, loss_bbox_unlabeled: 0.1789, losses_cls_ig_unlabeled: 0.1771, pseudo_num: 1.5412, pseudo_num_ig: 5.5782, pseudo_num_mining: 0.5157, pseudo_num(acc): 0.8324, pseudo_num ig(acc): 0.4491, loss: 1.4297
2021-11-07 09:19:29,320 - mmdet - INFO - Iter [3700/40000] lr: 2.000e-02, eta: 18:54:38, time: 1.671, data_time: 0.029, memory: 26485, loss_rpn_cls: 0.0435, loss_rpn_bbox: 0.0539, loss_cls: 0.2481, acc: 91.7872, loss_bbox: 0.2895, loss_rpn_cls_unlabeled: 0.0964, loss_rpn_bbox_unlabeled: 0.1028, loss_cls_unlabeled: 0.1999, acc_unlabeled: 91.1508, loss_bbox_unlabeled: 0.1855, losses_cls_ig_unlabeled: 0.1731, pseudo_num: 1.5423, pseudo_num_ig: 5.5815, pseudo_num_mining: 0.5172, pseudo_num(acc): 0.8325, pseudo_num ig(acc): 0.4490, loss: 1.3926
2021-11-07 09:20:54,177 - mmdet - INFO - Iter [3750/40000] lr: 2.000e-02, eta: 18:51:37, time: 1.696, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0437, loss_rpn_bbox: 0.0567, loss_cls: 0.2599, acc: 91.3928, loss_bbox: 0.3011, loss_rpn_cls_unlabeled: 0.1029, loss_rpn_bbox_unlabeled: 0.1003, loss_cls_unlabeled: 0.1985, acc_unlabeled: 91.3177, loss_bbox_unlabeled: 0.1831, losses_cls_ig_unlabeled: 0.1683, pseudo_num: 1.5432, pseudo_num_ig: 5.5810, pseudo_num_mining: 0.5184, pseudo_num(acc): 0.8329, pseudo_num ig(acc): 0.4491, loss: 1.4145
2021-11-07 09:22:19,417 - mmdet - INFO - Iter [3800/40000] lr: 2.000e-02, eta: 18:48:43, time: 1.705, data_time: 0.032, memory: 26485, loss_rpn_cls: 0.0421, loss_rpn_bbox: 0.0537, loss_cls: 0.2405, acc: 91.9208, loss_bbox: 0.2847, loss_rpn_cls_unlabeled: 0.1031, loss_rpn_bbox_unlabeled: 0.1052, loss_cls_unlabeled: 0.1920, acc_unlabeled: 91.4072, loss_bbox_unlabeled: 0.1765, losses_cls_ig_unlabeled: 0.1646, pseudo_num: 1.5438, pseudo_num_ig: 5.5822, pseudo_num_mining: 0.5197, pseudo_num(acc): 0.8332, pseudo_num ig(acc): 0.4492, loss: 1.3623
2021-11-07 09:23:43,585 - mmdet - INFO - Iter [3850/40000] lr: 2.000e-02, eta: 18:45:43, time: 1.685, data_time: 0.034, memory: 26485, loss_rpn_cls: 0.0443, loss_rpn_bbox: 0.0543, loss_cls: 0.2532, acc: 91.7034, loss_bbox: 0.2906, loss_rpn_cls_unlabeled: 0.1066, loss_rpn_bbox_unlabeled: 0.1056, loss_cls_unlabeled: 0.2009, acc_unlabeled: 91.2905, loss_bbox_unlabeled: 0.1872, losses_cls_ig_unlabeled: 0.1692, pseudo_num: 1.5454, pseudo_num_ig: 5.5831, pseudo_num_mining: 0.5205, pseudo_num(acc): 0.8335, pseudo_num ig(acc): 0.4491, loss: 1.4118
2021-11-07 09:25:09,157 - mmdet - INFO - Iter [3900/40000] lr: 2.000e-02, eta: 18:42:56, time: 1.709, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0418, loss_rpn_bbox: 0.0536, loss_cls: 0.2527, acc: 91.7235, loss_bbox: 0.2894, loss_rpn_cls_unlabeled: 0.1016, loss_rpn_bbox_unlabeled: 0.1026, loss_cls_unlabeled: 0.2089, acc_unlabeled: 91.2278, loss_bbox_unlabeled: 0.1942, losses_cls_ig_unlabeled: 0.1621, pseudo_num: 1.5468, pseudo_num_ig: 5.5830, pseudo_num_mining: 0.5217, pseudo_num(acc): 0.8336, pseudo_num ig(acc): 0.4492, loss: 1.4069
2021-11-07 09:26:33,071 - mmdet - INFO - Iter [3950/40000] lr: 2.000e-02, eta: 18:39:57, time: 1.680, data_time: 0.029, memory: 26485, loss_rpn_cls: 0.0417, loss_rpn_bbox: 0.0538, loss_cls: 0.2487, acc: 91.8241, loss_bbox: 0.2893, loss_rpn_cls_unlabeled: 0.1047, loss_rpn_bbox_unlabeled: 0.1057, loss_cls_unlabeled: 0.2101, acc_unlabeled: 91.0717, loss_bbox_unlabeled: 0.1911, losses_cls_ig_unlabeled: 0.1707, pseudo_num: 1.5489, pseudo_num_ig: 5.5832, pseudo_num_mining: 0.5228, pseudo_num(acc): 0.8339, pseudo_num ig(acc): 0.4491, loss: 1.4158
2021-11-07 09:27:56,017 - mmdet - INFO - pseudo pos: 0.98(7756.0-person) 0.95(146.0-bicycle) 0.92(1185.0-car) 0.95(195.0-motorcycle) 0.98(145.0-airplane) 0.99(173.0-bus) 0.97(164.0-train) 0.73(314.0-truck) 0.67(349.0-boat) 0.89(394.0-traffic light) 1.00(48.0-fire hydrant) 0.96(48.0-stop sign) 0.85(41.0-parking meter) 0.65(280.0-bench) 0.91(290.0-bird) 0.95(150.0-cat) 0.98(137.0-dog) 0.98(164.0-horse) 0.94(356.0-sheep) 0.93(231.0-cow) 0.99(158.0-elephant) 0.98(48.0-bear) 0.98(133.0-zebra) 0.98(127.0-giraffe) 0.48(294.0-backpack) 0.83(344.0-umbrella) 0.43(384.0-handbag) 0.94(128.0-tie) 0.78(152.0-suitcase) 0.96(68.0-frisbee) 0.56(193.0-skis) 0.63(70.0-snowboard) 0.99(141.0-sports ball) 0.92(220.0-kite) 0.83(110.0-baseball bat) 0.96(98.0-baseball glove) 0.97(179.0-skateboard) 0.80(217.0-surfboard) 0.97(112.0-tennis racket) 0.85(648.0-bottle) 0.94(172.0-wine glass) 0.87(615.0-cup) 0.71(119.0-fork) 0.41(217.0-knife) 0.36(210.0-spoon) 0.81(515.0-bowl) 0.63(255.0-banana) 0.43(166.0-apple) 0.77(124.0-sandwich) 0.59(175.0-orange) 0.71(189.0-broccoli) 0.48(288.0-carrot) 0.67(70.0-hot dog) 0.94(209.0-pizza) 0.84(225.0-donut) 0.74(162.0-cake) 0.72(1061.0-chair) 0.77(225.0-couch) 0.71(198.0-potted plant) 0.89(123.0-bed) 0.70(588.0-dining table) 0.87(75.0-toilet) 0.97(161.0-tv) 0.98(132.0-laptop) 0.98(54.0-mouse) 0.67(170.0-remote) 0.91(75.0-keyboard) 0.84(182.0-cell phone) 0.94(52.0-microwave) 0.83(105.0-oven) 0.00(0.0-toaster) 0.77(177.0-sink) 0.82(91.0-refrigerator) 0.30(575.0-book) 0.98(119.0-clock) 0.90(196.0-vase) 0.56(63.0-scissors) 0.93(110.0-teddy bear) 0.00(0.0-hair drier) 0.06(389.0-toothbrush)
2021-11-07 09:27:56,018 - mmdet - INFO - pseudo ig: 0.61(26921.0-person) 0.46(516.0-bicycle) 0.48(4333.0-car) 0.58(842.0-motorcycle) 0.65(372.0-airplane) 0.67(542.0-bus) 0.62(416.0-train) 0.38(1046.0-truck) 0.31(1202.0-boat) 0.40(1336.0-traffic light) 0.71(177.0-fire hydrant) 0.54(220.0-stop sign) 0.40(81.0-parking meter) 0.20(980.0-bench) 0.35(1131.0-bird) 0.73(483.0-cat) 0.70(466.0-dog) 0.55(607.0-horse) 0.47(1239.0-sheep) 0.44(985.0-cow) 0.74(667.0-elephant) 0.65(135.0-bear) 0.79(501.0-zebra) 0.79(585.0-giraffe) 0.20(1016.0-backpack) 0.36(1243.0-umbrella) 0.17(1380.0-handbag) 0.43(421.0-tie) 0.35(578.0-suitcase) 0.52(265.0-frisbee) 0.30(732.0-skis) 0.28(240.0-snowboard) 0.43(664.0-sports ball) 0.46(850.0-kite) 0.31(436.0-baseball bat) 0.38(409.0-baseball glove) 0.47(500.0-skateboard) 0.34(790.0-surfboard) 0.55(607.0-tennis racket) 0.38(2428.0-bottle) 0.43(759.0-wine glass) 0.32(2718.0-cup) 0.25(584.0-fork) 0.21(730.0-knife) 0.16(699.0-spoon) 0.37(1915.0-bowl) 0.26(1080.0-banana) 0.20(754.0-apple) 0.38(361.0-sandwich) 0.23(1106.0-orange) 0.42(665.0-broccoli) 0.24(796.0-carrot) 0.31(253.0-hot dog) 0.43(663.0-pizza) 0.28(873.0-donut) 0.35(581.0-cake) 0.30(3855.0-chair) 0.34(617.0-couch) 0.37(830.0-potted plant) 0.44(364.0-bed) 0.32(1669.0-dining table) 0.76(356.0-toilet) 0.53(524.0-tv) 0.54(567.0-laptop) 0.46(215.0-mouse) 0.26(705.0-remote) 0.41(274.0-keyboard) 0.26(777.0-cell phone) 0.40(174.0-microwave) 0.29(367.0-oven) 0.00(0.0-toaster) 0.45(550.0-sink) 0.33(279.0-refrigerator) 0.16(2355.0-book) 0.66(603.0-clock) 0.34(615.0-vase) 0.23(136.0-scissors) 0.57(410.0-teddy bear) 0.00(0.0-hair drier) 0.04(571.0-toothbrush)
2021-11-07 09:27:56,018 - mmdet - INFO - pseudo gt: 34812.0 1099.0 5709.0 1155.0 650.0 859.0 588.0 1384.0 1348.0 1693.0 261.0 266.0 194.0 1321.0 1523.0 594.0 739.0 796.0 1444.0 1003.0 857.0 182.0 653.0 692.0 1188.0 1515.0 1671.0 824.0 819.0 302.0 935.0 387.0 843.0 1183.0 446.0 548.0 796.0 814.0 668.0 3232.0 1044.0 2798.0 740.0 1020.0 835.0 1992.0 1363.0 843.0 603.0 863.0 1023.0 1149.0 330.0 740.0 982.0 999.0 5069.0 790.0 1145.0 497.0 2118.0 552.0 714.0 672.0 300.0 774.0 344.0 846.0 218.0 430.0 33.0 778.0 374.0 3222.0 819.0 924.0 251.0 599.0 30.0 253.0
2021-11-07 09:27:56,018 - mmdet - INFO - pseudo mining: 4492.0 11.0 487.0 52.0 39.0 89.0 25.0 8.0 19.0 130.0 49.0 105.0 0.0 4.0 20.0 42.0 25.0 46.0 133.0 31.0 186.0 33.0 205.0 232.0 1.0 43.0 0.0 20.0 5.0 62.0 7.0 0.0 181.0 110.0 15.0 46.0 28.0 15.0 99.0 151.0 25.0 120.0 2.0 1.0 0.0 44.0 7.0 2.0 2.0 5.0 33.0 8.0 0.0 27.0 49.0 6.0 13.0 1.0 25.0 1.0 12.0 123.0 103.0 54.0 50.0 7.0 10.0 10.0 5.0 2.0 0.0 38.0 6.0 0.0 356.0 18.0 0.0 20.0 0.0 0.0
2021-11-07 09:28:51,628 - mmdet - INFO - Evaluating bbox...
2021-11-07 09:30:05,148 - mmdet - INFO -
+---------------+-------+--------------+-------+----------------+-------+
| category | AP | category | AP | category | AP |
+---------------+-------+--------------+-------+----------------+-------+
| person | 0.410 | bicycle | 0.158 | car | 0.303 |
| motorcycle | 0.239 | airplane | 0.378 | bus | 0.455 |
| train | 0.399 | truck | 0.192 | boat | 0.139 |
| traffic light | 0.198 | fire hydrant | 0.451 | stop sign | 0.473 |
| parking meter | 0.310 | bench | 0.119 | bird | 0.199 |
| cat | 0.412 | dog | 0.369 | horse | 0.358 |
| sheep | 0.288 | cow | 0.379 | elephant | 0.428 |
| bear | 0.474 | zebra | 0.460 | giraffe | 0.487 |
| backpack | 0.060 | umbrella | 0.189 | handbag | 0.042 |
| tie | 0.133 | suitcase | 0.128 | frisbee | 0.439 |
| skis | 0.083 | snowboard | 0.088 | sports ball | 0.314 |
| kite | 0.233 | baseball bat | 0.127 | baseball glove | 0.212 |
| skateboard | 0.248 | surfboard | 0.180 | tennis racket | 0.260 |
| bottle | 0.267 | wine glass | 0.224 | cup | 0.285 |
| fork | 0.089 | knife | 0.038 | spoon | 0.036 |
| bowl | 0.276 | banana | 0.114 | apple | 0.089 |
| sandwich | 0.184 | orange | 0.172 | broccoli | 0.153 |
| carrot | 0.066 | hot dog | 0.108 | pizza | 0.326 |
| donut | 0.197 | cake | 0.169 | chair | 0.122 |
| couch | 0.223 | potted plant | 0.130 | bed | 0.238 |
| dining table | 0.130 | toilet | 0.369 | tv | 0.367 |
| laptop | 0.384 | mouse | 0.404 | remote | 0.112 |
| keyboard | 0.238 | cell phone | 0.180 | microwave | 0.386 |
| oven | 0.178 | toaster | 0.024 | sink | 0.189 |
| refrigerator | 0.255 | book | 0.052 | clock | 0.363 |
| vase | 0.214 | scissors | 0.089 | teddy bear | 0.239 |
| hair drier | 0.000 | toothbrush | 0.034 | None | None |
+---------------+-------+--------------+-------+----------------+-------+
2021-11-07 09:31:02,325 - mmdet - INFO - Evaluating bbox...
2021-11-07 09:32:13,488 - mmdet - INFO -
+---------------+-------+--------------+-------+----------------+-------+
| category | AP | category | AP | category | AP |
+---------------+-------+--------------+-------+----------------+-------+
| person | 0.431 | bicycle | 0.182 | car | 0.328 |
| motorcycle | 0.267 | airplane | 0.421 | bus | 0.482 |
| train | 0.433 | truck | 0.206 | boat | 0.148 |
| traffic light | 0.219 | fire hydrant | 0.481 | stop sign | 0.511 |
| parking meter | 0.330 | bench | 0.143 | bird | 0.233 |
| cat | 0.452 | dog | 0.398 | horse | 0.404 |
| sheep | 0.334 | cow | 0.390 | elephant | 0.472 |
| bear | 0.540 | zebra | 0.501 | giraffe | 0.532 |
| backpack | 0.068 | umbrella | 0.209 | handbag | 0.052 |
| tie | 0.166 | suitcase | 0.143 | frisbee | 0.488 |
| skis | 0.101 | snowboard | 0.111 | sports ball | 0.360 |
| kite | 0.285 | baseball bat | 0.175 | baseball glove | 0.242 |
| skateboard | 0.298 | surfboard | 0.204 | tennis racket | 0.290 |
| bottle | 0.283 | wine glass | 0.230 | cup | 0.306 |
| fork | 0.085 | knife | 0.047 | spoon | 0.047 |
| bowl | 0.316 | banana | 0.134 | apple | 0.113 |
| sandwich | 0.210 | orange | 0.214 | broccoli | 0.168 |
| carrot | 0.078 | hot dog | 0.124 | pizza | 0.358 |
| donut | 0.274 | cake | 0.178 | chair | 0.135 |
| couch | 0.251 | potted plant | 0.139 | bed | 0.256 |
| dining table | 0.141 | toilet | 0.406 | tv | 0.417 |
| laptop | 0.414 | mouse | 0.468 | remote | 0.134 |
| keyboard | 0.293 | cell phone | 0.198 | microwave | 0.387 |
| oven | 0.195 | toaster | 0.095 | sink | 0.197 |
| refrigerator | 0.312 | book | 0.050 | clock | 0.388 |
| vase | 0.241 | scissors | 0.075 | teddy bear | 0.273 |
| hair drier | 0.000 | toothbrush | 0.042 | None | None |
+---------------+-------+--------------+-------+----------------+-------+
2021-11-07 09:33:37,109 - mmdet - INFO - current percent: 0.2
2021-11-07 09:33:37,110 - mmdet - INFO - update score thr (positive): (0.99-person) (0.97-bicycle) (0.98-car) (0.99-motorcycle) (0.99-airplane) (0.99-bus) (0.99-train) (0.91-truck) (0.92-boat) (0.98-traffic light) (1.00-fire hydrant) (0.99-stop sign) (0.99-parking meter) (0.90-bench) (0.96-bird) (0.99-cat) (0.98-dog) (0.98-horse) (0.96-sheep) (0.94-cow) (0.99-elephant) (0.99-bear) (1.00-zebra) (0.99-giraffe) (0.85-backpack) (0.97-umbrella) (0.76-handbag) (0.96-tie) (0.91-suitcase) (0.99-frisbee) (0.89-skis) (0.75-snowboard) (0.99-sports ball) (0.99-kite) (0.97-baseball bat) (0.99-baseball glove) (0.99-skateboard) (0.97-surfboard) (0.99-tennis racket) (0.97-bottle) (0.97-wine glass) (0.96-cup) (0.84-fork) (0.71-knife) (0.71-spoon) (0.96-bowl) (0.93-banana) (0.80-apple) (0.94-sandwich) (0.90-orange) (0.94-broccoli) (0.85-carrot) (0.78-hot dog) (0.98-pizza) (0.94-donut) (0.94-cake) (0.86-chair) (0.92-couch) (0.96-potted plant) (0.96-bed) (0.95-dining table) (0.99-toilet) (0.99-tv) (0.99-laptop) (0.99-mouse) (0.89-remote) (0.96-keyboard) (0.93-cell phone) (0.95-microwave) (0.96-oven) (0.05-toaster) (0.98-sink) (0.95-refrigerator) (0.84-book) (0.99-clock) (0.98-vase) (0.91-scissors) (0.98-teddy bear) (0.05-hair drier) (0.84-toothbrush)
2021-11-07 09:33:37,110 - mmdet - INFO - update score thr (ignore): (0.42-person) (0.45-bicycle) (0.48-car) (0.51-motorcycle) (0.56-airplane) (0.48-bus) (0.52-train) (0.41-truck) (0.37-boat) (0.42-traffic light) (0.59-fire hydrant) (0.78-stop sign) (0.39-parking meter) (0.40-bench) (0.28-bird) (0.60-cat) (0.56-dog) (0.29-horse) (0.24-sheep) (0.33-cow) (0.51-elephant) (0.56-bear) (0.70-zebra) (0.39-giraffe) (0.44-backpack) (0.38-umbrella) (0.29-handbag) (0.43-tie) (0.36-suitcase) (0.66-frisbee) (0.36-skis) (0.32-snowboard) (0.34-sports ball) (0.51-kite) (0.40-baseball bat) (0.49-baseball glove) (0.43-skateboard) (0.43-surfboard) (0.37-tennis racket) (0.45-bottle) (0.32-wine glass) (0.39-cup) (0.27-fork) (0.30-knife) (0.23-spoon) (0.48-bowl) (0.37-banana) (0.33-apple) (0.49-sandwich) (0.56-orange) (0.52-broccoli) (0.47-carrot) (0.31-hot dog) (0.48-pizza) (0.36-donut) (0.33-cake) (0.32-chair) (0.45-couch) (0.56-potted plant) (0.46-bed) (0.46-dining table) (0.52-toilet) (0.61-tv) (0.50-laptop) (0.66-mouse) (0.37-remote) (0.45-keyboard) (0.43-cell phone) (0.52-microwave) (0.53-oven) (0.05-toaster) (0.57-sink) (0.49-refrigerator) (0.39-book) (0.81-clock) (0.45-vase) (0.33-scissors) (0.56-teddy bear) (0.05-hair drier) (0.44-toothbrush)
2021-11-07 09:33:37,361 - mmdet - INFO - Exp name: labelmatch_0.9_1_5_8.py
2021-11-07 09:33:37,362 - mmdet - INFO - Iter [4000/40000] lr: 2.000e-02, eta: 18:37:09, time: 1.697, data_time: 0.031, memory: 26485, bbox_mAP: 0.2590, bbox_mAP_50: 0.4550, bbox_mAP_75: 0.2650, bbox_mAP_s: 0.1430, bbox_mAP_m: 0.2870, bbox_mAP_l: 0.3340, bbox_mAP_copypaste: 0.259 0.455 0.265 0.143 0.287 0.334, loss_rpn_cls: 0.0450, loss_rpn_bbox: 0.0567, loss_cls: 0.2605, acc: 91.4690, loss_bbox: 0.3005, loss_rpn_cls_unlabeled: 0.1019, loss_rpn_bbox_unlabeled: 0.0985, loss_cls_unlabeled: 0.1925, acc_unlabeled: 91.4033, loss_bbox_unlabeled: 0.1777, losses_cls_ig_unlabeled: 0.1661, pseudo_num: 1.5497, pseudo_num_ig: 5.5818, pseudo_num_mining: 0.5234, pseudo_num(acc): 0.8340, pseudo_num ig(acc): 0.4491, loss: 1.3993
