Environment information (required)

Please run diagnose_tensorboard.py (link below) in the same environment from which you normally run TensorFlow/TensorBoard, and paste the output here:

Diagnostics

Diagnostics output

`````` --- check: autoidentify INFO: diagnose_tensorboard.py version 393931f9685bd7e0f3898d7dcdf28819fef54c43 --- check: general INFO: sys.version_info: sys.version_info(major=3, minor=6, micro=5, releaselevel='final', serial=0) INFO: os.name: posix INFO: os.uname(): posix.uname_result(sysname='Linux', nodename='smok', release='4.15.0-45-generic', version='#48-Ubuntu SMP Tue Jan 29 16:28:13 UTC 2019', machine='x86_64') INFO: sys.getwindowsversion(): N/A --- check: package_management INFO: has conda-meta: False INFO: $VIRTUAL_ENV: '/home/wokoziej/envs/mate' --- check: installed_packages INFO: installed: tensorboard==1.14.0 INFO: installed: tensorflow==1.14.0 INFO: installed: tensorflow-estimator==1.14.0 --- check: tensorboard_python_version INFO: tensorboard.version.VERSION: '1.14.0' --- check: tensorflow_python_version INFO: tensorflow.__version__: '1.14.0' INFO: tensorflow.__git_version__: 'v1.14.0-rc1-22-gaf24dc91b5' --- check: tensorboard_binary_path INFO: which tensorboard: b'/home/wokoziej/envs/mate/bin/tensorboard\n' --- check: readable_fqdn INFO: socket.getfqdn(): 'smok' --- check: stat_tensorboardinfo INFO: directory: /tmp/.tensorboard-info INFO: os.stat(...): os.stat_result(st_mode=16893, st_ino=781949450, st_dev=64772, st_nlink=2, st_uid=1024, st_gid=1024, st_size=28, st_atime=1562229106, st_mtime=1562578950, st_ctime=1562578950) INFO: mode: 0o40775 --- check: source_trees_without_genfiles INFO: tensorboard_roots (1): ['/home/wokoziej/envs/mate/lib/python3.6/site-packages']; bad_roots (0): [] --- check: full_pip_freeze INFO: pip freeze --all: absl-py==0.7.0 albumentations==0.2.3 astor==0.7.1 atomicwrites==1.3.0 attrs==19.1.0 backcall==0.1.0 bleach==3.1.0 certifi==2018.11.29 chardet==3.0.4 cloudpickle==0.7.0 coverage==4.5.3 cycler==0.10.0 dask==1.1.0 decorator==4.3.2 defusedxml==0.5.0 dependency-injector==3.13.2 entrypoints==0.3 filelock==3.0.10 gast==0.2.2 google-pasta==0.1.7 grpcio==1.18.0 h5py==2.9.0 idna==2.8 imageio==2.4.1 imgaug==0.2.6 imutils==0.5.2 ipykernel==5.1.0 ipython==7.2.0 ipython-genutils==0.2.0 ipywidgets==7.4.2 jedi==0.13.2 Jinja2==2.10 jsonschema==2.6.0 jupyter-client==5.2.4 jupyter-core==4.4.0 Keras-Applications==1.0.7 Keras-Preprocessing==1.0.6 kiwisolver==1.0.1 Markdown==3.0.1 MarkupSafe==1.1.0 matplotlib==3.0.2 mistune==0.8.4 more-itertools==7.0.0 nbconvert==5.4.0 nbformat==4.4.0 networkx==2.2 notebook==5.7.4 numpy==1.15.4 opencv-python==4.0.0.21 opencv-python-headless==4.1.0.25 pandas==0.24.0 pandocfilters==1.4.2 parso==0.3.2 pexpect==4.6.0 pickleshare==0.7.5 pika==0.12.0 Pillow==5.3.0 pip==19.0.1 plotly==3.5.0 pluggy==0.9.0 prometheus-client==0.5.0 prompt-toolkit==2.0.8 protobuf==3.6.1 ptyprocess==0.6.0 py==1.8.0 Pygments==2.3.1 pymongo==3.8.0 pyparsing==2.3.1 Pypubsub==4.0.0 pytest==4.5.0 pytest-cov==2.7.1 pytest-mock==1.10.4 python-dateutil==2.7.5 pytz==2018.9 PyWavelets==1.0.1 pyzmq==17.1.2 requests==2.21.0 retrying==1.3.3 scikit-image==0.14.2 scipy==1.2.0 Send2Trash==1.5.0 setuptools==41.0.1 Shapely==1.6.4.post2 six==1.11.0 tensorboard==1.14.0 tensorflow==1.14.0 tensorflow-estimator==1.14.0 termcolor==1.1.0 terminado==0.8.1 testpath==0.4.2 toml==0.10.0 toolz==0.9.0 tornado==5.1.1 tox==3.7.0 tqdm==4.30.0 traitlets==4.3.2 urllib3==1.24.1 virtualenv==16.4.1 wcwidth==0.1.7 webencodings==0.5.1 Werkzeug==0.14.1 wheel==0.32.3 widgetsnbextension==3.4.2 wrapt==1.11.2 xlwt==1.3.0 xmltodict==0.11.0 ``````

Suggestion: Fix permissions on "/tmp/.tensorboard-info"

The ".tensorboard-info" directory was created by an old version of TensorBoard, and its permissions are not set correctly; see issue

2010. Change that directory to be world-accessible (may require

superuser privilege):

chmod 777 /tmp/.tensorboard-info

Next steps

Please try each suggestion enumerated above to determine whether it solves your problem. If none of these suggestions works, please copy ALL of the above output, including the lines containing only backticks, into your GitHub issue or comment. Be sure to redact any sensitive information.

Issue description

As I wrote:

I run training

python object_detection/model_main.py --pipeline_config_path=/mnt/data/environments/bag/100bboxes/pipeline.config --model_dir=/mnt/data/environments/bag/100bboxes/exp

This is only one step training and its goal is to visualize bounding boxes in tensorboard images tam. On the "IMAGES" tab in tensorboard I don't see all bounding boxes which are in the tfrecord file. Options provided in the pipeline.config

num_visualizations: 200                                                                                                                   
max_num_boxes_to_visualize: 200

have no effect on this.

Describe the expected behavior I see all bounding boxes (ground thruth) in the tensorboard>images (pictures on the right)

Code to reproduce the issue I've created repo where you can find

pipeline.config - one step training, the same tfrecord for training and evaluation
classes.pbtxt - two sample classes
t.tfrecord - containg two white images: one with 100 bounding boxes and second with 200 bounding boxes
notebook-images-view.png - view from notebook when I've tried visualise bboxes
tensorboard-images-view.png - tensorboard images view

tensorflow / tensorboard

Tensorboard does not display more then 100 bounding boxes #2413