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Bump to 1.4.1a3 #1972

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Bump to 1.4.1a3 #1972

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roomrys
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@roomrys roomrys commented Sep 26, 2024

Description

This prerelease is the prerelease before we upgrade our python version to 3.10 in the 1.4.1a4 prerelease (followed by 1.4.1 if all goes well).

Types of changes

  • Bugfix
  • New feature
  • Refactor / Code style update (no logical changes)
  • Build / CI changes
  • Documentation Update
  • Other (prerelease)

Does this address any currently open issues?

Outside contributors checklist

  • Review the guidelines for contributing to this repository
  • Read and sign the CLA and add yourself to the authors list
  • Make sure you are making a pull request against the develop branch (not main). Also you should start your branch off develop
  • Add tests that prove your fix is effective or that your feature works
  • Add necessary documentation (if appropriate)

Thank you for contributing to SLEAP!

❤️

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coderabbitai bot commented Sep 26, 2024 •
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codecov bot commented Sep 26, 2024 •
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Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 75.51%. Comparing base (7ed1229) to head (0df062f).
Report is 56 commits behind head on develop.

Additional details and impacted files 
@@             Coverage Diff             @@
##           develop    #1972      +/-   ##
===========================================
+ Coverage    73.30%   75.51%   +2.20%     
===========================================
  Files          134      133       -1     
  Lines        24087    24635     +548     
===========================================
+ Hits         17658    18602     +944     
+ Misses        6429     6033     -396

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

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roomrys commented Sep 27, 2024 •
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Mac (manual test)

Backwards compatibility

image

To test backwards compatibility, we saved a project in v1.4.1a3 and then tried opening that project in liezl/add-elements-for-gui-sessions branch (off 1.3.3).