2021-11-07 09:35:00,667 - mmdet - INFO - Iter [4050/40000] lr: 2.000e-02, eta: 19:24:21, time: 8.454, data_time: 6.818, memory: 26485, loss_rpn_cls: 0.0427, loss_rpn_bbox: 0.0544, loss_cls: 0.2513, acc: 91.6229, loss_bbox: 0.2924, loss_rpn_cls_unlabeled: 0.0946, loss_rpn_bbox_unlabeled: 0.1002, loss_cls_unlabeled: 0.1915, acc_unlabeled: 91.3182, loss_bbox_unlabeled: 0.1726, losses_cls_ig_unlabeled: 0.1704, pseudo_num: 1.5498, pseudo_num_ig: 5.5815, pseudo_num_mining: 0.5246, pseudo_num(acc): 0.8341, pseudo_num ig(acc): 0.4493, loss: 1.3701
2021-11-07 09:36:23,742 - mmdet - INFO - Iter [4100/40000] lr: 2.000e-02, eta: 19:20:42, time: 1.665, data_time: 0.031, memory: 26485, loss_rpn_cls: 0.0411, loss_rpn_bbox: 0.0548, loss_cls: 0.2497, acc: 91.7568, loss_bbox: 0.2878, loss_rpn_cls_unlabeled: 0.0973, loss_rpn_bbox_unlabeled: 0.0999, loss_cls_unlabeled: 0.1878, acc_unlabeled: 91.3873, loss_bbox_unlabeled: 0.1682, losses_cls_ig_unlabeled: 0.1767, pseudo_num: 1.5487, pseudo_num_ig: 5.5795, pseudo_num_mining: 0.5260, pseudo_num(acc): 0.8346, pseudo_num ig(acc): 0.4495, loss: 1.3635
2021-11-07 09:37:48,593 - mmdet - INFO - Iter [4150/40000] lr: 2.000e-02, eta: 19:17:19, time: 1.695, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0425, loss_rpn_bbox: 0.0547, loss_cls: 0.2500, acc: 91.7566, loss_bbox: 0.2929, loss_rpn_cls_unlabeled: 0.0950, loss_rpn_bbox_unlabeled: 0.1009, loss_cls_unlabeled: 0.1965, acc_unlabeled: 91.2673, loss_bbox_unlabeled: 0.1802, losses_cls_ig_unlabeled: 0.1659, pseudo_num: 1.5483, pseudo_num_ig: 5.5805, pseudo_num_mining: 0.5275, pseudo_num(acc): 0.8350, pseudo_num ig(acc): 0.4497, loss: 1.3787
2021-11-07 09:39:12,966 - mmdet - INFO - Iter [4200/40000] lr: 2.000e-02, eta: 19:13:57, time: 1.689, data_time: 0.031, memory: 26485, loss_rpn_cls: 0.0420, loss_rpn_bbox: 0.0538, loss_cls: 0.2469, acc: 91.7078, loss_bbox: 0.2893, loss_rpn_cls_unlabeled: 0.0976, loss_rpn_bbox_unlabeled: 0.1022, loss_cls_unlabeled: 0.1921, acc_unlabeled: 91.2909, loss_bbox_unlabeled: 0.1706, losses_cls_ig_unlabeled: 0.1739, pseudo_num: 1.5472, pseudo_num_ig: 5.5811, pseudo_num_mining: 0.5291, pseudo_num(acc): 0.8355, pseudo_num ig(acc): 0.4499, loss: 1.3684
2021-11-07 09:40:36,939 - mmdet - INFO - Iter [4250/40000] lr: 2.000e-02, eta: 19:10:31, time: 1.674, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0409, loss_rpn_bbox: 0.0536, loss_cls: 0.2465, acc: 91.7689, loss_bbox: 0.2872, loss_rpn_cls_unlabeled: 0.0996, loss_rpn_bbox_unlabeled: 0.1062, loss_cls_unlabeled: 0.1921, acc_unlabeled: 91.1130, loss_bbox_unlabeled: 0.1765, losses_cls_ig_unlabeled: 0.1769, pseudo_num: 1.5462, pseudo_num_ig: 5.5833, pseudo_num_mining: 0.5306, pseudo_num(acc): 0.8359, pseudo_num ig(acc): 0.4501, loss: 1.3794
2021-11-07 09:42:01,161 - mmdet - INFO - Iter [4300/40000] lr: 2.000e-02, eta: 19:07:14, time: 1.688, data_time: 0.036, memory: 26485, loss_rpn_cls: 0.0409, loss_rpn_bbox: 0.0524, loss_cls: 0.2486, acc: 91.8124, loss_bbox: 0.2883, loss_rpn_cls_unlabeled: 0.0997, loss_rpn_bbox_unlabeled: 0.1064, loss_cls_unlabeled: 0.1898, acc_unlabeled: 91.4005, loss_bbox_unlabeled: 0.1792, losses_cls_ig_unlabeled: 0.1656, pseudo_num: 1.5463, pseudo_num_ig: 5.5856, pseudo_num_mining: 0.5322, pseudo_num(acc): 0.8362, pseudo_num ig(acc): 0.4502, loss: 1.3709
2021-11-07 09:43:25,159 - mmdet - INFO - Iter [4350/40000] lr: 2.000e-02, eta: 19:03:56, time: 1.681, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0408, loss_rpn_bbox: 0.0546, loss_cls: 0.2473, acc: 91.8077, loss_bbox: 0.2891, loss_rpn_cls_unlabeled: 0.0967, loss_rpn_bbox_unlabeled: 0.1025, loss_cls_unlabeled: 0.1940, acc_unlabeled: 91.2697, loss_bbox_unlabeled: 0.1765, losses_cls_ig_unlabeled: 0.1720, pseudo_num: 1.5463, pseudo_num_ig: 5.5861, pseudo_num_mining: 0.5335, pseudo_num(acc): 0.8365, pseudo_num ig(acc): 0.4503, loss: 1.3734
2021-11-07 09:44:48,279 - mmdet - INFO - Iter [4400/40000] lr: 2.000e-02, eta: 19:00:33, time: 1.663, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0434, loss_rpn_bbox: 0.0548, loss_cls: 0.2482, acc: 91.8711, loss_bbox: 0.2837, loss_rpn_cls_unlabeled: 0.0982, loss_rpn_bbox_unlabeled: 0.1034, loss_cls_unlabeled: 0.1902, acc_unlabeled: 91.3748, loss_bbox_unlabeled: 0.1736, losses_cls_ig_unlabeled: 0.1708, pseudo_num: 1.5458, pseudo_num_ig: 5.5876, pseudo_num_mining: 0.5347, pseudo_num(acc): 0.8369, pseudo_num ig(acc): 0.4504, loss: 1.3663
2021-11-07 09:46:11,681 - mmdet - INFO - Iter [4450/40000] lr: 2.000e-02, eta: 18:57:16, time: 1.668, data_time: 0.026, memory: 26485, loss_rpn_cls: 0.0422, loss_rpn_bbox: 0.0572, loss_cls: 0.2465, acc: 91.8641, loss_bbox: 0.2867, loss_rpn_cls_unlabeled: 0.0963, loss_rpn_bbox_unlabeled: 0.1041, loss_cls_unlabeled: 0.1965, acc_unlabeled: 91.4329, loss_bbox_unlabeled: 0.1834, losses_cls_ig_unlabeled: 0.1627, pseudo_num: 1.5457, pseudo_num_ig: 5.5898, pseudo_num_mining: 0.5361, pseudo_num(acc): 0.8375, pseudo_num ig(acc): 0.4505, loss: 1.3756
2021-11-07 09:47:34,075 - mmdet - INFO - pseudo pos: 0.98(8748.0-person) 0.94(160.0-bicycle) 0.92(1330.0-car) 0.96(217.0-motorcycle) 0.98(161.0-airplane) 0.99(193.0-bus) 0.97(184.0-train) 0.73(352.0-truck) 0.68(388.0-boat) 0.89(438.0-traffic light) 1.00(56.0-fire hydrant) 0.96(54.0-stop sign) 0.84(44.0-parking meter) 0.65(309.0-bench) 0.92(325.0-bird) 0.95(168.0-cat) 0.98(161.0-dog) 0.97(195.0-horse) 0.93(418.0-sheep) 0.92(261.0-cow) 0.99(176.0-elephant) 0.98(53.0-bear) 0.98(148.0-zebra) 0.99(146.0-giraffe) 0.48(323.0-backpack) 0.82(385.0-umbrella) 0.44(421.0-handbag) 0.93(148.0-tie) 0.80(171.0-suitcase) 0.96(74.0-frisbee) 0.58(221.0-skis) 0.64(78.0-snowboard) 0.99(162.0-sports ball) 0.92(248.0-kite) 0.83(122.0-baseball bat) 0.96(109.0-baseball glove) 0.97(198.0-skateboard) 0.80(244.0-surfboard) 0.98(129.0-tennis racket) 0.86(718.0-bottle) 0.94(203.0-wine glass) 0.86(678.0-cup) 0.72(126.0-fork) 0.42(244.0-knife) 0.37(231.0-spoon) 0.81(569.0-bowl) 0.62(293.0-banana) 0.41(186.0-apple) 0.77(134.0-sandwich) 0.59(175.0-orange) 0.73(206.0-broccoli) 0.48(299.0-carrot) 0.68(78.0-hot dog) 0.94(231.0-pizza) 0.86(281.0-donut) 0.77(199.0-cake) 0.71(1202.0-chair) 0.77(247.0-couch) 0.70(224.0-potted plant) 0.89(137.0-bed) 0.70(647.0-dining table) 0.90(96.0-toilet) 0.97(191.0-tv) 0.99(154.0-laptop) 0.98(60.0-mouse) 0.69(187.0-remote) 0.93(95.0-keyboard) 0.84(208.0-cell phone) 0.95(55.0-microwave) 0.83(122.0-oven) 0.00(0.0-toaster) 0.79(208.0-sink) 0.82(97.0-refrigerator) 0.31(660.0-book) 0.98(132.0-clock) 0.90(222.0-vase) 0.56(63.0-scissors) 0.92(133.0-teddy bear) 0.00(0.0-hair drier) 0.06(390.0-toothbrush)
2021-11-07 09:47:34,075 - mmdet - INFO - pseudo ig: 0.61(30313.0-person) 0.46(567.0-bicycle) 0.49(4894.0-car) 0.59(935.0-motorcycle) 0.65(428.0-airplane) 0.68(627.0-bus) 0.62(479.0-train) 0.38(1150.0-truck) 0.32(1328.0-boat) 0.41(1519.0-traffic light) 0.71(199.0-fire hydrant) 0.53(240.0-stop sign) 0.43(95.0-parking meter) 0.20(1095.0-bench) 0.35(1215.0-bird) 0.73(547.0-cat) 0.70(542.0-dog) 0.54(721.0-horse) 0.46(1376.0-sheep) 0.43(1144.0-cow) 0.74(743.0-elephant) 0.65(163.0-bear) 0.79(562.0-zebra) 0.79(686.0-giraffe) 0.20(1126.0-backpack) 0.37(1408.0-umbrella) 0.17(1542.0-handbag) 0.44(479.0-tie) 0.35(677.0-suitcase) 0.54(295.0-frisbee) 0.31(874.0-skis) 0.28(260.0-snowboard) 0.42(753.0-sports ball) 0.47(916.0-kite) 0.31(475.0-baseball bat) 0.39(482.0-baseball glove) 0.47(568.0-skateboard) 0.35(899.0-surfboard) 0.56(664.0-tennis racket) 0.38(2732.0-bottle) 0.43(846.0-wine glass) 0.32(3047.0-cup) 0.26(619.0-fork) 0.20(824.0-knife) 0.16(792.0-spoon) 0.37(2111.0-bowl) 0.25(1227.0-banana) 0.20(815.0-apple) 0.37(408.0-sandwich) 0.24(1135.0-orange) 0.41(753.0-broccoli) 0.24(859.0-carrot) 0.31(290.0-hot dog) 0.44(743.0-pizza) 0.29(960.0-donut) 0.35(666.0-cake) 0.29(4344.0-chair) 0.35(741.0-couch) 0.36(941.0-potted plant) 0.44(425.0-bed) 0.32(1886.0-dining table) 0.75(408.0-toilet) 0.53(612.0-tv) 0.54(645.0-laptop) 0.48(241.0-mouse) 0.25(769.0-remote) 0.40(305.0-keyboard) 0.26(865.0-cell phone) 0.42(190.0-microwave) 0.29(404.0-oven) 0.00(0.0-toaster) 0.45(614.0-sink) 0.33(307.0-refrigerator) 0.18(2687.0-book) 0.66(670.0-clock) 0.35(722.0-vase) 0.23(155.0-scissors) 0.56(461.0-teddy bear) 0.00(0.0-hair drier) 0.05(585.0-toothbrush)
2021-11-07 09:47:34,076 - mmdet - INFO - pseudo gt: 39082.0 1210.0 6414.0 1309.0 722.0 991.0 660.0 1559.0 1491.0 1948.0 295.0 294.0 214.0 1466.0 1670.0 688.0 849.0 911.0 1597.0 1147.0 968.0 208.0 742.0 805.0 1338.0 1680.0 1899.0 932.0 966.0 345.0 1077.0 423.0 939.0 1293.0 508.0 627.0 879.0 927.0 739.0 3579.0 1169.0 3115.0 785.0 1118.0 908.0 2213.0 1514.0 948.0 659.0 971.0 1129.0 1289.0 358.0 817.0 1126.0 1147.0 5648.0 913.0 1272.0 572.0 2362.0 630.0 817.0 758.0 346.0 870.0 397.0 978.0 246.0 472.0 37.0 869.0 408.0 3762.0 914.0 1064.0 274.0 708.0 32.0 288.0
2021-11-07 09:47:34,076 - mmdet - INFO - pseudo mining: 5142.0 14.0 585.0 56.0 44.0 101.0 32.0 9.0 21.0 158.0 59.0 113.0 5.0 5.0 22.0 52.0 33.0 53.0 139.0 36.0 212.0 40.0 233.0 273.0 2.0 64.0 0.0 28.0 8.0 78.0 9.0 0.0 199.0 127.0 18.0 60.0 35.0 21.0 114.0 189.0 28.0 147.0 2.0 1.0 0.0 54.0 8.0 2.0 3.0 5.0 34.0 8.0 0.0 31.0 51.0 8.0 13.0 1.0 28.0 2.0 13.0 135.0 129.0 71.0 59.0 7.0 11.0 15.0 6.0 2.0 0.0 45.0 6.0 1.0 406.0 26.0 0.0 23.0 0.0 0.0
2021-11-07 09:47:35,489 - mmdet - INFO - Iter [4500/40000] lr: 2.000e-02, eta: 18:54:04, time: 1.675, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0417, loss_rpn_bbox: 0.0560, loss_cls: 0.2501, acc: 91.6072, loss_bbox: 0.2970, loss_rpn_cls_unlabeled: 0.0944, loss_rpn_bbox_unlabeled: 0.1018, loss_cls_unlabeled: 0.1917, acc_unlabeled: 91.2567, loss_bbox_unlabeled: 0.1799, losses_cls_ig_unlabeled: 0.1649, pseudo_num: 1.5454, pseudo_num_ig: 5.5888, pseudo_num_mining: 0.5373, pseudo_num(acc): 0.8379, pseudo_num ig(acc): 0.4507, loss: 1.3774
2021-11-07 09:49:01,048 - mmdet - INFO - Iter [4550/40000] lr: 2.000e-02, eta: 18:51:07, time: 1.711, data_time: 0.029, memory: 26485, loss_rpn_cls: 0.0413, loss_rpn_bbox: 0.0550, loss_cls: 0.2497, acc: 91.6940, loss_bbox: 0.2925, loss_rpn_cls_unlabeled: 0.0947, loss_rpn_bbox_unlabeled: 0.1015, loss_cls_unlabeled: 0.1865, acc_unlabeled: 91.4293, loss_bbox_unlabeled: 0.1741, losses_cls_ig_unlabeled: 0.1704, pseudo_num: 1.5452, pseudo_num_ig: 5.5882, pseudo_num_mining: 0.5385, pseudo_num(acc): 0.8383, pseudo_num ig(acc): 0.4509, loss: 1.3657
2021-11-07 09:50:24,917 - mmdet - INFO - Iter [4600/40000] lr: 2.000e-02, eta: 18:48:01, time: 1.679, data_time: 0.029, memory: 26485, loss_rpn_cls: 0.0404, loss_rpn_bbox: 0.0541, loss_cls: 0.2433, acc: 91.8280, loss_bbox: 0.2928, loss_rpn_cls_unlabeled: 0.0978, loss_rpn_bbox_unlabeled: 0.1003, loss_cls_unlabeled: 0.1898, acc_unlabeled: 91.3844, loss_bbox_unlabeled: 0.1798, losses_cls_ig_unlabeled: 0.1708, pseudo_num: 1.5451, pseudo_num_ig: 5.5883, pseudo_num_mining: 0.5399, pseudo_num(acc): 0.8386, pseudo_num ig(acc): 0.4510, loss: 1.3691
2021-11-07 09:51:49,965 - mmdet - INFO - Iter [4650/40000] lr: 2.000e-02, eta: 18:45:05, time: 1.700, data_time: 0.031, memory: 26485, loss_rpn_cls: 0.0423, loss_rpn_bbox: 0.0561, loss_cls: 0.2450, acc: 91.8829, loss_bbox: 0.2869, loss_rpn_cls_unlabeled: 0.0945, loss_rpn_bbox_unlabeled: 0.1030, loss_cls_unlabeled: 0.1907, acc_unlabeled: 91.2135, loss_bbox_unlabeled: 0.1756, losses_cls_ig_unlabeled: 0.1764, pseudo_num: 1.5450, pseudo_num_ig: 5.5899, pseudo_num_mining: 0.5415, pseudo_num(acc): 0.8388, pseudo_num ig(acc): 0.4511, loss: 1.3706
2021-11-07 09:53:18,016 - mmdet - INFO - Iter [4700/40000] lr: 2.000e-02, eta: 18:42:33, time: 1.760, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0401, loss_rpn_bbox: 0.0532, loss_cls: 0.2386, acc: 91.9957, loss_bbox: 0.2857, loss_rpn_cls_unlabeled: 0.0968, loss_rpn_bbox_unlabeled: 0.1020, loss_cls_unlabeled: 0.1890, acc_unlabeled: 91.3104, loss_bbox_unlabeled: 0.1665, losses_cls_ig_unlabeled: 0.1728, pseudo_num: 1.5444, pseudo_num_ig: 5.5899, pseudo_num_mining: 0.5428, pseudo_num(acc): 0.8392, pseudo_num ig(acc): 0.4511, loss: 1.3446
2021-11-07 09:54:42,565 - mmdet - INFO - Iter [4750/40000] lr: 2.000e-02, eta: 18:39:37, time: 1.691, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0392, loss_rpn_bbox: 0.0518, loss_cls: 0.2429, acc: 91.8794, loss_bbox: 0.2857, loss_rpn_cls_unlabeled: 0.0910, loss_rpn_bbox_unlabeled: 0.1011, loss_cls_unlabeled: 0.1972, acc_unlabeled: 91.1046, loss_bbox_unlabeled: 0.1789, losses_cls_ig_unlabeled: 0.1747, pseudo_num: 1.5438, pseudo_num_ig: 5.5901, pseudo_num_mining: 0.5439, pseudo_num(acc): 0.8394, pseudo_num ig(acc): 0.4512, loss: 1.3626
2021-11-07 09:56:06,943 - mmdet - INFO - Iter [4800/40000] lr: 2.000e-02, eta: 18:36:42, time: 1.688, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0380, loss_rpn_bbox: 0.0523, loss_cls: 0.2366, acc: 92.0703, loss_bbox: 0.2821, loss_rpn_cls_unlabeled: 0.0948, loss_rpn_bbox_unlabeled: 0.0995, loss_cls_unlabeled: 0.1916, acc_unlabeled: 91.3436, loss_bbox_unlabeled: 0.1713, losses_cls_ig_unlabeled: 0.1717, pseudo_num: 1.5431, pseudo_num_ig: 5.5910, pseudo_num_mining: 0.5453, pseudo_num(acc): 0.8396, pseudo_num ig(acc): 0.4512, loss: 1.3380
2021-11-07 09:57:32,581 - mmdet - INFO - Iter [4850/40000] lr: 2.000e-02, eta: 18:33:58, time: 1.713, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0414, loss_rpn_bbox: 0.0538, loss_cls: 0.2386, acc: 92.0659, loss_bbox: 0.2780, loss_rpn_cls_unlabeled: 0.0988, loss_rpn_bbox_unlabeled: 0.1005, loss_cls_unlabeled: 0.1944, acc_unlabeled: 91.3542, loss_bbox_unlabeled: 0.1778, losses_cls_ig_unlabeled: 0.1677, pseudo_num: 1.5432, pseudo_num_ig: 5.5897, pseudo_num_mining: 0.5462, pseudo_num(acc): 0.8399, pseudo_num ig(acc): 0.4513, loss: 1.3508
2021-11-07 09:58:57,807 - mmdet - INFO - Iter [4900/40000] lr: 2.000e-02, eta: 18:31:11, time: 1.701, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0399, loss_rpn_bbox: 0.0550, loss_cls: 0.2417, acc: 91.9415, loss_bbox: 0.2816, loss_rpn_cls_unlabeled: 0.0977, loss_rpn_bbox_unlabeled: 0.1020, loss_cls_unlabeled: 0.1878, acc_unlabeled: 91.4817, loss_bbox_unlabeled: 0.1740, losses_cls_ig_unlabeled: 0.1662, pseudo_num: 1.5433, pseudo_num_ig: 5.5907, pseudo_num_mining: 0.5472, pseudo_num(acc): 0.8402, pseudo_num ig(acc): 0.4513, loss: 1.3459
