psybuzz
commented
3 years ago Thanks for the report, I can also reproduce this using bazel run tensorboard/plugins/projector/vz_projector:standalone (standalone version of the projector, and assuming that the integrated version works similarly).
evolu8
ss-hyun
In 2023, I met the same problem. Is this problem still going on?
Environment information (required)
Fresh conda env, TB-Version 2.4.1 Diagnose output:
Diagnostics output
`````` --- check: autoidentify INFO: diagnose_tensorboard.py version e43767ef2b648d0d5d57c00f38ccbd38390e38da --- check: general INFO: sys.version_info: sys.version_info(major=3, minor=7, micro=6, releaselevel='final', serial=0) INFO: os.name: posix INFO: os.uname(): posix.uname_result(sysname='Linux', nodename='dbe-graph-machine-learning', release='5.4.0-58-generic', version='#64~18.04.1-Ubuntu SMP Wed Dec 9 17:11:11 UTC 2020', machine='x86_64') INFO: sys.getwindowsversion(): N/A --- check: package_management INFO: has conda-meta: True INFO: $VIRTUAL_ENV: None --- check: installed_packages WARNING: no installation among: ['tb-nightly', 'tensorboard', 'tensorflow-tensorboard'] WARNING: no installation among: ['tensorflow', 'tensorflow-gpu', 'tf-nightly', 'tf-nightly-2.0-preview', 'tf-nightly-gpu', 'tf-nightly-gpu-2.0-preview'] WARNING: no installation among: ['tensorflow-estimator', 'tensorflow-estimator-2.0-preview', 'tf-estimator-nightly'] --- check: tensorboard_python_version INFO: tensorboard.version.VERSION: '2.4.1' --- check: tensorflow_python_version Traceback (most recent call last): File "diagnose_tensorboard.py", line 522, in main suggestions.extend(check()) File "diagnose_tensorboard.py", line 75, in wrapper result = fn() File "diagnose_tensorboard.py", line 278, in tensorflow_python_version import tensorflow as tf ModuleNotFoundError: No module named 'tensorflow' --- check: tensorboard_data_server_version INFO: no data server installed --- check: tensorboard_binary_path INFO: which tensorboard: b'/home/dbelousow/.conda/envs/tensorboard/bin/tensorboard\n' --- check: addrinfos socket.has_ipv6 = True socket.AF_UNSPEC =Issue description
When isolating points in a point cloud to a reduced number. The image preview uses the wrong images from the sprite.png. (see screenshots below). First screenshot shows a randomly chosen point in an embedding and it is showing the correct images as nearest neighbors. Second screenshot shows what happens when one isolates the neighbors to a few points. I guess the index of the image position is not saved and the projectors starts counting at 0 when matching the new list of points.
