Issues with image data update in `IMAGES` panel

Hi! I am currently using Tensorboard and have encountered an issue.
The description is as follows:

Environment information (required)

Operating System: Windows 10 Home Edition

Web Browser: Chrome (version 93.0.4577.63)

Diagnostics Output:

--- check: autoidentify
INFO: diagnose_tensorboard.py version e43767ef2b648d0d5d57c00f38ccbd38390e38da

--- check: general
INFO: sys.version_info: sys.version_info(major=3, minor=8, micro=5, releaselevel='final', serial=0)
INFO: os.name: nt
INFO: os.uname(): N/A
INFO: sys.getwindowsversion(): sys.getwindowsversion(major=10, minor=0, build=19042, platform=2, service_pack='')

--- check: package_management
INFO: has conda-meta: True
INFO: $VIRTUAL_ENV: None

--- check: installed_packages
INFO: installed: tensorboard==2.5.0
INFO: installed: tensorflow==2.5.0
INFO: installed: tensorflow-estimator==2.5.0
INFO: installed: tensorboard-data-server==0.6.1

--- check: tensorboard_python_version
INFO: tensorboard.version.VERSION: '2.5.0'

--- check: tensorflow_python_version
2021-09-04 14:06:03.149092: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library cudart64_110.dll
INFO: tensorflow.__version__: '2.5.0'
INFO: tensorflow.__git_version__: 'v2.5.0-rc3-213-ga4dfb8d1a71'

--- check: tensorboard_data_server_version
INFO: data server binary: None

--- check: tensorboard_binary_path
INFO: which tensorboard: b'C:\\Users\\joonjeon\\miniconda3\\Scripts\\tensorboard.exe\r\n'

--- check: addrinfos
socket.has_ipv6 = True
socket.AF_UNSPEC = <AddressFamily.AF_UNSPEC: 0>
socket.SOCK_STREAM = <SocketKind.SOCK_STREAM: 1>
socket.AI_ADDRCONFIG = <AddressInfo.AI_ADDRCONFIG: 1024>
socket.AI_PASSIVE = <AddressInfo.AI_PASSIVE: 1>
Loopback flags: <AddressInfo.AI_ADDRCONFIG: 1024>
Loopback infos: [(<AddressFamily.AF_INET6: 23>, <SocketKind.SOCK_STREAM: 1>, 0, '', ('::1', 0, 0, 0)), (<AddressFamily.AF_INET: 2>, <SocketKind.SOCK_STREAM: 1>, 0, '', ('127.0.0.1', 0))]
Wildcard flags: <AddressInfo.AI_PASSIVE: 1>
Wildcard infos: [(<AddressFamily.AF_INET6: 23>, <SocketKind.SOCK_STREAM: 1>, 0, '', ('::', 0, 0, 0)), (<AddressFamily.AF_INET: 2>, <SocketKind.SOCK_STREAM: 1>, 0, '', ('0.0.0.0', 0))]

--- check: readable_fqdn
INFO: socket.getfqdn(): 'DESKTOP-JOONJEON'

--- check: stat_tensorboardinfo
INFO: directory: C:\Users\joonjeon\AppData\Local\Temp\.tensorboard-info
INFO: os.stat(...): os.stat_result(st_mode=16895, st_ino=16325548649238242, st_dev=2456407384, st_nlink=1, st_uid=0, st_gid=0, st_size=0, st_atime=1630731956, st_mtime=1630731956, st_ctime=1627466907)
INFO: mode: 0o40777

--- check: source_trees_without_genfiles
INFO: tensorboard_roots (1): ['C:\\Users\\joonjeon\\miniconda3\\lib\\site-packages']; bad_roots (0): []

--- check: full_pip_freeze
INFO: pip freeze --all:
absl-py==0.13.0
astunparse==1.6.3
attrs==21.2.0
brotlipy==0.7.0
cachetools==4.2.2
certifi==2020.6.20
cffi @ file:///C:/ci/cffi_1605538112425/work
chardet @ file:///C:/ci/chardet_1605303225733/work
conda==4.9.2
conda-package-handling @ file:///C:/ci/conda-package-handling_1603003327818/work
cryptography @ file:///C:/ci/cryptography_1605526388508/work
cycler==0.10.0
dill==0.3.4
flatbuffers==1.12
future==0.18.2
gast==0.4.0
google-auth==1.32.1
google-auth-oauthlib==0.4.4
google-pasta==0.2.0
googleapis-common-protos==1.53.0
grpcio==1.34.1
h5py==3.1.0
idna @ file:///tmp/build/80754af9/idna_1593446292537/work
importlib-resources==5.2.0
keras-nightly==2.5.0.dev2021032900
Keras-Preprocessing==1.1.2
kiwisolver==1.3.1
lxml==4.6.3
Markdown==3.3.4
matplotlib==3.4.2
menuinst==1.4.16
numpy==1.19.5
oauthlib==3.1.1
opencv-python==4.5.3.56
opt-einsum==3.3.0
Pillow==8.2.0
pip==20.2.4
promise==2.3
protobuf==3.17.3
pyasn1==0.4.8
pyasn1-modules==0.2.8
pycosat==0.6.3
pycparser @ file:///tmp/build/80754af9/pycparser_1594388511720/work
pyOpenSSL @ file:///tmp/build/80754af9/pyopenssl_1605545627475/work
pyparsing==2.4.7
PySocks @ file:///C:/ci/pysocks_1605287845585/work
python-dateutil==2.8.1
pywin32==227
PyYAML==5.4.1
requests @ file:///tmp/build/80754af9/requests_1592841827918/work
requests-oauthlib==1.3.0
rsa==4.7.2
ruamel-yaml==0.15.87
scipy==1.6.3
setuptools==50.3.1.post20201107
six @ file:///C:/ci/six_1605187374963/work
tensorboard==2.5.0
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.0
tensorflow==2.5.0
tensorflow-datasets==4.3.0
tensorflow-estimator==2.5.0
tensorflow-metadata==1.1.0
termcolor==1.1.0
tqdm @ file:///tmp/build/80754af9/tqdm_1605303662894/work
typing-extensions==3.7.4.3
urllib3 @ file:///tmp/build/80754af9/urllib3_1603305693037/work
Werkzeug==2.0.1
wheel==0.35.1
win-inet-pton @ file:///C:/ci/win_inet_pton_1605306167264/work
wincertstore==0.2
wrapt==1.12.1
zipp==3.5.0

Issue description

I have built some object detection model (e.g. Faster R-CNN).
Then, I tried to check if it the detection output images are being visualized properly.
The detected bounding boxes are drawn on the test set images using pillow module,
and the images were to be displayed on the IMAGES panel using tf.summary.image function.
However, after first epoch of training and testing, even after numerous epochs of training,
no further update is being applied to the images shown on the IMAGES panel.

Note that this issue is still being reproduced when using higher versions of Tensorflow and Tensorboard (e.g. 2.6.0),
and the issue persists regardless of hardware specifications of the computer I am using.
Meanwhile, the issue is NOT reproduced when using Ubuntu 18.04 and Firefox Web browser.

Is there a way I could fix this issue? Or is this an ongoing official issue of Tensorboard?

Please pardon me if this is a duplicate posting of the issue previously mentioned.
If there are any other necessary information, please let me know.

Thanks in advance.