2021-11-07 10:00:23,439 - mmdet - INFO - Iter [4950/40000] lr: 2.000e-02, eta: 18:28:31, time: 1.716, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0425, loss_rpn_bbox: 0.0541, loss_cls: 0.2521, acc: 91.5541, loss_bbox: 0.2942, loss_rpn_cls_unlabeled: 0.0986, loss_rpn_bbox_unlabeled: 0.1033, loss_cls_unlabeled: 0.1896, acc_unlabeled: 91.4956, loss_bbox_unlabeled: 0.1788, losses_cls_ig_unlabeled: 0.1631, pseudo_num: 1.5430, pseudo_num_ig: 5.5901, pseudo_num_mining: 0.5483, pseudo_num(acc): 0.8404, pseudo_num ig(acc): 0.4513, loss: 1.3763
2021-11-07 10:01:48,203 - mmdet - INFO - pseudo pos: 0.98(9640.0-person) 0.95(172.0-bicycle) 0.92(1437.0-car) 0.96(239.0-motorcycle) 0.98(179.0-airplane) 1.00(215.0-bus) 0.97(205.0-train) 0.73(377.0-truck) 0.68(426.0-boat) 0.89(471.0-traffic light) 1.00(61.0-fire hydrant) 0.95(64.0-stop sign) 0.84(51.0-parking meter) 0.67(353.0-bench) 0.91(355.0-bird) 0.95(189.0-cat) 0.98(189.0-dog) 0.98(233.0-horse) 0.92(470.0-sheep) 0.91(301.0-cow) 1.00(201.0-elephant) 0.98(56.0-bear) 0.98(165.0-zebra) 0.99(157.0-giraffe) 0.48(342.0-backpack) 0.83(433.0-umbrella) 0.44(449.0-handbag) 0.93(165.0-tie) 0.79(192.0-suitcase) 0.96(78.0-frisbee) 0.58(250.0-skis) 0.65(82.0-snowboard) 0.98(186.0-sports ball) 0.92(278.0-kite) 0.83(134.0-baseball bat) 0.97(124.0-baseball glove) 0.98(218.0-skateboard) 0.80(261.0-surfboard) 0.98(143.0-tennis racket) 0.86(788.0-bottle) 0.94(219.0-wine glass) 0.86(740.0-cup) 0.69(142.0-fork) 0.44(275.0-knife) 0.39(244.0-spoon) 0.81(628.0-bowl) 0.63(315.0-banana) 0.42(217.0-apple) 0.78(147.0-sandwich) 0.59(187.0-orange) 0.74(225.0-broccoli) 0.48(313.0-carrot) 0.69(83.0-hot dog) 0.94(262.0-pizza) 0.84(303.0-donut) 0.77(208.0-cake) 0.71(1352.0-chair) 0.78(270.0-couch) 0.69(254.0-potted plant) 0.89(157.0-bed) 0.69(702.0-dining table) 0.89(121.0-toilet) 0.98(209.0-tv) 0.99(171.0-laptop) 0.97(65.0-mouse) 0.69(222.0-remote) 0.93(107.0-keyboard) 0.84(226.0-cell phone) 0.94(68.0-microwave) 0.85(143.0-oven) 0.00(0.0-toaster) 0.79(231.0-sink) 0.84(109.0-refrigerator) 0.30(724.0-book) 0.98(153.0-clock) 0.90(236.0-vase) 0.57(65.0-scissors) 0.93(150.0-teddy bear) 0.00(0.0-hair drier) 0.06(393.0-toothbrush)
2021-11-07 10:01:48,204 - mmdet - INFO - pseudo ig: 0.61(33562.0-person) 0.46(622.0-bicycle) 0.49(5452.0-car) 0.59(982.0-motorcycle) 0.64(483.0-airplane) 0.66(695.0-bus) 0.61(538.0-train) 0.38(1279.0-truck) 0.32(1457.0-boat) 0.41(1672.0-traffic light) 0.73(223.0-fire hydrant) 0.51(263.0-stop sign) 0.47(107.0-parking meter) 0.20(1198.0-bench) 0.36(1313.0-bird) 0.73(611.0-cat) 0.70(609.0-dog) 0.53(840.0-horse) 0.45(1552.0-sheep) 0.43(1304.0-cow) 0.74(821.0-elephant) 0.63(174.0-bear) 0.80(609.0-zebra) 0.79(765.0-giraffe) 0.20(1223.0-backpack) 0.37(1545.0-umbrella) 0.18(1668.0-handbag) 0.43(551.0-tie) 0.35(762.0-suitcase) 0.55(327.0-frisbee) 0.31(994.0-skis) 0.29(279.0-snowboard) 0.42(864.0-sports ball) 0.47(1025.0-kite) 0.30(526.0-baseball bat) 0.39(524.0-baseball glove) 0.48(644.0-skateboard) 0.37(986.0-surfboard) 0.56(737.0-tennis racket) 0.38(3085.0-bottle) 0.43(892.0-wine glass) 0.33(3379.0-cup) 0.25(681.0-fork) 0.20(914.0-knife) 0.15(896.0-spoon) 0.37(2300.0-bowl) 0.27(1312.0-banana) 0.21(898.0-apple) 0.37(457.0-sandwich) 0.24(1156.0-orange) 0.41(822.0-broccoli) 0.24(917.0-carrot) 0.31(322.0-hot dog) 0.44(830.0-pizza) 0.29(1076.0-donut) 0.36(718.0-cake) 0.29(4866.0-chair) 0.35(830.0-couch) 0.36(1031.0-potted plant) 0.46(483.0-bed) 0.31(2101.0-dining table) 0.73(456.0-toilet) 0.54(690.0-tv) 0.54(717.0-laptop) 0.49(268.0-mouse) 0.26(853.0-remote) 0.43(345.0-keyboard) 0.26(952.0-cell phone) 0.43(225.0-microwave) 0.29(461.0-oven) 0.00(0.0-toaster) 0.45(703.0-sink) 0.34(339.0-refrigerator) 0.18(2940.0-book) 0.66(734.0-clock) 0.37(807.0-vase) 0.23(160.0-scissors) 0.55(532.0-teddy bear) 0.00(0.0-hair drier) 0.05(594.0-toothbrush)
2021-11-07 10:01:48,204 - mmdet - INFO - pseudo gt: 43078.0 1295.0 7102.0 1399.0 796.0 1078.0 741.0 1699.0 1670.0 2137.0 329.0 327.0 233.0 1617.0 1832.0 786.0 962.0 1047.0 1739.0 1297.0 1088.0 223.0 809.0 887.0 1469.0 1907.0 2104.0 1041.0 1099.0 399.0 1205.0 467.0 1061.0 1465.0 563.0 693.0 970.0 1018.0 824.0 4032.0 1266.0 3449.0 851.0 1245.0 998.0 2442.0 1668.0 1086.0 708.0 1059.0 1224.0 1372.0 393.0 920.0 1259.0 1256.0 6283.0 1025.0 1421.0 646.0 2599.0 698.0 906.0 854.0 394.0 970.0 456.0 1062.0 285.0 538.0 39.0 979.0 455.0 4191.0 1017.0 1172.0 293.0 797.0 37.0 308.0
2021-11-07 10:01:48,204 - mmdet - INFO - pseudo mining: 5761.0 16.0 675.0 59.0 49.0 115.0 39.0 9.0 23.0 180.0 68.0 123.0 5.0 6.0 30.0 59.0 41.0 56.0 150.0 42.0 237.0 41.0 256.0 307.0 2.0 72.0 0.0 34.0 8.0 91.0 10.0 0.0 236.0 145.0 22.0 72.0 42.0 27.0 134.0 221.0 31.0 174.0 2.0 1.0 0.0 73.0 10.0 2.0 3.0 5.0 39.0 9.0 0.0 44.0 52.0 8.0 14.0 2.0 32.0 4.0 15.0 144.0 152.0 82.0 68.0 8.0 12.0 19.0 9.0 3.0 0.0 54.0 8.0 2.0 451.0 33.0 0.0 26.0 0.0 0.0
2021-11-07 10:03:12,946 - mmdet - INFO - current percent: 0.2
2021-11-07 10:03:12,947 - mmdet - INFO - update score thr (positive): (0.99-person) (0.96-bicycle) (0.97-car) (0.99-motorcycle) (0.99-airplane) (0.99-bus) (0.99-train) (0.93-truck) (0.92-boat) (0.97-traffic light) (1.00-fire hydrant) (1.00-stop sign) (0.99-parking meter) (0.90-bench) (0.97-bird) (0.99-cat) (0.98-dog) (0.99-horse) (0.98-sheep) (0.96-cow) (1.00-elephant) (1.00-bear) (1.00-zebra) (0.99-giraffe) (0.78-backpack) (0.95-umbrella) (0.71-handbag) (0.97-tie) (0.93-suitcase) (0.99-frisbee) (0.91-skis) (0.69-snowboard) (0.99-sports ball) (0.99-kite) (0.98-baseball bat) (0.99-baseball glove) (0.99-skateboard) (0.97-surfboard) (0.99-tennis racket) (0.97-bottle) (0.99-wine glass) (0.96-cup) (0.83-fork) (0.71-knife) (0.77-spoon) (0.96-bowl) (0.94-banana) (0.85-apple) (0.96-sandwich) (0.77-orange) (0.95-broccoli) (0.83-carrot) (0.92-hot dog) (0.99-pizza) (0.97-donut) (0.93-cake) (0.89-chair) (0.94-couch) (0.96-potted plant) (0.97-bed) (0.94-dining table) (1.00-toilet) (0.99-tv) (0.99-laptop) (0.99-mouse) (0.89-remote) (0.98-keyboard) (0.92-cell phone) (0.98-microwave) (0.97-oven) (0.05-toaster) (0.98-sink) (0.97-refrigerator) (0.80-book) (0.99-clock) (0.97-vase) (0.72-scissors) (0.98-teddy bear) (0.05-hair drier) (0.43-toothbrush)
2021-11-07 10:03:12,947 - mmdet - INFO - update score thr (ignore): (0.41-person) (0.39-bicycle) (0.42-car) (0.50-motorcycle) (0.58-airplane) (0.61-bus) (0.42-train) (0.42-truck) (0.30-boat) (0.42-traffic light) (0.56-fire hydrant) (0.88-stop sign) (0.19-parking meter) (0.35-bench) (0.26-bird) (0.61-cat) (0.63-dog) (0.43-horse) (0.34-sheep) (0.44-cow) (0.61-elephant) (0.63-bear) (0.43-zebra) (0.41-giraffe) (0.33-backpack) (0.29-umbrella) (0.27-handbag) (0.44-tie) (0.39-suitcase) (0.50-frisbee) (0.39-skis) (0.24-snowboard) (0.41-sports ball) (0.55-kite) (0.42-baseball bat) (0.56-baseball glove) (0.45-skateboard) (0.38-surfboard) (0.37-tennis racket) (0.49-bottle) (0.34-wine glass) (0.39-cup) (0.26-fork) (0.30-knife) (0.31-spoon) (0.44-bowl) (0.40-banana) (0.39-apple) (0.53-sandwich) (0.35-orange) (0.61-broccoli) (0.39-carrot) (0.44-hot dog) (0.50-pizza) (0.50-donut) (0.30-cake) (0.32-chair) (0.52-couch) (0.57-potted plant) (0.45-bed) (0.45-dining table) (0.80-toilet) (0.59-tv) (0.42-laptop) (0.56-mouse) (0.35-remote) (0.49-keyboard) (0.34-cell phone) (0.68-microwave) (0.50-oven) (0.05-toaster) (0.53-sink) (0.47-refrigerator) (0.33-book) (0.70-clock) (0.39-vase) (0.21-scissors) (0.57-teddy bear) (0.05-hair drier) (0.14-toothbrush)
2021-11-07 10:03:13,271 - mmdet - INFO - Exp name: labelmatch_0.9_1_5_8.py
2021-11-07 10:03:13,272 - mmdet - INFO - Iter [5000/40000] lr: 2.000e-02, eta: 18:25:56, time: 1.724, data_time: 0.029, memory: 26485, loss_rpn_cls: 0.0421, loss_rpn_bbox: 0.0529, loss_cls: 0.2423, acc: 92.0078, loss_bbox: 0.2853, loss_rpn_cls_unlabeled: 0.0989, loss_rpn_bbox_unlabeled: 0.1048, loss_cls_unlabeled: 0.1884, acc_unlabeled: 91.3746, loss_bbox_unlabeled: 0.1764, losses_cls_ig_unlabeled: 0.1682, pseudo_num: 1.5430, pseudo_num_ig: 5.5913, pseudo_num_mining: 0.5494, pseudo_num(acc): 0.8407, pseudo_num ig(acc): 0.4513, loss: 1.3592
2021-11-07 10:04:37,895 - mmdet - INFO - Iter [5050/40000] lr: 2.000e-02, eta: 18:32:49, time: 3.364, data_time: 1.703, memory: 26485, loss_rpn_cls: 0.0396, loss_rpn_bbox: 0.0528, loss_cls: 0.2340, acc: 92.0870, loss_bbox: 0.2823, loss_rpn_cls_unlabeled: 0.0984, loss_rpn_bbox_unlabeled: 0.1044, loss_cls_unlabeled: 0.1869, acc_unlabeled: 91.2985, loss_bbox_unlabeled: 0.1771, losses_cls_ig_unlabeled: 0.1650, pseudo_num: 1.5430, pseudo_num_ig: 5.5925, pseudo_num_mining: 0.5506, pseudo_num(acc): 0.8409, pseudo_num ig(acc): 0.4513, loss: 1.3405
2021-11-07 10:06:02,340 - mmdet - INFO - Iter [5100/40000] lr: 2.000e-02, eta: 18:29:57, time: 1.689, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0413, loss_rpn_bbox: 0.0564, loss_cls: 0.2399, acc: 91.9504, loss_bbox: 0.2856, loss_rpn_cls_unlabeled: 0.1034, loss_rpn_bbox_unlabeled: 0.1080, loss_cls_unlabeled: 0.1956, acc_unlabeled: 91.0630, loss_bbox_unlabeled: 0.1800, losses_cls_ig_unlabeled: 0.1757, pseudo_num: 1.5431, pseudo_num_ig: 5.5946, pseudo_num_mining: 0.5518, pseudo_num(acc): 0.8410, pseudo_num ig(acc): 0.4514, loss: 1.3858
2021-11-07 10:07:27,862 - mmdet - INFO - Iter [5150/40000] lr: 2.000e-02, eta: 18:27:15, time: 1.711, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0431, loss_rpn_bbox: 0.0561, loss_cls: 0.2522, acc: 91.5663, loss_bbox: 0.2989, loss_rpn_cls_unlabeled: 0.1025, loss_rpn_bbox_unlabeled: 0.1090, loss_cls_unlabeled: 0.2024, acc_unlabeled: 91.0140, loss_bbox_unlabeled: 0.1787, losses_cls_ig_unlabeled: 0.1758, pseudo_num: 1.5428, pseudo_num_ig: 5.5996, pseudo_num_mining: 0.5537, pseudo_num(acc): 0.8412, pseudo_num ig(acc): 0.4514, loss: 1.4188
2021-11-07 10:08:53,321 - mmdet - INFO - Iter [5200/40000] lr: 2.000e-02, eta: 18:24:33, time: 1.708, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0380, loss_rpn_bbox: 0.0539, loss_cls: 0.2370, acc: 92.0227, loss_bbox: 0.2811, loss_rpn_cls_unlabeled: 0.1031, loss_rpn_bbox_unlabeled: 0.1107, loss_cls_unlabeled: 0.1967, acc_unlabeled: 91.0911, loss_bbox_unlabeled: 0.1864, losses_cls_ig_unlabeled: 0.1690, pseudo_num: 1.5433, pseudo_num_ig: 5.6041, pseudo_num_mining: 0.5555, pseudo_num(acc): 0.8414, pseudo_num ig(acc): 0.4516, loss: 1.3759
2021-11-07 10:10:17,657 - mmdet - INFO - Iter [5250/40000] lr: 2.000e-02, eta: 18:21:46, time: 1.687, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0404, loss_rpn_bbox: 0.0567, loss_cls: 0.2428, acc: 91.7985, loss_bbox: 0.2904, loss_rpn_cls_unlabeled: 0.0982, loss_rpn_bbox_unlabeled: 0.1039, loss_cls_unlabeled: 0.1909, acc_unlabeled: 91.2119, loss_bbox_unlabeled: 0.1747, losses_cls_ig_unlabeled: 0.1702, pseudo_num: 1.5435, pseudo_num_ig: 5.6077, pseudo_num_mining: 0.5572, pseudo_num(acc): 0.8417, pseudo_num ig(acc): 0.4516, loss: 1.3683
2021-11-07 10:11:42,423 - mmdet - INFO - Iter [5300/40000] lr: 2.000e-02, eta: 18:19:04, time: 1.697, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0402, loss_rpn_bbox: 0.0557, loss_cls: 0.2462, acc: 91.7802, loss_bbox: 0.2915, loss_rpn_cls_unlabeled: 0.0994, loss_rpn_bbox_unlabeled: 0.1074, loss_cls_unlabeled: 0.1920, acc_unlabeled: 91.2126, loss_bbox_unlabeled: 0.1803, losses_cls_ig_unlabeled: 0.1685, pseudo_num: 1.5432, pseudo_num_ig: 5.6109, pseudo_num_mining: 0.5589, pseudo_num(acc): 0.8419, pseudo_num ig(acc): 0.4516, loss: 1.3813
2021-11-07 10:13:08,659 - mmdet - INFO - Iter [5350/40000] lr: 2.000e-02, eta: 18:16:33, time: 1.726, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0368, loss_rpn_bbox: 0.0534, loss_cls: 0.2392, acc: 91.9514, loss_bbox: 0.2858, loss_rpn_cls_unlabeled: 0.0970, loss_rpn_bbox_unlabeled: 0.1071, loss_cls_unlabeled: 0.1912, acc_unlabeled: 91.2719, loss_bbox_unlabeled: 0.1797, losses_cls_ig_unlabeled: 0.1686, pseudo_num: 1.5434, pseudo_num_ig: 5.6136, pseudo_num_mining: 0.5607, pseudo_num(acc): 0.8421, pseudo_num ig(acc): 0.4517, loss: 1.3588
2021-11-07 10:14:33,586 - mmdet - INFO - Iter [5400/40000] lr: 2.000e-02, eta: 18:13:53, time: 1.696, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0377, loss_rpn_bbox: 0.0542, loss_cls: 0.2375, acc: 92.0023, loss_bbox: 0.2852, loss_rpn_cls_unlabeled: 0.1050, loss_rpn_bbox_unlabeled: 0.1069, loss_cls_unlabeled: 0.1900, acc_unlabeled: 91.2181, loss_bbox_unlabeled: 0.1743, losses_cls_ig_unlabeled: 0.1678, pseudo_num: 1.5430, pseudo_num_ig: 5.6183, pseudo_num_mining: 0.5628, pseudo_num(acc): 0.8424, pseudo_num ig(acc): 0.4518, loss: 1.3585
2021-11-07 10:15:56,518 - mmdet - INFO - Iter [5450/40000] lr: 2.000e-02, eta: 18:11:03, time: 1.661, data_time: 0.029, memory: 26485, loss_rpn_cls: 0.0379, loss_rpn_bbox: 0.0526, loss_cls: 0.2380, acc: 92.0059, loss_bbox: 0.2876, loss_rpn_cls_unlabeled: 0.0945, loss_rpn_bbox_unlabeled: 0.1010, loss_cls_unlabeled: 0.1902, acc_unlabeled: 91.4636, loss_bbox_unlabeled: 0.1809, losses_cls_ig_unlabeled: 0.1617, pseudo_num: 1.5429, pseudo_num_ig: 5.6208, pseudo_num_mining: 0.5643, pseudo_num(acc): 0.8426, pseudo_num ig(acc): 0.4519, loss: 1.3443
2021-11-07 10:17:19,108 - mmdet - INFO - pseudo pos: 0.98(10661.0-person) 0.94(194.0-bicycle) 0.92(1586.0-car) 0.96(254.0-motorcycle) 0.98(187.0-airplane) 1.00(230.0-bus) 0.97(231.0-train) 0.74(405.0-truck) 0.69(477.0-boat) 0.90(514.0-traffic light) 1.00(64.0-fire hydrant) 0.96(67.0-stop sign) 0.83(54.0-parking meter) 0.66(401.0-bench) 0.92(393.0-bird) 0.96(202.0-cat) 0.98(210.0-dog) 0.98(250.0-horse) 0.92(489.0-sheep) 0.92(335.0-cow) 1.00(210.0-elephant) 0.98(58.0-bear) 0.98(181.0-zebra) 0.99(190.0-giraffe) 0.48(392.0-backpack) 0.83(493.0-umbrella) 0.45(493.0-handbag) 0.93(182.0-tie) 0.79(203.0-suitcase) 0.96(84.0-frisbee) 0.59(268.0-skis) 0.67(91.0-snowboard) 0.99(214.0-sports ball) 0.92(301.0-kite) 0.84(148.0-baseball bat) 0.97(140.0-baseball glove) 0.98(236.0-skateboard) 0.81(290.0-surfboard) 0.98(168.0-tennis racket) 0.86(843.0-bottle) 0.95(246.0-wine glass) 0.87(820.0-cup) 0.70(168.0-fork) 0.45(294.0-knife) 0.37(264.0-spoon) 0.82(691.0-bowl) 0.62(346.0-banana) 0.43(229.0-apple) 0.78(162.0-sandwich) 0.59(195.0-orange) 0.72(250.0-broccoli) 0.48(328.0-carrot) 0.67(91.0-hot dog) 0.94(289.0-pizza) 0.84(318.0-donut) 0.78(226.0-cake) 0.72(1472.0-chair) 0.78(287.0-couch) 0.70(287.0-potted plant) 0.90(169.0-bed) 0.69(778.0-dining table) 0.90(126.0-toilet) 0.98(223.0-tv) 0.98(190.0-laptop) 0.97(71.0-mouse) 0.69(242.0-remote) 0.93(121.0-keyboard) 0.82(257.0-cell phone) 0.95(73.0-microwave) 0.85(151.0-oven) 0.00(0.0-toaster) 0.79(249.0-sink) 0.85(111.0-refrigerator) 0.31(825.0-book) 0.98(167.0-clock) 0.91(260.0-vase) 0.57(70.0-scissors) 0.93(167.0-teddy bear) 0.00(0.0-hair drier) 0.07(400.0-toothbrush)