pip freeze 
pip freeze
absl-py @ file:///home/conda/feedstock_root/build_artifacts/absl-py_1705494584803/work
accessible-pygments==0.0.5
aiohappyeyeballs @ file:///home/conda/feedstock_root/build_artifacts/aiohappyeyeballs_1724167852130/work
aiohttp @ file:///Users/runner/miniforge3/conda-bld/aiohttp_1726062809260/work
aiosignal @ file:///home/conda/feedstock_root/build_artifacts/aiosignal_1667935791922/work
alabaster==0.7.16
aniposelib==0.5.1
anyio==3.7.1
appdirs==1.4.4
appnope==0.1.4
argon2-cffi==23.1.0
argon2-cffi-bindings==21.2.0
asttokens==2.4.1
astunparse @ file:///home/conda/feedstock_root/build_artifacts/astunparse_1610696312422/work
async-timeout @ file:///home/conda/feedstock_root/build_artifacts/async-timeout_1691763562544/work
attrs==21.4.0
babel==2.16.0
backports.tarfile==1.2.0
beautifulsoup4==4.12.3
black==21.6b0
bleach==6.1.0
blinker @ file:///home/conda/feedstock_root/build_artifacts/blinker_1715091184126/work
Brotli @ file:///Users/runner/miniforge3/conda-bld/brotli-split_1687884292427/work
cached-property @ file:///home/conda/feedstock_root/build_artifacts/cached_property_1615209429212/work
cachetools @ file:///home/conda/feedstock_root/build_artifacts/cachetools_1724028158384/work
cattrs @ file:///home/conda/feedstock_root/build_artifacts/cattrs_1604136207372/work
certifi @ file:///home/conda/feedstock_root/build_artifacts/certifi_1725278078093/work/certifi
cffi @ file:///Users/runner/miniforge3/conda-bld/cffi_1725560622100/work
cfgv==3.4.0
charset-normalizer @ file:///home/conda/feedstock_root/build_artifacts/charset-normalizer_1698833585322/work
click==8.0.4
colorama==0.4.6
comm==0.2.2
contourpy @ file:///Users/runner/miniforge3/conda-bld/contourpy_1712429965428/work
coverage==7.6.1
cryptography @ file:///Users/runner/miniforge3/conda-bld/cryptography-split_1672673285537/work
cycler @ file:///home/conda/feedstock_root/build_artifacts/cycler_1696677705766/work
debugpy==1.8.6
decorator==5.1.1
defusedxml==0.7.1
Deprecated==1.2.14
distlib==0.3.8
docutils==0.17.1
efficientnet==1.0.0
entrypoints==0.4
exceptiongroup==1.2.2
executing==2.1.0
filelock==3.16.1
flatbuffers @ file:///home/conda/feedstock_root/build_artifacts/python-flatbuffers_1617723079010/work
fonttools @ file:///Users/runner/miniforge3/conda-bld/fonttools_1727206370939/work
frozenlist @ file:///Users/runner/miniforge3/conda-bld/frozenlist_1725395672929/work
gast @ file:///home/conda/feedstock_root/build_artifacts/gast_1596839682936/work
gitdb==4.0.11
GitPython==3.1.43
google-auth @ file:///home/conda/feedstock_root/build_artifacts/google-auth_1726832896641/work
google-auth-oauthlib @ file:///home/conda/feedstock_root/build_artifacts/google-auth-oauthlib_1630497468950/work
google-pasta @ file:///home/conda/feedstock_root/build_artifacts/google-pasta_1722873999312/work
grpcio @ file:///Users/runner/miniforge3/conda-bld/grpc-split_1660663644663/work
h11==0.14.0
h2 @ file:///home/conda/feedstock_root/build_artifacts/h2_1634280454336/work
h5py @ file:///Users/runner/miniforge3/conda-bld/h5py_1674499003063/work
hdmf==3.14.4
hpack==4.0.0
hyperframe @ file:///home/conda/feedstock_root/build_artifacts/hyperframe_1619110129307/work
identify==2.6.1
idna @ file:///home/conda/feedstock_root/build_artifacts/idna_1726459485162/work
image-classifiers==1.0.0
imagecodecs @ file:///Users/runner/miniforge3/conda-bld/imagecodecs_1668867616820/work
imageio @ file:///home/conda/feedstock_root/build_artifacts/imageio_1724069053555/work
imageio-ffmpeg==0.5.1
imagesize==1.4.1
imgaug @ file:///home/conda/feedstock_root/build_artifacts/imgaug_1640909786103/work
imgstore==0.2.9
importlib_metadata @ file:///home/conda/feedstock_root/build_artifacts/importlib-metadata_1726082825846/work
importlib_resources @ file:///home/conda/feedstock_root/build_artifacts/importlib_resources_1725921340658/work
iniconfig==2.0.0
ipykernel==6.29.5
ipython==8.18.1
ipython-genutils==0.2.0
ipywidgets==7.8.4
jaraco.classes==3.4.0
jaraco.context==6.0.1
jaraco.functools==4.0.2
jedi==0.17.2
Jinja2==3.1.4
joblib @ file:///home/conda/feedstock_root/build_artifacts/joblib_1714665484399/work
jsmin @ file:///home/conda/feedstock_root/build_artifacts/jsmin_1642532731678/work
json5==0.9.25
jsonpickle==1.2
jsonschema==4.17.3
jupyter-cache==0.4.3
jupyter-server==1.13.5
jupyter-server-mathjax==0.2.6
jupyter-sphinx==0.3.2
jupyter_client==7.4.9
jupyter_core==5.7.2
jupyterlab==3.3.4
jupyterlab_pygments==0.3.0
jupyterlab_server==2.16.3