2021-11-07 10:17:19,109 - mmdet - INFO - pseudo ig: 0.60(37467.0-person) 0.46(750.0-bicycle) 0.49(6084.0-car) 0.59(1048.0-motorcycle) 0.65(533.0-airplane) 0.66(761.0-bus) 0.61(593.0-train) 0.37(1374.0-truck) 0.32(1656.0-boat) 0.41(1848.0-traffic light) 0.73(239.0-fire hydrant) 0.52(284.0-stop sign) 0.45(127.0-parking meter) 0.20(1361.0-bench) 0.36(1460.0-bird) 0.74(686.0-cat) 0.70(651.0-dog) 0.54(953.0-horse) 0.43(1758.0-sheep) 0.44(1421.0-cow) 0.74(881.0-elephant) 0.65(185.0-bear) 0.78(714.0-zebra) 0.79(829.0-giraffe) 0.20(1400.0-backpack) 0.37(1751.0-umbrella) 0.18(1876.0-handbag) 0.43(604.0-tie) 0.35(834.0-suitcase) 0.56(364.0-frisbee) 0.32(1083.0-skis) 0.28(307.0-snowboard) 0.42(957.0-sports ball) 0.47(1111.0-kite) 0.30(577.0-baseball bat) 0.41(569.0-baseball glove) 0.49(725.0-skateboard) 0.37(1098.0-surfboard) 0.57(816.0-tennis racket) 0.38(3288.0-bottle) 0.43(1013.0-wine glass) 0.33(3682.0-cup) 0.26(757.0-fork) 0.20(1016.0-knife) 0.16(985.0-spoon) 0.37(2522.0-bowl) 0.27(1451.0-banana) 0.21(950.0-apple) 0.37(512.0-sandwich) 0.24(1199.0-orange) 0.41(907.0-broccoli) 0.24(999.0-carrot) 0.31(344.0-hot dog) 0.45(928.0-pizza) 0.30(1197.0-donut) 0.36(799.0-cake) 0.29(5369.0-chair) 0.36(895.0-couch) 0.36(1133.0-potted plant) 0.47(549.0-bed) 0.31(2334.0-dining table) 0.74(495.0-toilet) 0.54(781.0-tv) 0.53(818.0-laptop) 0.50(292.0-mouse) 0.27(933.0-remote) 0.42(390.0-keyboard) 0.26(1061.0-cell phone) 0.43(239.0-microwave) 0.29(498.0-oven) 0.00(0.0-toaster) 0.45(765.0-sink) 0.34(369.0-refrigerator) 0.19(3339.0-book) 0.66(798.0-clock) 0.37(915.0-vase) 0.21(182.0-scissors) 0.55(564.0-teddy bear) 0.00(0.0-hair drier) 0.05(628.0-toothbrush)
2021-11-07 10:17:19,109 - mmdet - INFO - pseudo gt: 47775.0 1476.0 7835.0 1513.0 867.0 1178.0 827.0 1818.0 1898.0 2340.0 352.0 361.0 256.0 1810.0 2119.0 876.0 1051.0 1177.0 1854.0 1449.0 1153.0 244.0 932.0 979.0 1642.0 2148.0 2319.0 1140.0 1187.0 455.0 1313.0 508.0 1188.0 1613.0 615.0 767.0 1079.0 1133.0 941.0 4325.0 1399.0 3810.0 960.0 1390.0 1112.0 2681.0 1837.0 1158.0 770.0 1117.0 1341.0 1513.0 426.0 1050.0 1362.0 1360.0 7089.0 1129.0 1607.0 714.0 2874.0 755.0 1018.0 973.0 434.0 1071.0 511.0 1182.0 311.0 587.0 39.0 1047.0 489.0 4743.0 1127.0 1285.0 307.0 849.0 42.0 338.0
2021-11-07 10:17:19,109 - mmdet - INFO - pseudo mining: 6523.0 17.0 749.0 65.0 53.0 137.0 46.0 9.0 25.0 205.0 73.0 138.0 6.0 7.0 46.0 76.0 44.0 70.0 173.0 56.0 259.0 44.0 290.0 335.0 3.0 80.0 0.0 36.0 8.0 103.0 10.0 0.0 271.0 168.0 24.0 84.0 56.0 31.0 153.0 239.0 46.0 194.0 2.0 1.0 0.0 84.0 11.0 3.0 3.0 5.0 43.0 10.0 0.0 59.0 67.0 8.0 15.0 2.0 34.0 7.0 18.0 165.0 180.0 97.0 73.0 9.0 18.0 19.0 13.0 6.0 0.0 59.0 9.0 2.0 500.0 35.0 0.0 30.0 0.0 0.0
2021-11-07 10:17:20,809 - mmdet - INFO - Iter [5500/40000] lr: 2.000e-02, eta: 18:08:23, time: 1.686, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0407, loss_rpn_bbox: 0.0553, loss_cls: 0.2466, acc: 91.6765, loss_bbox: 0.2944, loss_rpn_cls_unlabeled: 0.0999, loss_rpn_bbox_unlabeled: 0.1039, loss_cls_unlabeled: 0.1897, acc_unlabeled: 91.2880, loss_bbox_unlabeled: 0.1747, losses_cls_ig_unlabeled: 0.1649, pseudo_num: 1.5427, pseudo_num_ig: 5.6204, pseudo_num_mining: 0.5656, pseudo_num(acc): 0.8428, pseudo_num ig(acc): 0.4520, loss: 1.3701
2021-11-07 10:18:44,765 - mmdet - INFO - Iter [5550/40000] lr: 2.000e-02, eta: 18:05:40, time: 1.672, data_time: 0.026, memory: 26485, loss_rpn_cls: 0.0383, loss_rpn_bbox: 0.0514, loss_cls: 0.2312, acc: 92.1627, loss_bbox: 0.2775, loss_rpn_cls_unlabeled: 0.0977, loss_rpn_bbox_unlabeled: 0.0998, loss_cls_unlabeled: 0.1848, acc_unlabeled: 91.4358, loss_bbox_unlabeled: 0.1766, losses_cls_ig_unlabeled: 0.1666, pseudo_num: 1.5425, pseudo_num_ig: 5.6216, pseudo_num_mining: 0.5671, pseudo_num(acc): 0.8429, pseudo_num ig(acc): 0.4520, loss: 1.3238
2021-11-07 10:20:10,044 - mmdet - INFO - Iter [5600/40000] lr: 2.000e-02, eta: 18:03:10, time: 1.710, data_time: 0.033, memory: 26485, loss_rpn_cls: 0.0375, loss_rpn_bbox: 0.0545, loss_cls: 0.2348, acc: 92.0776, loss_bbox: 0.2858, loss_rpn_cls_unlabeled: 0.1014, loss_rpn_bbox_unlabeled: 0.1069, loss_cls_unlabeled: 0.1920, acc_unlabeled: 91.4368, loss_bbox_unlabeled: 0.1800, losses_cls_ig_unlabeled: 0.1639, pseudo_num: 1.5422, pseudo_num_ig: 5.6221, pseudo_num_mining: 0.5686, pseudo_num(acc): 0.8431, pseudo_num ig(acc): 0.4520, loss: 1.3568
2021-11-07 10:21:35,465 - mmdet - INFO - Iter [5650/40000] lr: 2.000e-02, eta: 18:00:41, time: 1.710, data_time: 0.029, memory: 26485, loss_rpn_cls: 0.0382, loss_rpn_bbox: 0.0550, loss_cls: 0.2355, acc: 91.9358, loss_bbox: 0.2902, loss_rpn_cls_unlabeled: 0.0975, loss_rpn_bbox_unlabeled: 0.1034, loss_cls_unlabeled: 0.1914, acc_unlabeled: 91.2213, loss_bbox_unlabeled: 0.1814, losses_cls_ig_unlabeled: 0.1679, pseudo_num: 1.5423, pseudo_num_ig: 5.6242, pseudo_num_mining: 0.5700, pseudo_num(acc): 0.8432, pseudo_num ig(acc): 0.4520, loss: 1.3606
2021-11-07 10:23:00,357 - mmdet - INFO - Iter [5700/40000] lr: 2.000e-02, eta: 17:58:09, time: 1.696, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0367, loss_rpn_bbox: 0.0507, loss_cls: 0.2274, acc: 92.2523, loss_bbox: 0.2793, loss_rpn_cls_unlabeled: 0.0895, loss_rpn_bbox_unlabeled: 0.0968, loss_cls_unlabeled: 0.1873, acc_unlabeled: 91.5426, loss_bbox_unlabeled: 0.1778, losses_cls_ig_unlabeled: 0.1612, pseudo_num: 1.5423, pseudo_num_ig: 5.6235, pseudo_num_mining: 0.5710, pseudo_num(acc): 0.8434, pseudo_num ig(acc): 0.4521, loss: 1.3067
2021-11-07 10:24:23,490 - mmdet - INFO - Iter [5750/40000] lr: 2.000e-02, eta: 17:55:28, time: 1.662, data_time: 0.033, memory: 26485, loss_rpn_cls: 0.0378, loss_rpn_bbox: 0.0505, loss_cls: 0.2333, acc: 92.1320, loss_bbox: 0.2786, loss_rpn_cls_unlabeled: 0.0957, loss_rpn_bbox_unlabeled: 0.1025, loss_cls_unlabeled: 0.1917, acc_unlabeled: 91.3721, loss_bbox_unlabeled: 0.1785, losses_cls_ig_unlabeled: 0.1654, pseudo_num: 1.5423, pseudo_num_ig: 5.6228, pseudo_num_mining: 0.5719, pseudo_num(acc): 0.8436, pseudo_num ig(acc): 0.4522, loss: 1.3339
2021-11-07 10:25:47,131 - mmdet - INFO - Iter [5800/40000] lr: 2.000e-02, eta: 17:52:52, time: 1.676, data_time: 0.032, memory: 26485, loss_rpn_cls: 0.0379, loss_rpn_bbox: 0.0537, loss_cls: 0.2368, acc: 92.0228, loss_bbox: 0.2855, loss_rpn_cls_unlabeled: 0.0953, loss_rpn_bbox_unlabeled: 0.1014, loss_cls_unlabeled: 0.1954, acc_unlabeled: 91.5074, loss_bbox_unlabeled: 0.1825, losses_cls_ig_unlabeled: 0.1601, pseudo_num: 1.5422, pseudo_num_ig: 5.6232, pseudo_num_mining: 0.5729, pseudo_num(acc): 0.8436, pseudo_num ig(acc): 0.4522, loss: 1.3486
2021-11-07 10:27:10,063 - mmdet - INFO - Iter [5850/40000] lr: 2.000e-02, eta: 17:50:12, time: 1.655, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0374, loss_rpn_bbox: 0.0504, loss_cls: 0.2274, acc: 92.3691, loss_bbox: 0.2710, loss_rpn_cls_unlabeled: 0.0981, loss_rpn_bbox_unlabeled: 0.1035, loss_cls_unlabeled: 0.1950, acc_unlabeled: 91.2665, loss_bbox_unlabeled: 0.1905, losses_cls_ig_unlabeled: 0.1666, pseudo_num: 1.5426, pseudo_num_ig: 5.6230, pseudo_num_mining: 0.5739, pseudo_num(acc): 0.8437, pseudo_num ig(acc): 0.4523, loss: 1.3398
2021-11-07 10:28:34,381 - mmdet - INFO - Iter [5900/40000] lr: 2.000e-02, eta: 17:47:42, time: 1.687, data_time: 0.035, memory: 26485, loss_rpn_cls: 0.0408, loss_rpn_bbox: 0.0519, loss_cls: 0.2370, acc: 92.0806, loss_bbox: 0.2777, loss_rpn_cls_unlabeled: 0.1050, loss_rpn_bbox_unlabeled: 0.1042, loss_cls_unlabeled: 0.2013, acc_unlabeled: 91.0386, loss_bbox_unlabeled: 0.1838, losses_cls_ig_unlabeled: 0.1726, pseudo_num: 1.5430, pseudo_num_ig: 5.6241, pseudo_num_mining: 0.5752, pseudo_num(acc): 0.8439, pseudo_num ig(acc): 0.4523, loss: 1.3743
2021-11-07 10:30:00,535 - mmdet - INFO - Iter [5950/40000] lr: 2.000e-02, eta: 17:45:23, time: 1.723, data_time: 0.031, memory: 26485, loss_rpn_cls: 0.0370, loss_rpn_bbox: 0.0529, loss_cls: 0.2359, acc: 92.0104, loss_bbox: 0.2847, loss_rpn_cls_unlabeled: 0.0902, loss_rpn_bbox_unlabeled: 0.1020, loss_cls_unlabeled: 0.1906, acc_unlabeled: 91.3062, loss_bbox_unlabeled: 0.1777, losses_cls_ig_unlabeled: 0.1652, pseudo_num: 1.5434, pseudo_num_ig: 5.6259, pseudo_num_mining: 0.5761, pseudo_num(acc): 0.8440, pseudo_num ig(acc): 0.4523, loss: 1.3362
2021-11-07 10:31:23,669 - mmdet - INFO - pseudo pos: 0.98(11678.0-person) 0.93(220.0-bicycle) 0.92(1755.0-car) 0.97(279.0-motorcycle) 0.98(206.0-airplane) 1.00(242.0-bus) 0.98(255.0-train) 0.75(439.0-truck) 0.70(540.0-boat) 0.90(554.0-traffic light) 1.00(70.0-fire hydrant) 0.96(70.0-stop sign) 0.84(56.0-parking meter) 0.65(447.0-bench) 0.92(426.0-bird) 0.96(222.0-cat) 0.98(232.0-dog) 0.98(275.0-horse) 0.92(525.0-sheep) 0.92(375.0-cow) 1.00(218.0-elephant) 0.98(63.0-bear) 0.99(207.0-zebra) 0.99(216.0-giraffe) 0.48(440.0-backpack) 0.84(541.0-umbrella) 0.44(540.0-handbag) 0.93(201.0-tie) 0.79(236.0-suitcase) 0.97(99.0-frisbee) 0.62(294.0-skis) 0.67(96.0-snowboard) 0.99(234.0-sports ball) 0.92(321.0-kite) 0.86(162.0-baseball bat) 0.97(147.0-baseball glove) 0.98(252.0-skateboard) 0.81(310.0-surfboard) 0.98(187.0-tennis racket) 0.87(922.0-bottle) 0.93(269.0-wine glass) 0.87(922.0-cup) 0.71(185.0-fork) 0.46(342.0-knife) 0.37(282.0-spoon) 0.82(737.0-bowl) 0.63(364.0-banana) 0.44(241.0-apple) 0.79(178.0-sandwich) 0.54(241.0-orange) 0.73(280.0-broccoli) 0.47(336.0-carrot) 0.70(102.0-hot dog) 0.94(308.0-pizza) 0.85(344.0-donut) 0.79(245.0-cake) 0.72(1606.0-chair) 0.78(300.0-couch) 0.71(308.0-potted plant) 0.90(183.0-bed) 0.70(856.0-dining table) 0.90(127.0-toilet) 0.98(242.0-tv) 0.99(208.0-laptop) 0.97(77.0-mouse) 0.70(264.0-remote) 0.93(134.0-keyboard) 0.81(285.0-cell phone) 0.95(74.0-microwave) 0.85(164.0-oven) 0.00(0.0-toaster) 0.80(275.0-sink) 0.85(117.0-refrigerator) 0.31(899.0-book) 0.98(179.0-clock) 0.90(282.0-vase) 0.56(71.0-scissors) 0.93(182.0-teddy bear) 0.00(0.0-hair drier) 0.09(423.0-toothbrush)
2021-11-07 10:31:23,670 - mmdet - INFO - pseudo ig: 0.60(40899.0-person) 0.46(826.0-bicycle) 0.49(6756.0-car) 0.59(1157.0-motorcycle) 0.65(605.0-airplane) 0.67(842.0-bus) 0.61(679.0-train) 0.37(1501.0-truck) 0.31(1877.0-boat) 0.40(2020.0-traffic light) 0.73(254.0-fire hydrant) 0.55(310.0-stop sign) 0.45(151.0-parking meter) 0.19(1490.0-bench) 0.36(1652.0-bird) 0.75(737.0-cat) 0.70(717.0-dog) 0.55(1036.0-horse) 0.44(1884.0-sheep) 0.45(1590.0-cow) 0.74(940.0-elephant) 0.65(196.0-bear) 0.78(790.0-zebra) 0.78(884.0-giraffe) 0.20(1541.0-backpack) 0.37(1934.0-umbrella) 0.18(2035.0-handbag) 0.43(674.0-tie) 0.34(933.0-suitcase) 0.56(386.0-frisbee) 0.32(1145.0-skis) 0.26(354.0-snowboard) 0.43(1044.0-sports ball) 0.47(1255.0-kite) 0.30(642.0-baseball bat) 0.42(611.0-baseball glove) 0.49(777.0-skateboard) 0.38(1214.0-surfboard) 0.57(894.0-tennis racket) 0.39(3624.0-bottle) 0.44(1115.0-wine glass) 0.33(3994.0-cup) 0.26(825.0-fork) 0.19(1139.0-knife) 0.16(1055.0-spoon) 0.37(2708.0-bowl) 0.27(1561.0-banana) 0.21(982.0-apple) 0.36(576.0-sandwich) 0.24(1256.0-orange) 0.41(974.0-broccoli) 0.23(1096.0-carrot) 0.32(379.0-hot dog) 0.46(1014.0-pizza) 0.30(1246.0-donut) 0.36(860.0-cake) 0.29(5833.0-chair) 0.37(959.0-couch) 0.36(1226.0-potted plant) 0.47(610.0-bed) 0.31(2546.0-dining table) 0.75(543.0-toilet) 0.55(878.0-tv) 0.53(902.0-laptop) 0.50(329.0-mouse) 0.28(1042.0-remote) 0.43(453.0-keyboard) 0.26(1199.0-cell phone) 0.44(259.0-microwave) 0.30(546.0-oven) 0.00(0.0-toaster) 0.45(833.0-sink) 0.35(399.0-refrigerator) 0.18(3652.0-book) 0.66(859.0-clock) 0.36(984.0-vase) 0.20(208.0-scissors) 0.54(619.0-teddy bear) 0.00(0.0-hair drier) 0.05(697.0-toothbrush)
2021-11-07 10:31:23,670 - mmdet - INFO - pseudo gt: 52019.0 1575.0 8662.0 1692.0 967.0 1286.0 920.0 2026.0 2081.0 2572.0 374.0 402.0 277.0 1962.0 2342.0 953.0 1146.0 1303.0 2041.0 1633.0 1222.0 258.0 1026.0 1055.0 1798.0 2377.0 2508.0 1237.0 1298.0 496.0 1424.0 533.0 1283.0 1767.0 672.0 827.0 1171.0 1241.0 1035.0 4782.0 1549.0 4141.0 1073.0 1524.0 1203.0 2852.0 1973.0 1197.0 845.0 1196.0 1459.0 1598.0 457.0 1167.0 1427.0 1460.0 7662.0 1232.0 1757.0 789.0 3126.0 827.0 1126.0 1054.0 473.0 1194.0 578.0 1288.0 340.0 636.0 46.0 1149.0 519.0 5145.0 1213.0 1378.0 323.0 925.0 45.0 380.0
2021-11-07 10:31:23,671 - mmdet - INFO - pseudo mining: 7246.0 20.0 827.0 77.0 68.0 168.0 49.0 12.0 27.0 218.0 81.0 162.0 6.0 7.0 59.0 86.0 55.0 85.0 183.0 72.0 289.0 46.0 320.0 355.0 4.0 85.0 0.0 41.0 11.0 111.0 12.0 0.0 297.0 204.0 25.0 94.0 65.0 34.0 170.0 281.0 54.0 205.0 2.0 1.0 0.0 98.0 15.0 3.0 6.0 5.0 44.0 10.0 2.0 70.0 73.0 9.0 17.0 6.0 35.0 7.0 21.0 188.0 212.0 107.0 79.0 15.0 23.0 19.0 15.0 7.0 0.0 64.0 9.0 2.0 539.0 37.0 0.0 32.0 0.0 0.0
2021-11-07 10:32:19,358 - mmdet - INFO - Evaluating bbox...
2021-11-07 10:33:29,346 - mmdet - INFO -
+---------------+-------+--------------+-------+----------------+-------+
| category | AP | category | AP | category | AP |
+---------------+-------+--------------+-------+----------------+-------+
| person | 0.408 | bicycle | 0.173 | car | 0.299 |
| motorcycle | 0.263 | airplane | 0.384 | bus | 0.452 |
| train | 0.371 | truck | 0.184 | boat | 0.118 |
| traffic light | 0.196 | fire hydrant | 0.502 | stop sign | 0.478 |
| parking meter | 0.302 | bench | 0.116 | bird | 0.198 |
| cat | 0.365 | dog | 0.320 | horse | 0.370 |
| sheep | 0.316 | cow | 0.361 | elephant | 0.435 |
| bear | 0.458 | zebra | 0.487 | giraffe | 0.505 |
| backpack | 0.063 | umbrella | 0.197 | handbag | 0.048 |
| tie | 0.157 | suitcase | 0.137 | frisbee | 0.414 |
| skis | 0.100 | snowboard | 0.101 | sports ball | 0.347 |
| kite | 0.254 | baseball bat | 0.137 | baseball glove | 0.225 |
| skateboard | 0.263 | surfboard | 0.181 | tennis racket | 0.291 |
| bottle | 0.259 | wine glass | 0.204 | cup | 0.257 |
| fork | 0.069 | knife | 0.036 | spoon | 0.042 |
| bowl | 0.267 | banana | 0.106 | apple | 0.095 |
| sandwich | 0.178 | orange | 0.187 | broccoli | 0.149 |
| carrot | 0.073 | hot dog | 0.115 | pizza | 0.336 |
| donut | 0.228 | cake | 0.155 | chair | 0.106 |
| couch | 0.243 | potted plant | 0.133 | bed | 0.259 |
| dining table | 0.145 | toilet | 0.376 | tv | 0.364 |
| laptop | 0.378 | mouse | 0.395 | remote | 0.124 |
| keyboard | 0.301 | cell phone | 0.192 | microwave | 0.368 |
| oven | 0.186 | toaster | 0.095 | sink | 0.188 |
| refrigerator | 0.290 | book | 0.048 | clock | 0.373 |
| vase | 0.236 | scissors | 0.056 | teddy bear | 0.233 |
| hair drier | 0.000 | toothbrush | 0.057 | None | None |
+---------------+-------+--------------+-------+----------------+-------+
2021-11-07 10:34:25,400 - mmdet - INFO - Evaluating bbox...