jupyterlab_widgets==1.1.10
keras @ file:///home/conda/feedstock_root/build_artifacts/keras_1652925255303/work/keras-2.9.0-py2.py3-none-any.whl
Keras-Applications==1.0.8
Keras-Preprocessing @ file:///home/conda/feedstock_root/build_artifacts/keras-preprocessing_1610713559828/work
keyring==25.4.1
kiwisolver @ file:///Users/runner/miniforge3/conda-bld/kiwisolver_1725459226886/work
lazy_loader @ file:///home/conda/feedstock_root/build_artifacts/lazy-loader_1723774329602/work
libclang==18.1.1
linkify-it-py==2.0.3
llvmlite==0.43.0
lxml==5.3.0
Markdown @ file:///home/conda/feedstock_root/build_artifacts/markdown_1710435156458/work
markdown-it-py==1.1.0
MarkupSafe @ file:///Users/runner/miniforge3/conda-bld/markupsafe_1724959498027/work
matplotlib @ file:///Users/runner/miniforge3/conda-bld/matplotlib-suite_1715976202591/work
matplotlib-inline==0.1.7
mdit-py-plugins==0.2.8
mdurl @ file:///home/conda/feedstock_root/build_artifacts/mdurl_1704317613764/work
mistune==0.8.4
more-itertools==10.5.0
multidict @ file:///Users/runner/miniforge3/conda-bld/multidict_1725953662279/work
munkres==1.1.4
mypy-extensions==1.0.0
myst-nb==0.13.2
myst-parser==0.15.2
nbclassic==0.5.6
nbclient==0.5.13
nbconvert==6.5.4
nbdime==4.0.2
nbformat==5.1.3
ndx-pose==0.1.1
nest-asyncio==1.6.0
networkx @ file:///home/conda/feedstock_root/build_artifacts/networkx_1698504735452/work
nh3==0.2.18
nixio==1.5.3
nodeenv==1.9.1
notebook==6.5.7
notebook_shim==0.2.4
numba==0.60.0
numpy==1.24.4
oauthlib @ file:///home/conda/feedstock_root/build_artifacts/oauthlib_1666056362788/work
opencv-contrib-python==4.6.0.66
opencv-python==4.6.0
opt-einsum @ file:///home/conda/feedstock_root/build_artifacts/opt_einsum_1696448916724/work
packaging @ file:///home/conda/feedstock_root/build_artifacts/packaging_1718189413536/work
pandas @ file:///Users/runner/miniforge3/conda-bld/pandas_1715897641697/work
pandocfilters==1.5.1
parso==0.7.1
pathspec==0.12.1
patsy @ file:///home/conda/feedstock_root/build_artifacts/patsy_1704469236901/work
pexpect==4.9.0
Pillow @ file:///Users/runner/miniforge3/conda-bld/pillow_1666920692505/work
pkginfo==1.11.1
platformdirs==4.3.6
pluggy==1.5.0
pre-commit==3.8.0
prometheus_client==0.21.0
prompt_toolkit==3.0.47
protobuf==3.19.6
psutil @ file:///Users/runner/miniforge3/conda-bld/psutil_1725737869566/work
ptyprocess==0.7.0
pure_eval==0.2.3
pyasn1 @ file:///home/conda/feedstock_root/build_artifacts/pyasn1_1726839225972/work
pyasn1_modules @ file:///home/conda/feedstock_root/build_artifacts/pyasn1-modules_1726029546107/work
pycparser @ file:///home/conda/feedstock_root/build_artifacts/pycparser_1711811537435/work
pydata-sphinx-theme==0.13.3
PyGithub==2.4.0
Pygments @ file:///home/conda/feedstock_root/build_artifacts/pygments_1714846767233/work
PyJWT @ file:///home/conda/feedstock_root/build_artifacts/pyjwt_1722701264352/work
pykalman @ file:///home/conda/feedstock_root/build_artifacts/pykalman_1711547707628/work
PyNaCl==1.5.0
pynwb==2.8.2
pyOpenSSL @ file:///home/conda/feedstock_root/build_artifacts/pyopenssl_1685514481738/work
pyparsing @ file:///home/conda/feedstock_root/build_artifacts/pyparsing_1724616129934/work
pyrsistent==0.20.0
PySide2==5.15.8
PySocks @ file:///home/conda/feedstock_root/build_artifacts/pysocks_1661604839144/work
pytest==8.3.3
pytest-cov==3.0.0
pytest-qt==4.4.0
pytest-xvfb==3.0.0
python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1709299778482/work
python-rapidjson @ file:///Users/runner/miniforge3/conda-bld/python-rapidjson_1722901830846/work
pytz @ file:///home/conda/feedstock_root/build_artifacts/pytz_1726055524169/work
pyu2f @ file:///home/conda/feedstock_root/build_artifacts/pyu2f_1604248910016/work
PyVirtualDisplay==3.0
PyWavelets==1.6.0
PyYAML @ file:///Users/runner/miniforge3/conda-bld/pyyaml_1725456248054/work
pyzmq @ file:///Users/runner/miniforge3/conda-bld/pyzmq_1725430538615/work
qimage2ndarray==1.10.0
QtPy @ file:///home/conda/feedstock_root/build_artifacts/qtpy_1698112029416/work
readme_renderer==43.0
regex==2024.9.11
requests @ file:///home/conda/feedstock_root/build_artifacts/requests_1717057054362/work
requests-oauthlib @ file:///home/conda/feedstock_root/build_artifacts/requests-oauthlib_1711290127547/work
requests-toolbelt==1.0.0
rfc3986==2.0.0
rich @ file:///home/conda/feedstock_root/build_artifacts/rich_1726066019428/work/dist
rsa @ file:///home/conda/feedstock_root/build_artifacts/rsa_1658328885051/work
ruamel.yaml==0.18.6
ruamel.yaml.clib==0.2.8
scikit-image @ file:///Users/runner/miniforge3/conda-bld/scikit-image_1719499452114/work/dist/scikit_image-0.24.0-cp39-cp39-macosx_11_0_arm64.whl#sha256
=99a9d204a057340ff924741a9aa0c4fdd1ef9e918063988d46ba4645bcedbc64                                                                                       scikit-learn @ file:///Users/runner/miniforge3/conda-bld/scikit-learn_1632611447519/work
scikit-video==1.1.11
scipy==1.9.0
seaborn @ file:///home/conda/feedstock_root/build_artifacts/seaborn-split_1714494649443/work
segmentation-models==1.0.1
Send2Trash==1.8.3
shapely @ file:///Users/runner/miniforge3/conda-bld/shapely_1725393950858/work
shiboken2==5.15.8
six==1.15.0
-e git+https://github.com/talmolab/sleap@69e00b1ae946545b29311cc133b559ef7a500618#egg=sleap
sleap-anipose==0.1.8
smmap==5.0.1
sniffio==1.3.1
snowballstemmer==2.2.0
soupsieve==2.6
Sphinx==4.5.0
sphinx-autobuild==2024.9.19
sphinx-book-theme==1.0.1
sphinx-copybutton==0.5.2
sphinx-togglebutton==0.3.2
sphinxcontrib-applehelp==2.0.0
sphinxcontrib-devhelp==2.0.0
sphinxcontrib-htmlhelp==2.1.0
sphinxcontrib-jsmath==1.0.1
sphinxcontrib-qthelp==2.0.0
sphinxcontrib-serializinghtml==2.0.0
SQLAlchemy==1.4.54
stack-data==0.6.3
starlette==0.39.0
statsmodels @ file:///Users/runner/miniforge3/conda-bld/statsmodels_1726899020978/work
tensorboard @ file:///home/conda/feedstock_root/build_artifacts/tensorboard_1651519171059/work/tensorboard-2.9.0-py3-none-any.whl
tensorboard-data-server @ file:///Users/runner/miniforge3/conda-bld/tensorboard-data-server_1670043861058/work/tensorboard_data_server-0.6.1-py3-none-ma
cosx_11_0_arm64.whl                                                                                                                                     tensorboard-plugin-wit @ file:///home/conda/feedstock_root/build_artifacts/tensorboard-plugin-wit_1641458951060/work/tensorboard_plugin_wit-1.8.1-py3-no
ne-any.whl                                                                                                                                              tensorflow @ file:///Users/ngam/Repos/tensorflow-feedstock/miniforge3/conda-bld/tensorflow-split_1658102176686/work/tensorflow_pkg/tensorflow-2.9.1-cp39
-cp39-macosx_11_0_arm64.whl                                                                                                                             tensorflow-estimator @ file:///Users/ngam/Repos/tensorflow-feedstock/miniforge3/conda-bld/tensorflow-split_1658102176686/work/tensorflow-estimator/wheel
_dir/tensorflow_estimator-2.9.0-py2.py3-none-any.whl                                                                                                    tensorflow-hub @ file:///home/conda/feedstock_root/build_artifacts/tensorflow-hub_1618768305670/work/wheel_dir/tensorflow_hub-0.12.0-py2.py3-none-any.wh
l                                                                                                                                                       tensorflow-macos==2.9.2
tensorflow-metal==0.5.0
termcolor @ file:///home/conda/feedstock_root/build_artifacts/termcolor_1704357939450/work
terminado==0.18.1
threadpoolctl @ file:///home/conda/feedstock_root/build_artifacts/threadpoolctl_1714400101435/work
tifffile @ file:///home/conda/feedstock_root/build_artifacts/tifffile_1665588749940/work
tinycss2==1.3.0
toml==0.10.2
tomli==2.0.1
tornado==6.4.1
tqdm==4.66.5
traitlets==5.14.3
twine==3.3.0
typing_extensions @ file:///home/conda/feedstock_root/build_artifacts/typing_extensions_1717802530399/work
tzdata @ file:///home/conda/feedstock_root/build_artifacts/python-tzdata_1727140567071/work
tzlocal==5.2
uc-micro-py==1.0.3
unicodedata2 @ file:///Users/runner/miniforge3/conda-bld/unicodedata2_1695848020028/work
urllib3 @ file:///home/conda/feedstock_root/build_artifacts/urllib3_1726496430923/work
uvicorn==0.30.6
virtualenv==20.26.5
watchfiles==0.24.0
wcwidth==0.2.13
webencodings==0.5.1
websocket-client==1.8.0
websockets==13.1
Werkzeug @ file:///home/conda/feedstock_root/build_artifacts/werkzeug_1724330738730/work
widgetsnbextension==3.6.9
wrapt @ file:///Users/runner/miniforge3/conda-bld/wrapt_1724957887775/work
yarl @ file:///Users/runner/miniforge3/conda-bld/yarl_1726055125213/work
zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1726248574750/work
zstandard==0.23.0
mamba list 
micromamba list
List of packages in environment: "/Users/liezl/micromamba/envs/sa0"