2021-11-07 10:35:36,744 - mmdet - INFO -
+---------------+-------+--------------+-------+----------------+-------+
| category | AP | category | AP | category | AP |
+---------------+-------+--------------+-------+----------------+-------+
| person | 0.440 | bicycle | 0.195 | car | 0.338 |
| motorcycle | 0.279 | airplane | 0.418 | bus | 0.498 |
| train | 0.432 | truck | 0.219 | boat | 0.155 |
| traffic light | 0.212 | fire hydrant | 0.505 | stop sign | 0.498 |
| parking meter | 0.367 | bench | 0.146 | bird | 0.239 |
| cat | 0.475 | dog | 0.421 | horse | 0.421 |
| sheep | 0.349 | cow | 0.413 | elephant | 0.489 |
| bear | 0.563 | zebra | 0.514 | giraffe | 0.539 |
| backpack | 0.073 | umbrella | 0.225 | handbag | 0.062 |
| tie | 0.180 | suitcase | 0.155 | frisbee | 0.494 |
| skis | 0.108 | snowboard | 0.133 | sports ball | 0.367 |
| kite | 0.293 | baseball bat | 0.181 | baseball glove | 0.256 |
| skateboard | 0.321 | surfboard | 0.219 | tennis racket | 0.320 |
| bottle | 0.292 | wine glass | 0.240 | cup | 0.311 |
| fork | 0.116 | knife | 0.064 | spoon | 0.053 |
| bowl | 0.325 | banana | 0.139 | apple | 0.117 |
| sandwich | 0.232 | orange | 0.219 | broccoli | 0.175 |
| carrot | 0.075 | hot dog | 0.119 | pizza | 0.387 |
| donut | 0.290 | cake | 0.193 | chair | 0.146 |
| couch | 0.269 | potted plant | 0.151 | bed | 0.273 |
| dining table | 0.154 | toilet | 0.439 | tv | 0.430 |
| laptop | 0.448 | mouse | 0.482 | remote | 0.136 |
| keyboard | 0.331 | cell phone | 0.223 | microwave | 0.413 |
| oven | 0.213 | toaster | 0.132 | sink | 0.223 |
| refrigerator | 0.339 | book | 0.049 | clock | 0.394 |
| vase | 0.264 | scissors | 0.106 | teddy bear | 0.289 |
| hair drier | 0.000 | toothbrush | 0.060 | None | None |
+---------------+-------+--------------+-------+----------------+-------+
2021-11-07 10:37:02,459 - mmdet - INFO - current percent: 0.2
2021-11-07 10:37:02,699 - mmdet - INFO - update score thr (positive): (0.99-person) (0.98-bicycle) (0.98-car) (0.99-motorcycle) (0.99-airplane) (0.99-bus) (0.99-train) (0.93-truck) (0.96-boat) (0.98-traffic light) (1.00-fire hydrant) (1.00-stop sign) (0.99-parking meter) (0.93-bench) (0.98-bird) (0.98-cat) (0.99-dog) (0.99-horse) (0.98-sheep) (0.96-cow) (0.99-elephant) (1.00-bear) (1.00-zebra) (1.00-giraffe) (0.84-backpack) (0.98-umbrella) (0.79-handbag) (0.98-tie) (0.94-suitcase) (1.00-frisbee) (0.92-skis) (0.80-snowboard) (0.99-sports ball) (0.99-kite) (0.98-baseball bat) (0.99-baseball glove) (0.99-skateboard) (0.97-surfboard) (0.99-tennis racket) (0.98-bottle) (0.99-wine glass) (0.97-cup) (0.84-fork) (0.79-knife) (0.80-spoon) (0.96-bowl) (0.92-banana) (0.91-apple) (0.96-sandwich) (0.88-orange) (0.94-broccoli) (0.84-carrot) (0.86-hot dog) (0.98-pizza) (0.99-donut) (0.91-cake) (0.90-chair) (0.91-couch) (0.96-potted plant) (0.97-bed) (0.96-dining table) (1.00-toilet) (0.99-tv) (0.99-laptop) (0.99-mouse) (0.93-remote) (0.98-keyboard) (0.96-cell phone) (0.96-microwave) (0.96-oven) (0.05-toaster) (0.99-sink) (0.97-refrigerator) (0.83-book) (0.99-clock) (0.98-vase) (0.94-scissors) (0.99-teddy bear) (0.05-hair drier) (0.74-toothbrush)
2021-11-07 10:37:02,700 - mmdet - INFO - update score thr (ignore): (0.42-person) (0.41-bicycle) (0.50-car) (0.49-motorcycle) (0.42-airplane) (0.56-bus) (0.42-train) (0.38-truck) (0.38-boat) (0.44-traffic light) (0.46-fire hydrant) (0.73-stop sign) (0.20-parking meter) (0.40-bench) (0.24-bird) (0.49-cat) (0.63-dog) (0.49-horse) (0.35-sheep) (0.38-cow) (0.75-elephant) (0.75-bear) (0.57-zebra) (0.75-giraffe) (0.41-backpack) (0.36-umbrella) (0.28-handbag) (0.46-tie) (0.40-suitcase) (0.59-frisbee) (0.36-skis) (0.33-snowboard) (0.32-sports ball) (0.58-kite) (0.49-baseball bat) (0.42-baseball glove) (0.38-skateboard) (0.36-surfboard) (0.54-tennis racket) (0.47-bottle) (0.33-wine glass) (0.34-cup) (0.25-fork) (0.39-knife) (0.29-spoon) (0.40-bowl) (0.40-banana) (0.43-apple) (0.54-sandwich) (0.39-orange) (0.54-broccoli) (0.38-carrot) (0.35-hot dog) (0.52-pizza) (0.63-donut) (0.31-cake) (0.33-chair) (0.48-couch) (0.56-potted plant) (0.57-bed) (0.49-dining table) (0.67-toilet) (0.63-tv) (0.52-laptop) (0.75-mouse) (0.35-remote) (0.56-keyboard) (0.45-cell phone) (0.48-microwave) (0.43-oven) (0.05-toaster) (0.55-sink) (0.49-refrigerator) (0.34-book) (0.53-clock) (0.41-vase) (0.35-scissors) (0.47-teddy bear) (0.05-hair drier) (0.33-toothbrush)
2021-11-07 10:37:03,072 - mmdet - INFO - Exp name: labelmatch_0.9_1_5_8.py
2021-11-07 10:37:03,073 - mmdet - INFO - Iter [6000/40000] lr: 2.000e-02, eta: 17:42:57, time: 1.694, data_time: 0.030, memory: 26485, bbox_mAP: 0.2730, bbox_mAP_50: 0.4710, bbox_mAP_75: 0.2820, bbox_mAP_s: 0.1520, bbox_mAP_m: 0.3040, bbox_mAP_l: 0.3530, bbox_mAP_copypaste: 0.273 0.471 0.282 0.152 0.304 0.353, loss_rpn_cls: 0.0419, loss_rpn_bbox: 0.0551, loss_cls: 0.2387, acc: 91.9097, loss_bbox: 0.2899, loss_rpn_cls_unlabeled: 0.1026, loss_rpn_bbox_unlabeled: 0.1028, loss_cls_unlabeled: 0.1929, acc_unlabeled: 91.4281, loss_bbox_unlabeled: 0.1880, losses_cls_ig_unlabeled: 0.1632, pseudo_num: 1.5438, pseudo_num_ig: 5.6259, pseudo_num_mining: 0.5771, pseudo_num(acc): 0.8442, pseudo_num ig(acc): 0.4524, loss: 1.3750
2021-11-07 10:38:26,588 - mmdet - INFO - Iter [6050/40000] lr: 2.000e-02, eta: 18:12:03, time: 8.430, data_time: 6.788, memory: 26485, loss_rpn_cls: 0.0397, loss_rpn_bbox: 0.0530, loss_cls: 0.2401, acc: 91.8577, loss_bbox: 0.2890, loss_rpn_cls_unlabeled: 0.0911, loss_rpn_bbox_unlabeled: 0.0983, loss_cls_unlabeled: 0.1811, acc_unlabeled: 91.6461, loss_bbox_unlabeled: 0.1714, losses_cls_ig_unlabeled: 0.1666, pseudo_num: 1.5436, pseudo_num_ig: 5.6267, pseudo_num_mining: 0.5787, pseudo_num(acc): 0.8444, pseudo_num ig(acc): 0.4525, loss: 1.3304
2021-11-07 10:39:50,967 - mmdet - INFO - Iter [6100/40000] lr: 2.000e-02, eta: 18:09:18, time: 1.684, data_time: 0.029, memory: 26485, loss_rpn_cls: 0.0352, loss_rpn_bbox: 0.0505, loss_cls: 0.2273, acc: 92.3252, loss_bbox: 0.2759, loss_rpn_cls_unlabeled: 0.0898, loss_rpn_bbox_unlabeled: 0.0968, loss_cls_unlabeled: 0.1845, acc_unlabeled: 91.4901, loss_bbox_unlabeled: 0.1692, losses_cls_ig_unlabeled: 0.1685, pseudo_num: 1.5425, pseudo_num_ig: 5.6261, pseudo_num_mining: 0.5796, pseudo_num(acc): 0.8447, pseudo_num ig(acc): 0.4526, loss: 1.2976
2021-11-07 10:41:16,391 - mmdet - INFO - Iter [6150/40000] lr: 2.000e-02, eta: 18:06:42, time: 1.712, data_time: 0.032, memory: 26485, loss_rpn_cls: 0.0385, loss_rpn_bbox: 0.0521, loss_cls: 0.2301, acc: 92.1412, loss_bbox: 0.2825, loss_rpn_cls_unlabeled: 0.0920, loss_rpn_bbox_unlabeled: 0.0990, loss_cls_unlabeled: 0.1802, acc_unlabeled: 91.6390, loss_bbox_unlabeled: 0.1728, losses_cls_ig_unlabeled: 0.1629, pseudo_num: 1.5416, pseudo_num_ig: 5.6259, pseudo_num_mining: 0.5811, pseudo_num(acc): 0.8450, pseudo_num ig(acc): 0.4528, loss: 1.3100
2021-11-07 10:42:43,425 - mmdet - INFO - Iter [6200/40000] lr: 2.000e-02, eta: 18:04:14, time: 1.738, data_time: 0.029, memory: 26485, loss_rpn_cls: 0.0390, loss_rpn_bbox: 0.0515, loss_cls: 0.2349, acc: 92.0220, loss_bbox: 0.2786, loss_rpn_cls_unlabeled: 0.0921, loss_rpn_bbox_unlabeled: 0.0975, loss_cls_unlabeled: 0.1903, acc_unlabeled: 91.3560, loss_bbox_unlabeled: 0.1740, losses_cls_ig_unlabeled: 0.1710, pseudo_num: 1.5410, pseudo_num_ig: 5.6263, pseudo_num_mining: 0.5827, pseudo_num(acc): 0.8453, pseudo_num ig(acc): 0.4530, loss: 1.3289
2021-11-07 10:44:07,611 - mmdet - INFO - Iter [6250/40000] lr: 2.000e-02, eta: 18:01:34, time: 1.687, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0370, loss_rpn_bbox: 0.0536, loss_cls: 0.2308, acc: 92.1466, loss_bbox: 0.2793, loss_rpn_cls_unlabeled: 0.0929, loss_rpn_bbox_unlabeled: 0.0960, loss_cls_unlabeled: 0.1842, acc_unlabeled: 91.5237, loss_bbox_unlabeled: 0.1679, losses_cls_ig_unlabeled: 0.1664, pseudo_num: 1.5399, pseudo_num_ig: 5.6264, pseudo_num_mining: 0.5840, pseudo_num(acc): 0.8455, pseudo_num ig(acc): 0.4531, loss: 1.3082
2021-11-07 10:45:31,627 - mmdet - INFO - Iter [6300/40000] lr: 2.000e-02, eta: 17:58:52, time: 1.678, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0390, loss_rpn_bbox: 0.0553, loss_cls: 0.2391, acc: 91.8824, loss_bbox: 0.2856, loss_rpn_cls_unlabeled: 0.0975, loss_rpn_bbox_unlabeled: 0.0976, loss_cls_unlabeled: 0.1825, acc_unlabeled: 91.5321, loss_bbox_unlabeled: 0.1671, losses_cls_ig_unlabeled: 0.1656, pseudo_num: 1.5390, pseudo_num_ig: 5.6266, pseudo_num_mining: 0.5853, pseudo_num(acc): 0.8457, pseudo_num ig(acc): 0.4533, loss: 1.3293
2021-11-07 10:46:55,321 - mmdet - INFO - Iter [6350/40000] lr: 2.000e-02, eta: 17:56:11, time: 1.674, data_time: 0.031, memory: 26485, loss_rpn_cls: 0.0406, loss_rpn_bbox: 0.0535, loss_cls: 0.2366, acc: 92.0264, loss_bbox: 0.2794, loss_rpn_cls_unlabeled: 0.0900, loss_rpn_bbox_unlabeled: 0.0964, loss_cls_unlabeled: 0.1721, acc_unlabeled: 91.7637, loss_bbox_unlabeled: 0.1596, losses_cls_ig_unlabeled: 0.1651, pseudo_num: 1.5379, pseudo_num_ig: 5.6265, pseudo_num_mining: 0.5867, pseudo_num(acc): 0.8459, pseudo_num ig(acc): 0.4534, loss: 1.2934
2021-11-07 10:48:20,184 - mmdet - INFO - Iter [6400/40000] lr: 2.000e-02, eta: 17:53:37, time: 1.697, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0374, loss_rpn_bbox: 0.0548, loss_cls: 0.2349, acc: 91.9457, loss_bbox: 0.2854, loss_rpn_cls_unlabeled: 0.0957, loss_rpn_bbox_unlabeled: 0.0990, loss_cls_unlabeled: 0.1835, acc_unlabeled: 91.4064, loss_bbox_unlabeled: 0.1646, losses_cls_ig_unlabeled: 0.1739, pseudo_num: 1.5370, pseudo_num_ig: 5.6271, pseudo_num_mining: 0.5881, pseudo_num(acc): 0.8461, pseudo_num ig(acc): 0.4535, loss: 1.3292
2021-11-07 10:49:43,613 - mmdet - INFO - Iter [6450/40000] lr: 2.000e-02, eta: 17:50:57, time: 1.670, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0382, loss_rpn_bbox: 0.0535, loss_cls: 0.2321, acc: 92.1287, loss_bbox: 0.2797, loss_rpn_cls_unlabeled: 0.0909, loss_rpn_bbox_unlabeled: 0.0972, loss_cls_unlabeled: 0.1781, acc_unlabeled: 91.6145, loss_bbox_unlabeled: 0.1691, losses_cls_ig_unlabeled: 0.1672, pseudo_num: 1.5365, pseudo_num_ig: 5.6270, pseudo_num_mining: 0.5892, pseudo_num(acc): 0.8465, pseudo_num ig(acc): 0.4536, loss: 1.3060
2021-11-07 10:51:05,502 - mmdet - INFO - pseudo pos: 0.98(12594.0-person) 0.93(231.0-bicycle) 0.92(1891.0-car) 0.97(305.0-motorcycle) 0.98(222.0-airplane) 1.00(260.0-bus) 0.98(286.0-train) 0.75(468.0-truck) 0.71(598.0-boat) 0.90(597.0-traffic light) 1.00(77.0-fire hydrant) 0.96(83.0-stop sign) 0.84(56.0-parking meter) 0.66(477.0-bench) 0.92(451.0-bird) 0.96(239.0-cat) 0.98(241.0-dog) 0.98(292.0-horse) 0.92(544.0-sheep) 0.92(424.0-cow) 1.00(243.0-elephant) 0.98(65.0-bear) 0.99(224.0-zebra) 0.99(225.0-giraffe) 0.49(469.0-backpack) 0.84(591.0-umbrella) 0.44(571.0-handbag) 0.92(216.0-tie) 0.80(246.0-suitcase) 0.97(106.0-frisbee) 0.62(312.0-skis) 0.68(102.0-snowboard) 0.99(258.0-sports ball) 0.91(340.0-kite) 0.85(171.0-baseball bat) 0.97(156.0-baseball glove) 0.98(269.0-skateboard) 0.82(332.0-surfboard) 0.98(203.0-tennis racket) 0.87(974.0-bottle) 0.94(286.0-wine glass) 0.87(998.0-cup) 0.72(206.0-fork) 0.46(352.0-knife) 0.37(307.0-spoon) 0.82(796.0-bowl) 0.62(399.0-banana) 0.48(262.0-apple) 0.80(194.0-sandwich) 0.55(275.0-orange) 0.75(304.0-broccoli) 0.48(361.0-carrot) 0.69(107.0-hot dog) 0.94(327.0-pizza) 0.85(351.0-donut) 0.79(266.0-cake) 0.72(1729.0-chair) 0.78(331.0-couch) 0.72(331.0-potted plant) 0.90(198.0-bed) 0.71(925.0-dining table) 0.91(145.0-toilet) 0.98(273.0-tv) 0.99(232.0-laptop) 0.98(84.0-mouse) 0.69(271.0-remote) 0.93(148.0-keyboard) 0.82(300.0-cell phone) 0.95(76.0-microwave) 0.85(176.0-oven) 0.00(0.0-toaster) 0.79(291.0-sink) 0.86(127.0-refrigerator) 0.31(965.0-book) 0.98(205.0-clock) 0.91(300.0-vase) 0.58(74.0-scissors) 0.92(204.0-teddy bear) 0.00(0.0-hair drier) 0.09(426.0-toothbrush)
2021-11-07 10:51:05,503 - mmdet - INFO - pseudo ig: 0.60(44190.0-person) 0.46(870.0-bicycle) 0.49(7359.0-car) 0.59(1251.0-motorcycle) 0.65(696.0-airplane) 0.67(917.0-bus) 0.60(728.0-train) 0.37(1644.0-truck) 0.33(2099.0-boat) 0.40(2167.0-traffic light) 0.73(268.0-fire hydrant) 0.55(328.0-stop sign) 0.46(160.0-parking meter) 0.20(1621.0-bench) 0.36(1720.0-bird) 0.76(808.0-cat) 0.71(787.0-dog) 0.56(1119.0-horse) 0.44(2072.0-sheep) 0.45(1730.0-cow) 0.74(999.0-elephant) 0.67(210.0-bear) 0.78(848.0-zebra) 0.79(932.0-giraffe) 0.20(1643.0-backpack) 0.38(2060.0-umbrella) 0.18(2198.0-handbag) 0.44(742.0-tie) 0.34(1013.0-suitcase) 0.58(430.0-frisbee) 0.31(1235.0-skis) 0.25(383.0-snowboard) 0.42(1147.0-sports ball) 0.47(1344.0-kite) 0.30(690.0-baseball bat) 0.42(646.0-baseball glove) 0.50(845.0-skateboard) 0.38(1310.0-surfboard) 0.58(932.0-tennis racket) 0.39(3866.0-bottle) 0.44(1220.0-wine glass) 0.32(4351.0-cup) 0.25(902.0-fork) 0.20(1218.0-knife) 0.16(1140.0-spoon) 0.36(2951.0-bowl) 0.27(1681.0-banana) 0.21(1071.0-apple) 0.36(629.0-sandwich) 0.24(1372.0-orange) 0.41(1052.0-broccoli) 0.23(1195.0-carrot) 0.32(405.0-hot dog) 0.47(1094.0-pizza) 0.32(1322.0-donut) 0.36(948.0-cake) 0.29(6342.0-chair) 0.37(1048.0-couch) 0.36(1314.0-potted plant) 0.48(641.0-bed) 0.32(2745.0-dining table) 0.75(584.0-toilet) 0.54(954.0-tv) 0.54(961.0-laptop) 0.51(343.0-mouse) 0.27(1102.0-remote) 0.44(495.0-keyboard) 0.27(1284.0-cell phone) 0.43(274.0-microwave) 0.30(593.0-oven) 0.00(0.0-toaster) 0.44(917.0-sink) 0.35(431.0-refrigerator) 0.18(3907.0-book) 0.65(959.0-clock) 0.37(1071.0-vase) 0.23(235.0-scissors) 0.53(705.0-teddy bear) 0.00(0.0-hair drier) 0.05(713.0-toothbrush)
2021-11-07 10:51:05,503 - mmdet - INFO - pseudo gt: 56181.0 1624.0 9423.0 1840.0 1077.0 1395.0 992.0 2200.0 2337.0 2801.0 399.0 437.0 289.0 2145.0 2530.0 1049.0 1236.0 1427.0 2200.0 1779.0 1321.0 277.0 1109.0 1121.0 1923.0 2576.0 2717.0 1342.0 1374.0 550.0 1504.0 575.0 1391.0 1952.0 720.0 880.0 1261.0 1329.0 1118.0 5088.0 1685.0 4470.0 1166.0 1637.0 1321.0 3091.0 2118.0 1278.0 923.0 1305.0 1563.0 1702.0 529.0 1266.0 1546.0 1573.0 8321.0 1325.0 1855.0 847.0 3400.0 892.0 1221.0 1157.0 520.0 1273.0 634.0 1390.0 354.0 680.0 47.0 1240.0 564.0 5571.0 1344.0 1472.0 348.0 1006.0 49.0 408.0
2021-11-07 10:51:05,503 - mmdet - INFO - pseudo mining: 7964.0 22.0 931.0 81.0 77.0 184.0 55.0 13.0 31.0 234.0 87.0 172.0 6.0 9.0 62.0 97.0 68.0 95.0 221.0 88.0 317.0 50.0 338.0 382.0 4.0 96.0 0.0 48.0 11.0 126.0 12.0 0.0 325.0 231.0 31.0 99.0 72.0 36.0 185.0 307.0 61.0 223.0 2.0 1.0 0.0 111.0 18.0 5.0 10.0 9.0 48.0 10.0 2.0 77.0 91.0 9.0 20.0 6.0 41.0 8.0 28.0 210.0 229.0 118.0 87.0 17.0 27.0 23.0 16.0 9.0 0.0 83.0 10.0 4.0 592.0 45.0 0.0 43.0 0.0 0.0