  Name                       Version       Build                   Channel    
────────────────────────────────────────────────────────────────────────────────
  abseil-cpp                 20211102.0    he4e09e4_3              conda-forge
  absl-py                    2.1.0         pyhd8ed1ab_0            conda-forge
  aiohappyeyeballs           2.4.0         pyhd8ed1ab_0            conda-forge
  aiohttp                    3.10.5        py39h06df861_1          conda-forge
  aiosignal                  1.3.1         pyhd8ed1ab_0            conda-forge
  aom                        3.5.0         h7ea286d_0              conda-forge
  astunparse                 1.6.3         pyhd8ed1ab_0            conda-forge
  async-timeout              4.0.3         pyhd8ed1ab_0            conda-forge
  attrs                      24.2.0        pyh71513ae_0            conda-forge
  blas                       2.120         openblas                conda-forge
  blas-devel                 3.9.0         20_osxarm64_openblas    conda-forge
  blinker                    1.8.2         pyhd8ed1ab_0            conda-forge
  blosc                      1.21.5        hc338f07_0              conda-forge
  brotli                     1.0.9         h1a8c8d9_9              conda-forge
  brotli-bin                 1.0.9         h1a8c8d9_9              conda-forge
  brotli-python              1.0.9         py39h23fbdae_9          conda-forge
  brunsli                    0.1           h9f76cd9_0              conda-forge
  bzip2                      1.0.8         h99b78c6_7              conda-forge
  c-ares                     1.33.1        hd74edd7_0              conda-forge
  c-blosc2                   2.12.0        ha57e6be_0              conda-forge
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Training/Inference via GUI