2021-11-07 10:51:07,234 - mmdet - INFO - Iter [6500/40000] lr: 2.000e-02, eta: 17:48:18, time: 1.672, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0421, loss_rpn_bbox: 0.0559, loss_cls: 0.2331, acc: 92.0933, loss_bbox: 0.2844, loss_rpn_cls_unlabeled: 0.0904, loss_rpn_bbox_unlabeled: 0.0961, loss_cls_unlabeled: 0.1865, acc_unlabeled: 91.7449, loss_bbox_unlabeled: 0.1783, losses_cls_ig_unlabeled: 0.1624, pseudo_num: 1.5364, pseudo_num_ig: 5.6273, pseudo_num_mining: 0.5902, pseudo_num(acc): 0.8468, pseudo_num ig(acc): 0.4538, loss: 1.3292
2021-11-07 10:52:32,335 - mmdet - INFO - Iter [6550/40000] lr: 2.000e-02, eta: 17:45:49, time: 1.703, data_time: 0.029, memory: 26485, loss_rpn_cls: 0.0401, loss_rpn_bbox: 0.0563, loss_cls: 0.2371, acc: 91.9130, loss_bbox: 0.2879, loss_rpn_cls_unlabeled: 0.0915, loss_rpn_bbox_unlabeled: 0.1019, loss_cls_unlabeled: 0.1826, acc_unlabeled: 91.6012, loss_bbox_unlabeled: 0.1683, losses_cls_ig_unlabeled: 0.1681, pseudo_num: 1.5361, pseudo_num_ig: 5.6255, pseudo_num_mining: 0.5908, pseudo_num(acc): 0.8471, pseudo_num ig(acc): 0.4539, loss: 1.3337
2021-11-07 10:53:55,181 - mmdet - INFO - Iter [6600/40000] lr: 2.000e-02, eta: 17:43:08, time: 1.656, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0374, loss_rpn_bbox: 0.0519, loss_cls: 0.2289, acc: 92.1178, loss_bbox: 0.2813, loss_rpn_cls_unlabeled: 0.1005, loss_rpn_bbox_unlabeled: 0.1004, loss_cls_unlabeled: 0.1848, acc_unlabeled: 91.4445, loss_bbox_unlabeled: 0.1750, losses_cls_ig_unlabeled: 0.1709, pseudo_num: 1.5357, pseudo_num_ig: 5.6257, pseudo_num_mining: 0.5919, pseudo_num(acc): 0.8474, pseudo_num ig(acc): 0.4540, loss: 1.3312
2021-11-07 10:55:19,376 - mmdet - INFO - Iter [6650/40000] lr: 2.000e-02, eta: 17:40:36, time: 1.684, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0376, loss_rpn_bbox: 0.0516, loss_cls: 0.2272, acc: 92.2350, loss_bbox: 0.2716, loss_rpn_cls_unlabeled: 0.0913, loss_rpn_bbox_unlabeled: 0.0972, loss_cls_unlabeled: 0.1817, acc_unlabeled: 91.8164, loss_bbox_unlabeled: 0.1718, losses_cls_ig_unlabeled: 0.1608, pseudo_num: 1.5357, pseudo_num_ig: 5.6263, pseudo_num_mining: 0.5932, pseudo_num(acc): 0.8478, pseudo_num ig(acc): 0.4542, loss: 1.2909
2021-11-07 10:56:44,084 - mmdet - INFO - Iter [6700/40000] lr: 2.000e-02, eta: 17:38:08, time: 1.695, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0407, loss_rpn_bbox: 0.0563, loss_cls: 0.2267, acc: 92.1710, loss_bbox: 0.2809, loss_rpn_cls_unlabeled: 0.0928, loss_rpn_bbox_unlabeled: 0.0982, loss_cls_unlabeled: 0.1908, acc_unlabeled: 91.5150, loss_bbox_unlabeled: 0.1762, losses_cls_ig_unlabeled: 0.1683, pseudo_num: 1.5354, pseudo_num_ig: 5.6252, pseudo_num_mining: 0.5941, pseudo_num(acc): 0.8481, pseudo_num ig(acc): 0.4543, loss: 1.3309
2021-11-07 10:58:08,385 - mmdet - INFO - Iter [6750/40000] lr: 2.000e-02, eta: 17:35:38, time: 1.685, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0379, loss_rpn_bbox: 0.0546, loss_cls: 0.2304, acc: 92.1569, loss_bbox: 0.2809, loss_rpn_cls_unlabeled: 0.0897, loss_rpn_bbox_unlabeled: 0.0967, loss_cls_unlabeled: 0.1836, acc_unlabeled: 91.6622, loss_bbox_unlabeled: 0.1739, losses_cls_ig_unlabeled: 0.1610, pseudo_num: 1.5353, pseudo_num_ig: 5.6251, pseudo_num_mining: 0.5953, pseudo_num(acc): 0.8483, pseudo_num ig(acc): 0.4545, loss: 1.3088
2021-11-07 10:59:32,684 - mmdet - INFO - Iter [6800/40000] lr: 2.000e-02, eta: 17:33:09, time: 1.686, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0353, loss_rpn_bbox: 0.0507, loss_cls: 0.2236, acc: 92.3051, loss_bbox: 0.2753, loss_rpn_cls_unlabeled: 0.0944, loss_rpn_bbox_unlabeled: 0.1005, loss_cls_unlabeled: 0.1821, acc_unlabeled: 91.6204, loss_bbox_unlabeled: 0.1717, losses_cls_ig_unlabeled: 0.1675, pseudo_num: 1.5353, pseudo_num_ig: 5.6255, pseudo_num_mining: 0.5964, pseudo_num(acc): 0.8484, pseudo_num ig(acc): 0.4546, loss: 1.3012
2021-11-07 11:00:57,114 - mmdet - INFO - Iter [6850/40000] lr: 2.000e-02, eta: 17:30:42, time: 1.690, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0385, loss_rpn_bbox: 0.0532, loss_cls: 0.2283, acc: 92.2618, loss_bbox: 0.2824, loss_rpn_cls_unlabeled: 0.0938, loss_rpn_bbox_unlabeled: 0.0996, loss_cls_unlabeled: 0.1909, acc_unlabeled: 91.4171, loss_bbox_unlabeled: 0.1812, losses_cls_ig_unlabeled: 0.1651, pseudo_num: 1.5353, pseudo_num_ig: 5.6261, pseudo_num_mining: 0.5975, pseudo_num(acc): 0.8487, pseudo_num ig(acc): 0.4548, loss: 1.3329
2021-11-07 11:02:22,401 - mmdet - INFO - Iter [6900/40000] lr: 2.000e-02, eta: 17:28:20, time: 1.705, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0381, loss_rpn_bbox: 0.0543, loss_cls: 0.2228, acc: 92.2317, loss_bbox: 0.2804, loss_rpn_cls_unlabeled: 0.0918, loss_rpn_bbox_unlabeled: 0.0978, loss_cls_unlabeled: 0.1792, acc_unlabeled: 91.6542, loss_bbox_unlabeled: 0.1711, losses_cls_ig_unlabeled: 0.1671, pseudo_num: 1.5355, pseudo_num_ig: 5.6258, pseudo_num_mining: 0.5982, pseudo_num(acc): 0.8489, pseudo_num ig(acc): 0.4549, loss: 1.3028
2021-11-07 11:03:47,738 - mmdet - INFO - Iter [6950/40000] lr: 2.000e-02, eta: 17:25:59, time: 1.704, data_time: 0.031, memory: 26485, loss_rpn_cls: 0.0357, loss_rpn_bbox: 0.0532, loss_cls: 0.2271, acc: 92.1868, loss_bbox: 0.2801, loss_rpn_cls_unlabeled: 0.0966, loss_rpn_bbox_unlabeled: 0.0999, loss_cls_unlabeled: 0.1869, acc_unlabeled: 91.5557, loss_bbox_unlabeled: 0.1752, losses_cls_ig_unlabeled: 0.1682, pseudo_num: 1.5355, pseudo_num_ig: 5.6250, pseudo_num_mining: 0.5990, pseudo_num(acc): 0.8492, pseudo_num ig(acc): 0.4550, loss: 1.3228
2021-11-07 11:05:10,736 - mmdet - INFO - pseudo pos: 0.98(13581.0-person) 0.94(250.0-bicycle) 0.92(2045.0-car) 0.96(338.0-motorcycle) 0.98(245.0-airplane) 1.00(276.0-bus) 0.98(311.0-train) 0.74(502.0-truck) 0.71(612.0-boat) 0.91(658.0-traffic light) 1.00(85.0-fire hydrant) 0.97(93.0-stop sign) 0.85(60.0-parking meter) 0.66(507.0-bench) 0.93(477.0-bird) 0.96(262.0-cat) 0.98(253.0-dog) 0.98(328.0-horse) 0.92(563.0-sheep) 0.92(460.0-cow) 1.00(264.0-elephant) 0.99(71.0-bear) 0.99(242.0-zebra) 0.99(235.0-giraffe) 0.49(496.0-backpack) 0.84(637.0-umbrella) 0.45(609.0-handbag) 0.92(241.0-tie) 0.79(261.0-suitcase) 0.97(115.0-frisbee) 0.63(341.0-skis) 0.69(108.0-snowboard) 0.99(280.0-sports ball) 0.91(360.0-kite) 0.85(178.0-baseball bat) 0.96(168.0-baseball glove) 0.98(300.0-skateboard) 0.82(355.0-surfboard) 0.98(216.0-tennis racket) 0.87(1071.0-bottle) 0.94(312.0-wine glass) 0.87(1076.0-cup) 0.71(228.0-fork) 0.47(380.0-knife) 0.38(340.0-spoon) 0.82(865.0-bowl) 0.62(421.0-banana) 0.50(278.0-apple) 0.82(211.0-sandwich) 0.56(342.0-orange) 0.74(352.0-broccoli) 0.49(383.0-carrot) 0.67(133.0-hot dog) 0.94(353.0-pizza) 0.85(364.0-donut) 0.78(286.0-cake) 0.73(1848.0-chair) 0.78(360.0-couch) 0.72(357.0-potted plant) 0.90(210.0-bed) 0.71(999.0-dining table) 0.92(154.0-toilet) 0.98(293.0-tv) 0.99(249.0-laptop) 0.98(99.0-mouse) 0.70(282.0-remote) 0.93(166.0-keyboard) 0.82(315.0-cell phone) 0.95(81.0-microwave) 0.85(197.0-oven) 0.00(0.0-toaster) 0.79(305.0-sink) 0.87(136.0-refrigerator) 0.31(1017.0-book) 0.98(231.0-clock) 0.91(324.0-vase) 0.60(81.0-scissors) 0.92(229.0-teddy bear) 0.00(0.0-hair drier) 0.10(433.0-toothbrush)
2021-11-07 11:05:10,737 - mmdet - INFO - pseudo ig: 0.61(47625.0-person) 0.46(956.0-bicycle) 0.50(7991.0-car) 0.59(1375.0-motorcycle) 0.64(763.0-airplane) 0.67(1001.0-bus) 0.60(823.0-train) 0.37(1840.0-truck) 0.32(2206.0-boat) 0.41(2350.0-traffic light) 0.73(291.0-fire hydrant) 0.56(352.0-stop sign) 0.47(198.0-parking meter) 0.20(1745.0-bench) 0.35(1807.0-bird) 0.75(857.0-cat) 0.71(842.0-dog) 0.56(1205.0-horse) 0.44(2204.0-sheep) 0.45(1868.0-cow) 0.74(1049.0-elephant) 0.67(220.0-bear) 0.78(962.0-zebra) 0.80(987.0-giraffe) 0.20(1740.0-backpack) 0.38(2238.0-umbrella) 0.18(2358.0-handbag) 0.45(796.0-tie) 0.34(1061.0-suitcase) 0.58(454.0-frisbee) 0.31(1351.0-skis) 0.25(405.0-snowboard) 0.42(1221.0-sports ball) 0.47(1418.0-kite) 0.32(733.0-baseball bat) 0.42(701.0-baseball glove) 0.50(937.0-skateboard) 0.38(1428.0-surfboard) 0.58(977.0-tennis racket) 0.40(4177.0-bottle) 0.45(1346.0-wine glass) 0.32(4681.0-cup) 0.25(1040.0-fork) 0.20(1312.0-knife) 0.16(1276.0-spoon) 0.36(3184.0-bowl) 0.28(1805.0-banana) 0.22(1133.0-apple) 0.36(677.0-sandwich) 0.24(1485.0-orange) 0.41(1181.0-broccoli) 0.24(1310.0-carrot) 0.33(449.0-hot dog) 0.47(1171.0-pizza) 0.32(1363.0-donut) 0.35(1013.0-cake) 0.29(6771.0-chair) 0.36(1125.0-couch) 0.36(1419.0-potted plant) 0.48(676.0-bed) 0.32(2985.0-dining table) 0.75(637.0-toilet) 0.54(1036.0-tv) 0.54(1013.0-laptop) 0.52(368.0-mouse) 0.28(1168.0-remote) 0.43(529.0-keyboard) 0.27(1374.0-cell phone) 0.42(292.0-microwave) 0.30(660.0-oven) 0.00(0.0-toaster) 0.45(1003.0-sink) 0.35(471.0-refrigerator) 0.18(4206.0-book) 0.64(1048.0-clock) 0.37(1153.0-vase) 0.22(254.0-scissors) 0.52(783.0-teddy bear) 0.00(0.0-hair drier) 0.06(737.0-toothbrush)
2021-11-07 11:05:10,737 - mmdet - INFO - pseudo gt: 60445.0 1738.0 10280.0 2022.0 1166.0 1503.0 1090.0 2401.0 2442.0 3071.0 433.0 479.0 334.0 2296.0 2617.0 1116.0 1321.0 1542.0 2315.0 1919.0 1424.0 292.0 1246.0 1192.0 2060.0 2802.0 2941.0 1459.0 1489.0 582.0 1615.0 614.0 1499.0 2061.0 774.0 936.0 1364.0 1429.0 1183.0 5562.0 1859.0 4794.0 1289.0 1829.0 1446.0 3343.0 2296.0 1399.0 987.0 1393.0 1728.0 1888.0 582.0 1370.0 1582.0 1672.0 8969.0 1421.0 2023.0 902.0 3692.0 971.0 1322.0 1230.0 566.0 1354.0 691.0 1484.0 383.0 743.0 49.0 1351.0 609.0 5890.0 1451.0 1606.0 370.0 1084.0 52.0 448.0
2021-11-07 11:05:10,737 - mmdet - INFO - pseudo mining: 8632.0 25.0 1060.0 92.0 87.0 203.0 67.0 14.0 31.0 255.0 94.0 183.0 14.0 11.0 67.0 99.0 75.0 108.0 241.0 94.0 333.0 54.0 382.0 415.0 4.0 107.0 0.0 52.0 11.0 133.0 12.0 0.0 344.0 253.0 40.0 112.0 83.0 38.0 197.0 343.0 72.0 246.0 2.0 2.0 0.0 123.0 22.0 6.0 10.0 9.0 57.0 12.0 2.0 83.0 97.0 9.0 22.0 6.0 49.0 10.0 33.0 236.0 245.0 126.0 96.0 20.0 31.0 32.0 16.0 9.0 0.0 106.0 11.0 5.0 629.0 52.0 0.0 59.0 0.0 0.0
2021-11-07 11:06:36,880 - mmdet - INFO - current percent: 0.2
2021-11-07 11:06:36,881 - mmdet - INFO - update score thr (positive): (0.99-person) (0.98-bicycle) (0.98-car) (0.99-motorcycle) (0.99-airplane) (1.00-bus) (0.99-train) (0.93-truck) (0.95-boat) (0.98-traffic light) (1.00-fire hydrant) (1.00-stop sign) (0.98-parking meter) (0.94-bench) (0.97-bird) (0.98-cat) (0.98-dog) (0.99-horse) (0.98-sheep) (0.98-cow) (0.99-elephant) (0.99-bear) (1.00-zebra) (1.00-giraffe) (0.87-backpack) (0.96-umbrella) (0.76-handbag) (0.97-tie) (0.94-suitcase) (0.99-frisbee) (0.93-skis) (0.76-snowboard) (0.99-sports ball) (0.99-kite) (0.97-baseball bat) (0.98-baseball glove) (0.99-skateboard) (0.97-surfboard) (0.99-tennis racket) (0.97-bottle) (0.99-wine glass) (0.96-cup) (0.80-fork) (0.84-knife) (0.82-spoon) (0.97-bowl) (0.81-banana) (0.84-apple) (0.95-sandwich) (0.91-orange) (0.95-broccoli) (0.87-carrot) (0.76-hot dog) (0.98-pizza) (0.94-donut) (0.96-cake) (0.90-chair) (0.94-couch) (0.96-potted plant) (0.97-bed) (0.95-dining table) (1.00-toilet) (0.99-tv) (0.99-laptop) (0.99-mouse) (0.90-remote) (0.99-keyboard) (0.95-cell phone) (0.98-microwave) (0.97-oven) (0.05-toaster) (0.99-sink) (0.98-refrigerator) (0.81-book) (1.00-clock) (0.98-vase) (0.83-scissors) (0.99-teddy bear) (0.05-hair drier) (0.74-toothbrush)
2021-11-07 11:06:36,881 - mmdet - INFO - update score thr (ignore): (0.41-person) (0.47-bicycle) (0.49-car) (0.52-motorcycle) (0.63-airplane) (0.51-bus) (0.64-train) (0.42-truck) (0.36-boat) (0.47-traffic light) (0.61-fire hydrant) (0.73-stop sign) (0.20-parking meter) (0.39-bench) (0.21-bird) (0.49-cat) (0.55-dog) (0.37-horse) (0.33-sheep) (0.45-cow) (0.53-elephant) (0.62-bear) (0.48-zebra) (0.31-giraffe) (0.44-backpack) (0.25-umbrella) (0.29-handbag) (0.50-tie) (0.34-suitcase) (0.58-frisbee) (0.38-skis) (0.28-snowboard) (0.42-sports ball) (0.63-kite) (0.35-baseball bat) (0.41-baseball glove) (0.45-skateboard) (0.37-surfboard) (0.36-tennis racket) (0.44-bottle) (0.28-wine glass) (0.35-cup) (0.25-fork) (0.35-knife) (0.34-spoon) (0.47-bowl) (0.20-banana) (0.25-apple) (0.47-sandwich) (0.36-orange) (0.59-broccoli) (0.46-carrot) (0.27-hot dog) (0.44-pizza) (0.36-donut) (0.33-cake) (0.31-chair) (0.49-couch) (0.56-potted plant) (0.49-bed) (0.46-dining table) (0.84-toilet) (0.60-tv) (0.45-laptop) (0.55-mouse) (0.33-remote) (0.51-keyboard) (0.42-cell phone) (0.52-microwave) (0.53-oven) (0.05-toaster) (0.60-sink) (0.56-refrigerator) (0.31-book) (0.81-clock) (0.42-vase) (0.25-scissors) (0.65-teddy bear) (0.05-hair drier) (0.30-toothbrush)
2021-11-07 11:06:37,173 - mmdet - INFO - Exp name: labelmatch_0.9_1_5_8.py
2021-11-07 11:06:37,173 - mmdet - INFO - Iter [7000/40000] lr: 2.000e-02, eta: 17:23:35, time: 1.694, data_time: 0.029, memory: 26485, loss_rpn_cls: 0.0360, loss_rpn_bbox: 0.0512, loss_cls: 0.2250, acc: 92.2377, loss_bbox: 0.2789, loss_rpn_cls_unlabeled: 0.0879, loss_rpn_bbox_unlabeled: 0.0931, loss_cls_unlabeled: 0.1818, acc_unlabeled: 91.8505, loss_bbox_unlabeled: 0.1762, losses_cls_ig_unlabeled: 0.1585, pseudo_num: 1.5354, pseudo_num_ig: 5.6234, pseudo_num_mining: 0.5996, pseudo_num(acc): 0.8495, pseudo_num ig(acc): 0.4551, loss: 1.2887
2021-11-07 11:09:19,169 - mmdet - INFO - Iter [7050/40000] lr: 2.000e-02, eta: 17:33:51, time: 4.938, data_time: 1.723, memory: 26485, loss_rpn_cls: 0.0351, loss_rpn_bbox: 0.0502, loss_cls: 0.2278, acc: 92.2732, loss_bbox: 0.2771, loss_rpn_cls_unlabeled: 0.0909, loss_rpn_bbox_unlabeled: 0.1047, loss_cls_unlabeled: 0.1878, acc_unlabeled: 91.2544, loss_bbox_unlabeled: 0.1779, losses_cls_ig_unlabeled: 0.1705, pseudo_num: 1.5350, pseudo_num_ig: 5.6226, pseudo_num_mining: 0.6004, pseudo_num(acc): 0.8497, pseudo_num ig(acc): 0.4552, loss: 1.3221
2021-11-07 11:10:44,334 - mmdet - INFO - Iter [7100/40000] lr: 2.000e-02, eta: 17:31:25, time: 1.703, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0354, loss_rpn_bbox: 0.0492, loss_cls: 0.2230, acc: 92.2920, loss_bbox: 0.2755, loss_rpn_cls_unlabeled: 0.0963, loss_rpn_bbox_unlabeled: 0.1050, loss_cls_unlabeled: 0.1898, acc_unlabeled: 91.3856, loss_bbox_unlabeled: 0.1794, losses_cls_ig_unlabeled: 0.1667, pseudo_num: 1.5350, pseudo_num_ig: 5.6248, pseudo_num_mining: 0.6020, pseudo_num(acc): 0.8498, pseudo_num ig(acc): 0.4552, loss: 1.3202
2021-11-07 11:12:08,669 - mmdet - INFO - Iter [7150/40000] lr: 2.000e-02, eta: 17:28:55, time: 1.683, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0355, loss_rpn_bbox: 0.0529, loss_cls: 0.2297, acc: 92.1180, loss_bbox: 0.2804, loss_rpn_cls_unlabeled: 0.0973, loss_rpn_bbox_unlabeled: 0.1011, loss_cls_unlabeled: 0.1944, acc_unlabeled: 91.5751, loss_bbox_unlabeled: 0.1791, losses_cls_ig_unlabeled: 0.1630, pseudo_num: 1.5353, pseudo_num_ig: 5.6264, pseudo_num_mining: 0.6035, pseudo_num(acc): 0.8499, pseudo_num ig(acc): 0.4553, loss: 1.3334
2021-11-07 11:13:35,381 - mmdet - INFO - Iter [7200/40000] lr: 2.000e-02, eta: 17:26:38, time: 1.737, data_time: 0.031, memory: 26485, loss_rpn_cls: 0.0366, loss_rpn_bbox: 0.0517, loss_cls: 0.2285, acc: 92.1012, loss_bbox: 0.2827, loss_rpn_cls_unlabeled: 0.0946, loss_rpn_bbox_unlabeled: 0.0995, loss_cls_unlabeled: 0.1897, acc_unlabeled: 91.3713, loss_bbox_unlabeled: 0.1807, losses_cls_ig_unlabeled: 0.1681, pseudo_num: 1.5355, pseudo_num_ig: 5.6280, pseudo_num_mining: 0.6052, pseudo_num(acc): 0.8501, pseudo_num ig(acc): 0.4554, loss: 1.3320
2021-11-07 11:15:00,301 - mmdet - INFO - Iter [7250/40000] lr: 2.000e-02, eta: 17:24:14, time: 1.700, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0368, loss_rpn_bbox: 0.0530, loss_cls: 0.2246, acc: 92.2996, loss_bbox: 0.2790, loss_rpn_cls_unlabeled: 0.0920, loss_rpn_bbox_unlabeled: 0.0976, loss_cls_unlabeled: 0.1910, acc_unlabeled: 91.5724, loss_bbox_unlabeled: 0.1801, losses_cls_ig_unlabeled: 0.1607, pseudo_num: 1.5358, pseudo_num_ig: 5.6291, pseudo_num_mining: 0.6063, pseudo_num(acc): 0.8503, pseudo_num ig(acc): 0.4556, loss: 1.3148
2021-11-07 11:16:24,352 - mmdet - INFO - Iter [7300/40000] lr: 2.000e-02, eta: 17:21:47, time: 1.681, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0353, loss_rpn_bbox: 0.0519, loss_cls: 0.2239, acc: 92.2732, loss_bbox: 0.2754, loss_rpn_cls_unlabeled: 0.0987, loss_rpn_bbox_unlabeled: 0.1007, loss_cls_unlabeled: 0.1957, acc_unlabeled: 91.4963, loss_bbox_unlabeled: 0.1891, losses_cls_ig_unlabeled: 0.1597, pseudo_num: 1.5362, pseudo_num_ig: 5.6302, pseudo_num_mining: 0.6075, pseudo_num(acc): 0.8505, pseudo_num ig(acc): 0.4557, loss: 1.3304
2021-11-07 11:17:49,444 - mmdet - INFO - Iter [7350/40000] lr: 2.000e-02, eta: 17:19:23, time: 1.697, data_time: 0.028, memory: 26485, loss_rpn_cls: 0.0338, loss_rpn_bbox: 0.0512, loss_cls: 0.2258, acc: 92.3372, loss_bbox: 0.2730, loss_rpn_cls_unlabeled: 0.0975, loss_rpn_bbox_unlabeled: 0.1010, loss_cls_unlabeled: 0.1860, acc_unlabeled: 91.6132, loss_bbox_unlabeled: 0.1753, losses_cls_ig_unlabeled: 0.1645, pseudo_num: 1.5361, pseudo_num_ig: 5.6303, pseudo_num_mining: 0.6088, pseudo_num(acc): 0.8506, pseudo_num ig(acc): 0.4558, loss: 1.3083
2021-11-07 11:19:13,983 - mmdet - INFO - Iter [7400/40000] lr: 2.000e-02, eta: 17:17:00, time: 1.695, data_time: 0.035, memory: 26485, loss_rpn_cls: 0.0364, loss_rpn_bbox: 0.0526, loss_cls: 0.2283, acc: 92.1554, loss_bbox: 0.2825, loss_rpn_cls_unlabeled: 0.0914, loss_rpn_bbox_unlabeled: 0.1003, loss_cls_unlabeled: 0.1909, acc_unlabeled: 91.6545, loss_bbox_unlabeled: 0.1823, losses_cls_ig_unlabeled: 0.1606, pseudo_num: 1.5362, pseudo_num_ig: 5.6302, pseudo_num_mining: 0.6099, pseudo_num(acc): 0.8507, pseudo_num ig(acc): 0.4559, loss: 1.3252
2021-11-07 11:20:41,872 - mmdet - INFO - Iter [7450/40000] lr: 2.000e-02, eta: 17:14:52, time: 1.759, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0340, loss_rpn_bbox: 0.0490, loss_cls: 0.2162, acc: 92.5166, loss_bbox: 0.2672, loss_rpn_cls_unlabeled: 0.0886, loss_rpn_bbox_unlabeled: 0.0971, loss_cls_unlabeled: 0.1892, acc_unlabeled: 91.7477, loss_bbox_unlabeled: 0.1814, losses_cls_ig_unlabeled: 0.1569, pseudo_num: 1.5363, pseudo_num_ig: 5.6303, pseudo_num_mining: 0.6109, pseudo_num(acc): 0.8507, pseudo_num ig(acc): 0.4559, loss: 1.2795
2021-11-07 11:22:06,304 - mmdet - INFO - pseudo pos: 0.98(14549.0-person) 0.93(271.0-bicycle) 0.92(2199.0-car) 0.97(362.0-motorcycle) 0.98(258.0-airplane) 1.00(292.0-bus) 0.98(328.0-train) 0.75(556.0-truck) 0.72(651.0-boat) 0.91(697.0-traffic light) 1.00(90.0-fire hydrant) 0.96(106.0-stop sign) 0.86(64.0-parking meter) 0.66(543.0-bench) 0.92(504.0-bird) 0.96(278.0-cat) 0.98(281.0-dog) 0.99(360.0-horse) 0.92(594.0-sheep) 0.93(486.0-cow) 1.00(292.0-elephant) 0.99(77.0-bear) 0.99(254.0-zebra) 0.99(250.0-giraffe) 0.50(525.0-backpack) 0.84(681.0-umbrella) 0.46(662.0-handbag) 0.92(260.0-tie) 0.79(289.0-suitcase) 0.98(132.0-frisbee) 0.64(364.0-skis) 0.68(116.0-snowboard) 0.99(301.0-sports ball) 0.91(381.0-kite) 0.86(190.0-baseball bat) 0.96(178.0-baseball glove) 0.98(318.0-skateboard) 0.82(376.0-surfboard) 0.98(236.0-tennis racket) 0.88(1165.0-bottle) 0.93(335.0-wine glass) 0.87(1153.0-cup) 0.71(254.0-fork) 0.47(416.0-knife) 0.40(361.0-spoon) 0.82(929.0-bowl) 0.62(516.0-banana) 0.53(310.0-apple) 0.81(229.0-sandwich) 0.58(359.0-orange) 0.75(377.0-broccoli) 0.50(408.0-carrot) 0.67(150.0-hot dog) 0.94(376.0-pizza) 0.85(416.0-donut) 0.79(304.0-cake) 0.73(1967.0-chair) 0.79(378.0-couch) 0.73(379.0-potted plant) 0.90(225.0-bed) 0.70(1076.0-dining table) 0.92(165.0-toilet) 0.98(307.0-tv) 0.99(265.0-laptop) 0.98(102.0-mouse) 0.70(299.0-remote) 0.94(172.0-keyboard) 0.82(338.0-cell phone) 0.95(87.0-microwave) 0.85(219.0-oven) 0.00(0.0-toaster) 0.80(323.0-sink) 0.88(154.0-refrigerator) 0.32(1107.0-book) 0.98(246.0-clock) 0.90(342.0-vase) 0.61(89.0-scissors) 0.91(248.0-teddy bear) 0.00(0.0-hair drier) 0.10(439.0-toothbrush)
2021-11-07 11:22:06,304 - mmdet - INFO - pseudo ig: 0.61(50980.0-person) 0.46(1025.0-bicycle) 0.50(8614.0-car) 0.58(1463.0-motorcycle) 0.66(820.0-airplane) 0.67(1080.0-bus) 0.60(858.0-train) 0.37(2008.0-truck) 0.32(2361.0-boat) 0.41(2481.0-traffic light) 0.73(312.0-fire hydrant) 0.56(376.0-stop sign) 0.47(215.0-parking meter) 0.20(1893.0-bench) 0.35(1982.0-bird) 0.75(909.0-cat) 0.71(897.0-dog) 0.56(1291.0-horse) 0.44(2310.0-sheep) 0.45(1972.0-cow) 0.75(1131.0-elephant) 0.67(237.0-bear) 0.78(1049.0-zebra) 0.80(1044.0-giraffe) 0.20(1821.0-backpack) 0.37(2422.0-umbrella) 0.18(2516.0-handbag) 0.44(850.0-tie) 0.35(1141.0-suitcase) 0.59(490.0-frisbee) 0.31(1447.0-skis) 0.27(452.0-snowboard) 0.43(1298.0-sports ball) 0.48(1470.0-kite) 0.32(772.0-baseball bat) 0.41(739.0-baseball glove) 0.51(1000.0-skateboard) 0.38(1537.0-surfboard) 0.59(1040.0-tennis racket) 0.40(4532.0-bottle) 0.44(1435.0-wine glass) 0.32(5014.0-cup) 0.26(1132.0-fork) 0.21(1423.0-knife) 0.17(1394.0-spoon) 0.36(3394.0-bowl) 0.27(2064.0-banana) 0.22(1273.0-apple) 0.36(755.0-sandwich) 0.24(1598.0-orange) 0.41(1255.0-broccoli) 0.24(1394.0-carrot) 0.32(485.0-hot dog) 0.47(1272.0-pizza) 0.32(1502.0-donut) 0.35(1098.0-cake) 0.29(7233.0-chair) 0.36(1190.0-couch) 0.36(1487.0-potted plant) 0.47(725.0-bed) 0.32(3229.0-dining table) 0.75(677.0-toilet) 0.54(1105.0-tv) 0.54(1065.0-laptop) 0.51(390.0-mouse) 0.28(1247.0-remote) 0.43(558.0-keyboard) 0.27(1450.0-cell phone) 0.44(317.0-microwave) 0.30(721.0-oven) 0.00(0.0-toaster) 0.46(1090.0-sink) 0.36(506.0-refrigerator) 0.18(4546.0-book) 0.64(1101.0-clock) 0.37(1230.0-vase) 0.22(274.0-scissors) 0.53(831.0-teddy bear) 0.00(0.0-hair drier) 0.06(756.0-toothbrush)
2021-11-07 11:22:06,304 - mmdet - INFO - pseudo gt: 64519.0 1858.0 11202.0 2116.0 1258.0 1628.0 1152.0 2613.0 2607.0 3246.0 469.0 518.0 360.0 2440.0 2762.0 1184.0 1407.0 1637.0 2468.0 2064.0 1544.0 313.0 1346.0 1262.0 2189.0 2966.0 3128.0 1555.0 1605.0 634.0 1719.0 676.0 1631.0 2158.0 820.0 982.0 1440.0 1523.0 1278.0 6038.0 2012.0 5086.0 1393.0 1972.0 1566.0 3604.0 2512.0 1518.0 1102.0 1522.0 1861.0 2039.0 634.0 1461.0 1750.0 1775.0 9493.0 1515.0 2151.0 968.0 3963.0 1026.0 1419.0 1296.0 597.0 1439.0 726.0 1564.0 418.0 802.0 54.0 1456.0 671.0 6323.0 1554.0 1707.0 408.0 1154.0 58.0 475.0
2021-11-07 11:22:06,304 - mmdet - INFO - pseudo mining: 9403.0 27.0 1178.0 96.0 103.0 226.0 74.0 15.0 38.0 279.0 105.0 196.0 14.0 12.0 76.0 106.0 83.0 112.0 260.0 110.0 360.0 59.0 413.0 444.0 4.0 109.0 0.0 60.0 13.0 144.0 16.0 0.0 368.0 266.0 41.0 117.0 91.0 43.0 212.0 377.0 74.0 264.0 2.0 2.0 0.0 140.0 22.0 6.0 13.0 11.0 64.0 15.0 2.0 94.0 102.0 9.0 26.0 6.0 53.0 10.0 35.0 255.0 269.0 133.0 103.0 21.0 32.0 36.0 21.0 11.0 0.0 126.0 12.0 5.0 673.0 53.0 0.0 72.0 0.0 0.0
2021-11-07 11:22:08,004 - mmdet - INFO - Iter [7500/40000] lr: 2.000e-02, eta: 17:12:37, time: 1.722, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0357, loss_rpn_bbox: 0.0529, loss_cls: 0.2251, acc: 92.2216, loss_bbox: 0.2829, loss_rpn_cls_unlabeled: 0.0958, loss_rpn_bbox_unlabeled: 0.1030, loss_cls_unlabeled: 0.1921, acc_unlabeled: 91.5498, loss_bbox_unlabeled: 0.1789, losses_cls_ig_unlabeled: 0.1636, pseudo_num: 1.5364, pseudo_num_ig: 5.6310, pseudo_num_mining: 0.6120, pseudo_num(acc): 0.8507, pseudo_num ig(acc): 0.4559, loss: 1.3298
2021-11-07 11:23:32,404 - mmdet - INFO - Iter [7550/40000] lr: 2.000e-02, eta: 17:10:14, time: 1.684, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0351, loss_rpn_bbox: 0.0516, loss_cls: 0.2252, acc: 92.2522, loss_bbox: 0.2758, loss_rpn_cls_unlabeled: 0.0915, loss_rpn_bbox_unlabeled: 0.1027, loss_cls_unlabeled: 0.1878, acc_unlabeled: 91.4368, loss_bbox_unlabeled: 0.1779, losses_cls_ig_unlabeled: 0.1659, pseudo_num: 1.5364, pseudo_num_ig: 5.6310, pseudo_num_mining: 0.6131, pseudo_num(acc): 0.8508, pseudo_num ig(acc): 0.4559, loss: 1.3134
2021-11-07 11:24:57,527 - mmdet - INFO - Iter [7600/40000] lr: 2.000e-02, eta: 17:07:56, time: 1.704, data_time: 0.032, memory: 26485, loss_rpn_cls: 0.0347, loss_rpn_bbox: 0.0494, loss_cls: 0.2141, acc: 92.6616, loss_bbox: 0.2646, loss_rpn_cls_unlabeled: 0.0929, loss_rpn_bbox_unlabeled: 0.1011, loss_cls_unlabeled: 0.1875, acc_unlabeled: 91.3190, loss_bbox_unlabeled: 0.1795, losses_cls_ig_unlabeled: 0.1687, pseudo_num: 1.5366, pseudo_num_ig: 5.6326, pseudo_num_mining: 0.6142, pseudo_num(acc): 0.8510, pseudo_num ig(acc): 0.4559, loss: 1.2924
2021-11-07 11:26:22,231 - mmdet - INFO - Iter [7650/40000] lr: 2.000e-02, eta: 17:05:36, time: 1.694, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0383, loss_rpn_bbox: 0.0550, loss_cls: 0.2311, acc: 92.0300, loss_bbox: 0.2841, loss_rpn_cls_unlabeled: 0.0946, loss_rpn_bbox_unlabeled: 0.0983, loss_cls_unlabeled: 0.1862, acc_unlabeled: 91.7512, loss_bbox_unlabeled: 0.1770, losses_cls_ig_unlabeled: 0.1630, pseudo_num: 1.5367, pseudo_num_ig: 5.6328, pseudo_num_mining: 0.6152, pseudo_num(acc): 0.8511, pseudo_num ig(acc): 0.4559, loss: 1.3277
2021-11-07 11:27:47,310 - mmdet - INFO - Iter [7700/40000] lr: 2.000e-02, eta: 17:03:19, time: 1.703, data_time: 0.029, memory: 26485, loss_rpn_cls: 0.0368, loss_rpn_bbox: 0.0537, loss_cls: 0.2262, acc: 92.2229, loss_bbox: 0.2780, loss_rpn_cls_unlabeled: 0.0951, loss_rpn_bbox_unlabeled: 0.0989, loss_cls_unlabeled: 0.1917, acc_unlabeled: 91.3439, loss_bbox_unlabeled: 0.1836, losses_cls_ig_unlabeled: 0.1676, pseudo_num: 1.5367, pseudo_num_ig: 5.6335, pseudo_num_mining: 0.6161, pseudo_num(acc): 0.8511, pseudo_num ig(acc): 0.4559, loss: 1.3316
2021-11-07 11:29:11,842 - mmdet - INFO - Iter [7750/40000] lr: 2.000e-02, eta: 17:01:00, time: 1.690, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0352, loss_rpn_bbox: 0.0529, loss_cls: 0.2200, acc: 92.4159, loss_bbox: 0.2739, loss_rpn_cls_unlabeled: 0.0938, loss_rpn_bbox_unlabeled: 0.0969, loss_cls_unlabeled: 0.1855, acc_unlabeled: 91.6567, loss_bbox_unlabeled: 0.1801, losses_cls_ig_unlabeled: 0.1640, pseudo_num: 1.5367, pseudo_num_ig: 5.6328, pseudo_num_mining: 0.6167, pseudo_num(acc): 0.8512, pseudo_num ig(acc): 0.4559, loss: 1.3023
2021-11-07 11:30:35,781 - mmdet - INFO - Iter [7800/40000] lr: 2.000e-02, eta: 16:58:40, time: 1.680, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0361, loss_rpn_bbox: 0.0498, loss_cls: 0.2196, acc: 92.4628, loss_bbox: 0.2671, loss_rpn_cls_unlabeled: 0.0970, loss_rpn_bbox_unlabeled: 0.0976, loss_cls_unlabeled: 0.1822, acc_unlabeled: 91.6027, loss_bbox_unlabeled: 0.1718, losses_cls_ig_unlabeled: 0.1656, pseudo_num: 1.5366, pseudo_num_ig: 5.6334, pseudo_num_mining: 0.6176, pseudo_num(acc): 0.8513, pseudo_num ig(acc): 0.4559, loss: 1.2869
2021-11-07 11:32:00,478 - mmdet - INFO - Iter [7850/40000] lr: 2.000e-02, eta: 16:56:23, time: 1.693, data_time: 0.029, memory: 26485, loss_rpn_cls: 0.0372, loss_rpn_bbox: 0.0520, loss_cls: 0.2255, acc: 92.2910, loss_bbox: 0.2787, loss_rpn_cls_unlabeled: 0.0918, loss_rpn_bbox_unlabeled: 0.0988, loss_cls_unlabeled: 0.1828, acc_unlabeled: 91.6207, loss_bbox_unlabeled: 0.1849, losses_cls_ig_unlabeled: 0.1625, pseudo_num: 1.5364, pseudo_num_ig: 5.6331, pseudo_num_mining: 0.6183, pseudo_num(acc): 0.8514, pseudo_num ig(acc): 0.4560, loss: 1.3143
2021-11-07 11:33:23,910 - mmdet - INFO - Iter [7900/40000] lr: 2.000e-02, eta: 16:54:02, time: 1.671, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0360, loss_rpn_bbox: 0.0521, loss_cls: 0.2224, acc: 92.2871, loss_bbox: 0.2822, loss_rpn_cls_unlabeled: 0.0908, loss_rpn_bbox_unlabeled: 0.1039, loss_cls_unlabeled: 0.1896, acc_unlabeled: 91.5203, loss_bbox_unlabeled: 0.1863, losses_cls_ig_unlabeled: 0.1596, pseudo_num: 1.5370, pseudo_num_ig: 5.6343, pseudo_num_mining: 0.6194, pseudo_num(acc): 0.8515, pseudo_num ig(acc): 0.4559, loss: 1.3229
2021-11-07 11:34:49,405 - mmdet - INFO - Iter [7950/40000] lr: 2.000e-02, eta: 16:51:49, time: 1.705, data_time: 0.026, memory: 26485, loss_rpn_cls: 0.0351, loss_rpn_bbox: 0.0512, loss_cls: 0.2258, acc: 92.1942, loss_bbox: 0.2802, loss_rpn_cls_unlabeled: 0.0980, loss_rpn_bbox_unlabeled: 0.1045, loss_cls_unlabeled: 0.1934, acc_unlabeled: 91.5803, loss_bbox_unlabeled: 0.1827, losses_cls_ig_unlabeled: 0.1613, pseudo_num: 1.5374, pseudo_num_ig: 5.6350, pseudo_num_mining: 0.6202, pseudo_num(acc): 0.8516, pseudo_num ig(acc): 0.4559, loss: 1.3321