image
image
image
image

Resetting monitor window.
Polling: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131621.centroid.n=149/viz/validation.*.png
Start training centroid...
['sleap-train', '/var/folders/k4/_rfdxrp915b371f_6vf3fkjc0000gp/T/tmpdby_rtvs/240927_131622_training_job.json', '/Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/courtship_labels_1.4.1a3.slp', '--zmq', '--controller_port', '9000', '--publish_port', '9001', '--save_viz']
INFO:sleap.nn.training:Versions:
SLEAP: 1.4.1a3
TensorFlow: 2.9.2
Numpy: 1.22.4
Python: 3.9.20
OS: macOS-14.6.1-arm64-arm-64bit
INFO:sleap.nn.training:Training labels file: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/courtship_labels_1.4.1a3.slp
INFO:sleap.nn.training:Training profile: /var/folders/k4/_rfdxrp915b371f_6vf3fkjc0000gp/T/tmpdby_rtvs/240927_131622_training_job.json
INFO:sleap.nn.training:
INFO:sleap.nn.training:Arguments:
INFO:sleap.nn.training:{
    "training_job_path": "/var/folders/k4/_rfdxrp915b371f_6vf3fkjc0000gp/T/tmpdby_rtvs/240927_131622_training_job.json",
    "labels_path": "/Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/courtship_labels_1.4.1a3.slp",
    "video_paths": [
        ""
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    "val_labels": null,
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    "base_checkpoint": null,
    "tensorboard": false,
    "save_viz": true,
    "keep_viz": false,
    "zmq": true,
    "publish_port": 9001,
    "controller_port": 9000,
    "run_name": "",
    "prefix": "",
    "suffix": "",
    "cpu": false,
    "first_gpu": false,
    "last_gpu": false,
    "gpu": "auto"
}
INFO:sleap.nn.training:
INFO:sleap.nn.training:Training job:
INFO:sleap.nn.training:{
    "data": {
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            "min_learning_rate": 1e-08
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        "hard_keypoint_mining": {
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            "hard_to_easy_ratio": 2.0,
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            "loss_scale": 5.0
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        "early_stopping": {
            "stop_training_on_plateau": true,
            "plateau_min_delta": 1e-08,
            "plateau_patience": 20
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        "runs_folder": "/Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models",
        "tags": [
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        "save_visualizations": true,
        "keep_viz_images": false,
        "zip_outputs": false,
        "log_to_csv": true,
        "checkpointing": {
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        "tensorboard": {
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        "zmq": {
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            "controller_address": "tcp://127.0.0.1:9000",
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    "filename": "/var/folders/k4/_rfdxrp915b371f_6vf3fkjc0000gp/T/tmpdby_rtvs/240927_131622_training_job.json"
}
INFO:sleap.nn.training:
INFO:sleap.nn.training:Failed to query GPU memory from nvidia-smi. Defaulting to first GPU.
INFO:sleap.nn.training:Using GPU 0 for acceleration.
INFO:sleap.nn.training:Disabled GPU memory pre-allocation.
INFO:sleap.nn.training:System:
GPUs: 1/1 available
  Device: /physical_device:GPU:0
         Available: True
       Initialized: False
     Memory growth: True
INFO:sleap.nn.training:
INFO:sleap.nn.training:Initializing trainer...
INFO:sleap.nn.training:Loading training labels from: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/courtship_labels_1.4.1a3.slp
INFO:sleap.nn.training:Creating training and validation splits from validation fraction: 0.1
INFO:sleap.nn.training:  Splits: Training = 134 / Validation = 15.
INFO:sleap.nn.training:Setting up for training...
INFO:sleap.nn.training:Setting up pipeline builders...
INFO:sleap.nn.training:Setting up model...
INFO:sleap.nn.training:Building test pipeline...
Metal device set to: Apple M2