2021-11-07 11:36:11,680 - mmdet - INFO - pseudo pos: 0.98(15522.0-person) 0.94(289.0-bicycle) 0.92(2322.0-car) 0.97(388.0-motorcycle) 0.99(273.0-airplane) 1.00(308.0-bus) 0.98(341.0-train) 0.76(587.0-truck) 0.72(685.0-boat) 0.92(733.0-traffic light) 1.00(95.0-fire hydrant) 0.97(117.0-stop sign) 0.87(75.0-parking meter) 0.66(583.0-bench) 0.92(549.0-bird) 0.96(293.0-cat) 0.98(300.0-dog) 0.98(382.0-horse) 0.91(627.0-sheep) 0.93(511.0-cow) 1.00(319.0-elephant) 0.99(82.0-bear) 0.99(279.0-zebra) 0.99(278.0-giraffe) 0.51(554.0-backpack) 0.84(723.0-umbrella) 0.45(707.0-handbag) 0.91(279.0-tie) 0.77(315.0-suitcase) 0.98(141.0-frisbee) 0.64(386.0-skis) 0.69(125.0-snowboard) 0.99(324.0-sports ball) 0.91(395.0-kite) 0.85(205.0-baseball bat) 0.96(195.0-baseball glove) 0.99(345.0-skateboard) 0.82(402.0-surfboard) 0.98(256.0-tennis racket) 0.87(1240.0-bottle) 0.93(355.0-wine glass) 0.86(1246.0-cup) 0.72(272.0-fork) 0.48(439.0-knife) 0.40(391.0-spoon) 0.82(1021.0-bowl) 0.61(553.0-banana) 0.53(333.0-apple) 0.81(247.0-sandwich) 0.58(365.0-orange) 0.76(422.0-broccoli) 0.50(442.0-carrot) 0.68(167.0-hot dog) 0.94(398.0-pizza) 0.85(440.0-donut) 0.80(322.0-cake) 0.73(2094.0-chair) 0.78(394.0-couch) 0.73(398.0-potted plant) 0.90(239.0-bed) 0.71(1151.0-dining table) 0.92(172.0-toilet) 0.98(330.0-tv) 0.99(278.0-laptop) 0.98(104.0-mouse) 0.69(311.0-remote) 0.94(178.0-keyboard) 0.81(351.0-cell phone) 0.96(93.0-microwave) 0.85(234.0-oven) 0.00(0.0-toaster) 0.80(338.0-sink) 0.89(166.0-refrigerator) 0.32(1163.0-book) 0.98(271.0-clock) 0.90(367.0-vase) 0.61(92.0-scissors) 0.91(268.0-teddy bear) 0.00(0.0-hair drier) 0.11(446.0-toothbrush)
2021-11-07 11:36:11,680 - mmdet - INFO - pseudo ig: 0.61(54386.0-person) 0.46(1108.0-bicycle) 0.50(9087.0-car) 0.58(1549.0-motorcycle) 0.66(863.0-airplane) 0.67(1167.0-bus) 0.61(905.0-train) 0.37(2149.0-truck) 0.32(2523.0-boat) 0.42(2629.0-traffic light) 0.73(343.0-fire hydrant) 0.55(398.0-stop sign) 0.43(244.0-parking meter) 0.20(2025.0-bench) 0.35(2139.0-bird) 0.75(960.0-cat) 0.70(936.0-dog) 0.56(1366.0-horse) 0.43(2617.0-sheep) 0.46(2066.0-cow) 0.75(1220.0-elephant) 0.67(251.0-bear) 0.78(1132.0-zebra) 0.79(1150.0-giraffe) 0.21(1919.0-backpack) 0.37(2575.0-umbrella) 0.18(2680.0-handbag) 0.45(902.0-tie) 0.35(1243.0-suitcase) 0.59(518.0-frisbee) 0.31(1520.0-skis) 0.27(499.0-snowboard) 0.43(1364.0-sports ball) 0.48(1547.0-kite) 0.32(811.0-baseball bat) 0.41(779.0-baseball glove) 0.51(1074.0-skateboard) 0.38(1638.0-surfboard) 0.60(1118.0-tennis racket) 0.40(4831.0-bottle) 0.44(1510.0-wine glass) 0.32(5346.0-cup) 0.26(1220.0-fork) 0.21(1538.0-knife) 0.17(1461.0-spoon) 0.37(3643.0-bowl) 0.26(2191.0-banana) 0.21(1393.0-apple) 0.36(816.0-sandwich) 0.25(1698.0-orange) 0.41(1384.0-broccoli) 0.24(1493.0-carrot) 0.31(542.0-hot dog) 0.47(1349.0-pizza) 0.32(1626.0-donut) 0.35(1190.0-cake) 0.29(7696.0-chair) 0.36(1270.0-couch) 0.37(1594.0-potted plant) 0.48(781.0-bed) 0.32(3447.0-dining table) 0.75(728.0-toilet) 0.54(1176.0-tv) 0.54(1108.0-laptop) 0.50(424.0-mouse) 0.27(1327.0-remote) 0.43(584.0-keyboard) 0.27(1540.0-cell phone) 0.45(341.0-microwave) 0.30(775.0-oven) 0.00(0.0-toaster) 0.46(1158.0-sink) 0.36(533.0-refrigerator) 0.18(4840.0-book) 0.65(1178.0-clock) 0.39(1325.0-vase) 0.22(302.0-scissors) 0.53(877.0-teddy bear) 0.00(0.0-hair drier) 0.06(778.0-toothbrush)
2021-11-07 11:36:11,681 - mmdet - INFO - pseudo gt: 68667.0 2004.0 11870.0 2253.0 1342.0 1733.0 1221.0 2754.0 2814.0 3450.0 500.0 544.0 384.0 2617.0 2970.0 1254.0 1476.0 1735.0 2655.0 2175.0 1681.0 331.0 1456.0 1382.0 2334.0 3095.0 3304.0 1685.0 1695.0 672.0 1820.0 734.0 1734.0 2280.0 883.0 1048.0 1537.0 1601.0 1366.0 6440.0 2140.0 5429.0 1499.0 2104.0 1702.0 3907.0 2608.0 1650.0 1156.0 1619.0 2081.0 2174.0 721.0 1537.0 1854.0 1879.0 10029.0 1602.0 2302.0 1047.0 4214.0 1100.0 1499.0 1367.0 622.0 1515.0 756.0 1649.0 444.0 868.0 55.0 1549.0 712.0 6814.0 1702.0 1843.0 420.0 1240.0 62.0 494.0
2021-11-07 11:36:11,681 - mmdet - INFO - pseudo mining: 10127.0 30.0 1257.0 110.0 110.0 249.0 82.0 17.0 42.0 316.0 117.0 204.0 14.0 13.0 92.0 113.0 85.0 118.0 310.0 132.0 386.0 63.0 449.0 495.0 5.0 113.0 0.0 64.0 13.0 157.0 19.0 0.0 400.0 295.0 43.0 121.0 102.0 43.0 235.0 403.0 78.0 286.0 2.0 3.0 0.0 152.0 22.0 6.0 15.0 12.0 72.0 16.0 2.0 103.0 108.0 12.0 26.0 6.0 59.0 11.0 36.0 277.0 291.0 141.0 110.0 22.0 33.0 39.0 29.0 13.0 0.0 139.0 12.0 5.0 734.0 60.0 0.0 78.0 0.0 0.0
2021-11-07 11:37:06,980 - mmdet - INFO - Evaluating bbox...
2021-11-07 11:38:17,909 - mmdet - INFO -
+---------------+-------+--------------+-------+----------------+-------+
| category | AP | category | AP | category | AP |
+---------------+-------+--------------+-------+----------------+-------+
| person | 0.423 | bicycle | 0.166 | car | 0.322 |
| motorcycle | 0.262 | airplane | 0.401 | bus | 0.496 |
| train | 0.440 | truck | 0.229 | boat | 0.140 |
| traffic light | 0.210 | fire hydrant | 0.479 | stop sign | 0.431 |
| parking meter | 0.260 | bench | 0.127 | bird | 0.206 |
| cat | 0.413 | dog | 0.391 | horse | 0.360 |
| sheep | 0.326 | cow | 0.380 | elephant | 0.461 |
| bear | 0.543 | zebra | 0.494 | giraffe | 0.508 |
| backpack | 0.064 | umbrella | 0.214 | handbag | 0.050 |
| tie | 0.169 | suitcase | 0.129 | frisbee | 0.468 |
| skis | 0.099 | snowboard | 0.102 | sports ball | 0.329 |
| kite | 0.254 | baseball bat | 0.155 | baseball glove | 0.207 |
| skateboard | 0.263 | surfboard | 0.188 | tennis racket | 0.267 |
| bottle | 0.256 | wine glass | 0.210 | cup | 0.283 |
| fork | 0.133 | knife | 0.049 | spoon | 0.042 |
| bowl | 0.284 | banana | 0.122 | apple | 0.113 |
| sandwich | 0.202 | orange | 0.204 | broccoli | 0.145 |
| carrot | 0.075 | hot dog | 0.104 | pizza | 0.362 |
| donut | 0.254 | cake | 0.179 | chair | 0.130 |
| couch | 0.236 | potted plant | 0.119 | bed | 0.260 |
| dining table | 0.168 | toilet | 0.396 | tv | 0.372 |
| laptop | 0.405 | mouse | 0.463 | remote | 0.141 |
| keyboard | 0.312 | cell phone | 0.213 | microwave | 0.339 |
| oven | 0.168 | toaster | 0.096 | sink | 0.220 |
| refrigerator | 0.302 | book | 0.041 | clock | 0.393 |
| vase | 0.222 | scissors | 0.124 | teddy bear | 0.275 |
| hair drier | 0.000 | toothbrush | 0.065 | None | None |
+---------------+-------+--------------+-------+----------------+-------+
2021-11-07 11:39:13,686 - mmdet - INFO - Evaluating bbox...
2021-11-07 11:40:27,097 - mmdet - INFO -
+---------------+-------+--------------+-------+----------------+-------+
| category | AP | category | AP | category | AP |
+---------------+-------+--------------+-------+----------------+-------+
| person | 0.447 | bicycle | 0.195 | car | 0.345 |
| motorcycle | 0.288 | airplane | 0.451 | bus | 0.497 |
| train | 0.460 | truck | 0.224 | boat | 0.165 |
| traffic light | 0.221 | fire hydrant | 0.510 | stop sign | 0.515 |
| parking meter | 0.354 | bench | 0.156 | bird | 0.239 |
| cat | 0.480 | dog | 0.418 | horse | 0.433 |
| sheep | 0.361 | cow | 0.424 | elephant | 0.490 |
| bear | 0.594 | zebra | 0.529 | giraffe | 0.539 |
| backpack | 0.078 | umbrella | 0.238 | handbag | 0.064 |
| tie | 0.192 | suitcase | 0.175 | frisbee | 0.507 |
| skis | 0.114 | snowboard | 0.141 | sports ball | 0.384 |
| kite | 0.287 | baseball bat | 0.184 | baseball glove | 0.261 |
| skateboard | 0.336 | surfboard | 0.221 | tennis racket | 0.319 |
| bottle | 0.295 | wine glass | 0.246 | cup | 0.313 |
| fork | 0.144 | knife | 0.070 | spoon | 0.057 |
| bowl | 0.327 | banana | 0.153 | apple | 0.117 |
| sandwich | 0.223 | orange | 0.215 | broccoli | 0.174 |
| carrot | 0.086 | hot dog | 0.140 | pizza | 0.379 |
| donut | 0.298 | cake | 0.206 | chair | 0.157 |
| couch | 0.285 | potted plant | 0.164 | bed | 0.281 |
| dining table | 0.163 | toilet | 0.434 | tv | 0.449 |
| laptop | 0.449 | mouse | 0.493 | remote | 0.154 |
| keyboard | 0.338 | cell phone | 0.230 | microwave | 0.428 |
| oven | 0.217 | toaster | 0.138 | sink | 0.239 |
| refrigerator | 0.354 | book | 0.053 | clock | 0.410 |
| vase | 0.268 | scissors | 0.101 | teddy bear | 0.294 |
| hair drier | 0.000 | toothbrush | 0.051 | None | None |
+---------------+-------+--------------+-------+----------------+-------+
2021-11-07 11:41:52,138 - mmdet - INFO - current percent: 0.2
2021-11-07 11:41:52,139 - mmdet - INFO - update score thr (positive): (0.99-person) (0.98-bicycle) (0.98-car) (0.99-motorcycle) (0.99-airplane) (0.99-bus) (0.99-train) (0.95-truck) (0.95-boat) (0.97-traffic light) (1.00-fire hydrant) (0.99-stop sign) (0.99-parking meter) (0.93-bench) (0.96-bird) (0.99-cat) (0.99-dog) (0.99-horse) (0.99-sheep) (0.97-cow) (1.00-elephant) (1.00-bear) (1.00-zebra) (1.00-giraffe) (0.85-backpack) (0.97-umbrella) (0.83-handbag) (0.98-tie) (0.95-suitcase) (1.00-frisbee) (0.90-skis) (0.84-snowboard) (0.99-sports ball) (0.98-kite) (0.98-baseball bat) (0.99-baseball glove) (0.99-skateboard) (0.97-surfboard) (0.99-tennis racket) (0.97-bottle) (0.99-wine glass) (0.97-cup) (0.89-fork) (0.82-knife) (0.81-spoon) (0.97-bowl) (0.95-banana) (0.82-apple) (0.95-sandwich) (0.87-orange) (0.96-broccoli) (0.90-carrot) (0.91-hot dog) (0.97-pizza) (0.98-donut) (0.96-cake) (0.90-chair) (0.94-couch) (0.97-potted plant) (0.95-bed) (0.96-dining table) (1.00-toilet) (0.99-tv) (0.99-laptop) (1.00-mouse) (0.92-remote) (0.99-keyboard) (0.95-cell phone) (0.97-microwave) (0.97-oven) (0.05-toaster) (0.99-sink) (0.99-refrigerator) (0.80-book) (1.00-clock) (0.96-vase) (0.97-scissors) (0.99-teddy bear) (0.05-hair drier) (0.81-toothbrush)
2021-11-07 11:41:52,140 - mmdet - INFO - update score thr (ignore): (0.44-person) (0.43-bicycle) (0.44-car) (0.48-motorcycle) (0.53-airplane) (0.48-bus) (0.44-train) (0.42-truck) (0.38-boat) (0.44-traffic light) (0.69-fire hydrant) (0.75-stop sign) (0.45-parking meter) (0.40-bench) (0.24-bird) (0.42-cat) (0.61-dog) (0.38-horse) (0.49-sheep) (0.34-cow) (0.78-elephant) (0.76-bear) (0.53-zebra) (0.35-giraffe) (0.38-backpack) (0.34-umbrella) (0.33-handbag) (0.37-tie) (0.42-suitcase) (0.57-frisbee) (0.34-skis) (0.33-snowboard) (0.29-sports ball) (0.43-kite) (0.40-baseball bat) (0.51-baseball glove) (0.40-skateboard) (0.38-surfboard) (0.50-tennis racket) (0.42-bottle) (0.38-wine glass) (0.35-cup) (0.25-fork) (0.33-knife) (0.30-spoon) (0.43-bowl) (0.53-banana) (0.23-apple) (0.43-sandwich) (0.29-orange) (0.65-broccoli) (0.49-carrot) (0.41-hot dog) (0.43-pizza) (0.56-donut) (0.37-cake) (0.33-chair) (0.46-couch) (0.59-potted plant) (0.38-bed) (0.47-dining table) (0.64-toilet) (0.61-tv) (0.40-laptop) (0.66-mouse) (0.36-remote) (0.43-keyboard) (0.45-cell phone) (0.56-microwave) (0.48-oven) (0.05-toaster) (0.52-sink) (0.53-refrigerator) (0.33-book) (0.74-clock) (0.46-vase) (0.55-scissors) (0.61-teddy bear) (0.05-hair drier) (0.29-toothbrush)
2021-11-07 11:41:52,400 - mmdet - INFO - Exp name: labelmatch_0.9_1_5_8.py
2021-11-07 11:41:52,401 - mmdet - INFO - Iter [8000/40000] lr: 2.000e-02, eta: 16:49:33, time: 1.686, data_time: 0.031, memory: 26485, bbox_mAP: 0.2800, bbox_mAP_50: 0.4810, bbox_mAP_75: 0.2910, bbox_mAP_s: 0.1570, bbox_mAP_m: 0.3110, bbox_mAP_l: 0.3640, bbox_mAP_copypaste: 0.280 0.481 0.291 0.157 0.311 0.364, loss_rpn_cls: 0.0338, loss_rpn_bbox: 0.0502, loss_cls: 0.2201, acc: 92.3407, loss_bbox: 0.2767, loss_rpn_cls_unlabeled: 0.0996, loss_rpn_bbox_unlabeled: 0.1040, loss_cls_unlabeled: 0.1918, acc_unlabeled: 91.4640, loss_bbox_unlabeled: 0.1901, losses_cls_ig_unlabeled: 0.1647, pseudo_num: 1.5379, pseudo_num_ig: 5.6371, pseudo_num_mining: 0.6214, pseudo_num(acc): 0.8517, pseudo_num ig(acc): 0.4559, loss: 1.3310
2021-11-07 11:43:17,476 - mmdet - INFO - Iter [8050/40000] lr: 2.000e-02, eta: 17:09:44, time: 8.474, data_time: 6.806, memory: 26485, loss_rpn_cls: 0.0367, loss_rpn_bbox: 0.0545, loss_cls: 0.2256, acc: 92.2535, loss_bbox: 0.2819, loss_rpn_cls_unlabeled: 0.0972, loss_rpn_bbox_unlabeled: 0.1018, loss_cls_unlabeled: 0.1929, acc_unlabeled: 91.3369, loss_bbox_unlabeled: 0.1833, losses_cls_ig_unlabeled: 0.1693, pseudo_num: 1.5384, pseudo_num_ig: 5.6389, pseudo_num_mining: 0.6225, pseudo_num(acc): 0.8518, pseudo_num ig(acc): 0.4559, loss: 1.3431
2021-11-07 11:44:42,990 - mmdet - INFO - Iter [8100/40000] lr: 2.000e-02, eta: 17:07:24, time: 1.713, data_time: 0.033, memory: 26485, loss_rpn_cls: 0.0348, loss_rpn_bbox: 0.0520, loss_cls: 0.2225, acc: 92.2870, loss_bbox: 0.2771, loss_rpn_cls_unlabeled: 0.0949, loss_rpn_bbox_unlabeled: 0.1003, loss_cls_unlabeled: 0.1857, acc_unlabeled: 91.7875, loss_bbox_unlabeled: 0.1771, losses_cls_ig_unlabeled: 0.1601, pseudo_num: 1.5382, pseudo_num_ig: 5.6400, pseudo_num_mining: 0.6240, pseudo_num(acc): 0.8520, pseudo_num ig(acc): 0.4561, loss: 1.3046
2021-11-07 11:46:06,244 - mmdet - INFO - Iter [8150/40000] lr: 2.000e-02, eta: 17:04:55, time: 1.665, data_time: 0.031, memory: 26485, loss_rpn_cls: 0.0358, loss_rpn_bbox: 0.0538, loss_cls: 0.2234, acc: 92.3004, loss_bbox: 0.2793, loss_rpn_cls_unlabeled: 0.0943, loss_rpn_bbox_unlabeled: 0.1017, loss_cls_unlabeled: 0.1833, acc_unlabeled: 91.6473, loss_bbox_unlabeled: 0.1788, losses_cls_ig_unlabeled: 0.1642, pseudo_num: 1.5378, pseudo_num_ig: 5.6404, pseudo_num_mining: 0.6253, pseudo_num(acc): 0.8522, pseudo_num ig(acc): 0.4562, loss: 1.3146
2021-11-07 11:47:29,894 - mmdet - INFO - Iter [8200/40000] lr: 2.000e-02, eta: 17:02:29, time: 1.673, data_time: 0.030, memory: 26485, loss_rpn_cls: 0.0362, loss_rpn_bbox: 0.0511, loss_cls: 0.2252, acc: 92.2660, loss_bbox: 0.2816, loss_rpn_cls_unlabeled: 0.0932, loss_rpn_bbox_unlabeled: 0.1039, loss_cls_unlabeled: 0.1866, acc_unlabeled: 91.5034, loss_bbox_unlabeled: 0.1802, losses_cls_ig_unlabeled: 0.1612, pseudo_num: 1.5377, pseudo_num_ig: 5.6424, pseudo_num_mining: 0.6269, pseudo_num(acc): 0.8524, pseudo_num ig(acc): 0.4562, loss: 1.3193
2021-11-07 11:48:54,497 - mmdet - INFO - Iter [8250/40000] lr: 2.000e-02, eta: 17:00:07, time: 1.695, data_time: 0.031, memory: 26485, loss_rpn_cls: 0.0331, loss_rpn_bbox: 0.0492, loss_cls: 0.2101, acc: 92.6997, loss_bbox: 0.2638, loss_rpn_cls_unlabeled: 0.0897, loss_rpn_bbox_unlabeled: 0.1017, loss_cls_unlabeled: 0.1832, acc_unlabeled: 91.8334, loss_bbox_unlabeled: 0.1761, losses_cls_ig_unlabeled: 0.1627, pseudo_num: 1.5374, pseudo_num_ig: 5.6422, pseudo_num_mining: 0.6279, pseudo_num(acc): 0.8525, pseudo_num ig(acc): 0.4563, loss: 1.2696
2021-11-07 11:50:20,492 - mmdet - INFO - Iter [8300/40000] lr: 2.000e-02, eta: 16:57:51, time: 1.719, data_time: 0.027, memory: 26485, loss_rpn_cls: 0.0348, loss_rpn_bbox: 0.0516, loss_cls: 0.2228, acc: 92.2566, loss_bbox: 0.2761, loss_rpn_cls_unlabeled: 0.0950, loss_rpn_bbox_unlabeled: 0.0999, loss_cls_unlabeled: 0.1823, acc_unlabeled: 91.4923, loss_bbox_unlabeled: 0.1780, losses_cls_ig_unlabeled: 0.1699, pseudo_num: 1.5375, pseudo_num_ig: 5.6425, pseudo_num_mining: 0.6292, pseudo_num(acc): 0.8527, pseudo_num ig(acc): 0.4564, loss: 1.3104