systemMemory: 8.00 GB
maxCacheSize: 2.67 GB

2024-09-27 13:16:28.557802: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:305] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.
2024-09-27 13:16:28.558035: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:271] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>)
2024-09-27 13:16:28.899898: W tensorflow/core/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz
INFO:sleap.nn.training:Loaded test example. [0.967s]
INFO:sleap.nn.training:  Input shape: (512, 512, 3)
INFO:sleap.nn.training:Created Keras model.
INFO:sleap.nn.training:  Backbone: UNet(stacks=1, filters=16, filters_rate=2.0, kernel_size=3, stem_kernel_size=7, convs_per_block=2, stem_blocks=0, down_blocks=4, middle_block=True, up_blocks=3, up_interpolate=True, block_contraction=False)
INFO:sleap.nn.training:  Max stride: 16
INFO:sleap.nn.training:  Parameters: 1,953,393
INFO:sleap.nn.training:  Heads: 
INFO:sleap.nn.training:    [0] = CentroidConfmapsHead(anchor_part=None, sigma=2.5, output_stride=2, loss_weight=1.0)
INFO:sleap.nn.training:  Outputs: 
INFO:sleap.nn.training:    [0] = KerasTensor(type_spec=TensorSpec(shape=(None, 256, 256, 1), dtype=tf.float32, name=None), name='CentroidConfmapsHead/BiasAdd:0', description="created by layer 'CentroidConfmapsHead'")
INFO:sleap.nn.training:Training from scratch
INFO:sleap.nn.training:Setting up data pipelines...
INFO:sleap.nn.training:Training set: n = 134
INFO:sleap.nn.training:Validation set: n = 15
INFO:sleap.nn.training:Setting up optimization...
INFO:sleap.nn.training:  Learning rate schedule: LearningRateScheduleConfig(reduce_on_plateau=True, reduction_factor=0.5, plateau_min_delta=1e-06, plateau_patience=5, plateau_cooldown=3, min_learning_rate=1e-08)
INFO:sleap.nn.training:  Early stopping: EarlyStoppingConfig(stop_training_on_plateau=True, plateau_min_delta=1e-08, plateau_patience=20)
INFO:sleap.nn.training:Setting up outputs...
INFO:sleap.nn.callbacks:Training controller subscribed to: tcp://127.0.0.1:9000 (topic: )
INFO:sleap.nn.training:  ZMQ controller subcribed to: tcp://127.0.0.1:9000
INFO:sleap.nn.callbacks:Progress reporter publishing on: tcp://127.0.0.1:9001 for: not_set
INFO:sleap.nn.training:  ZMQ progress reporter publish on: tcp://127.0.0.1:9001
INFO:sleap.nn.training:Created run path: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131621.centroid.n=149
INFO:sleap.nn.training:Setting up visualization...
2024-09-27 13:16:31.299210: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:16:31.327875: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:16:31.342017: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -34 } dim { size: -35 } dim { size: -36 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: -37 } dim { size: -38 } dim { size: 1 } } }
2024-09-27 13:16:31.907054: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:16:31.934686: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:16:31.947161: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -34 } dim { size: -35 } dim { size: -36 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: -37 } dim { size: -38 } dim { size: 1 } } }
INFO:sleap.nn.training:Finished trainer set up. [3.5s]
INFO:sleap.nn.training:Creating tf.data.Datasets for training data generation...
INFO:sleap.nn.training:Finished creating training datasets. [6.5s]
INFO:sleap.nn.training:Starting training loop...
Epoch 1/2
2024-09-27 13:16:39.109005: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:17:30.975676: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
200/200 - 56s - loss: 2.4318e-04 - val_loss: 1.8214e-04 - lr: 1.0000e-04 - 56s/epoch - 282ms/step
Epoch 2/2
Polling: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131621.centroid.n=149/viz/validation.*.png
200/200 - 49s - loss: 1.2795e-04 - val_loss: 1.3762e-04 - lr: 1.0000e-04 - 49s/epoch - 246ms/step
Polling: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131621.centroid.n=149/viz/validation.*.png
INFO:sleap.nn.training:Finished training loop. [1.8 min]
INFO:sleap.nn.training:Deleting visualization directory: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131621.centroid.n=149/viz
INFO:sleap.nn.training:Saving evaluation metrics to model folder...
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% ETA: -:--:-- ?2024-09-27 13:18:26.168673: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:18:26.287486: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -43 } dim { size: -44 } dim { size: -45 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -9 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: -46 } dim { size: -47 } dim { size: 1 } } }
2024-09-27 13:18:26.287731: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_UINT8 } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_UINT8 shape { dim { size: 4 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -9 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: -55 } dim { size: -56 } dim { size: 3 } } }
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺  99% ETA: 0:00:01 21.3 FPS2024-09-27 13:18:34.301029: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:18:34.419874: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -56 } dim { size: -57 } dim { size: -58 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -9 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: -59 } dim { size: -60 } dim { size: 1 } } }
2024-09-27 13:18:34.420126: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_UINT8 } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_UINT8 shape { dim { size: -18 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -9 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: -68 } dim { size: -69 } dim { size: 3 } } }
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% ETA: 0:00:00 13.3 FPS
INFO:sleap.nn.evals:Saved predictions: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131621.centroid.n=149/labels_pr.train.slp
INFO:sleap.nn.evals:Saved metrics: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131621.centroid.n=149/metrics.train.npz
INFO:sleap.nn.evals:OKS mAP: 1.000000
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% ETA: -:--:-- ?2024-09-27 13:18:36.827331: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:18:36.936273: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -43 } dim { size: -44 } dim { size: -45 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -9 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: -46 } dim { size: -47 } dim { size: 1 } } }
2024-09-27 13:18:36.936466: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_UINT8 } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_UINT8 shape { dim { size: 4 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -9 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: -55 } dim { size: -56 } dim { size: 3 } } }
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━  80% ETA: 0:00:01 36.5 FPS2024-09-27 13:18:38.533821: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:18:38.651741: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -56 } dim { size: -57 } dim { size: -58 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -9 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: -59 } dim { size: -60 } dim { size: 1 } } }
2024-09-27 13:18:38.652007: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_UINT8 } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_UINT8 shape { dim { size: -18 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -9 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -9 } dim { size: -68 } dim { size: -69 } dim { size: 3 } } }
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% ETA: 0:00:00 5.6 FPS
INFO:sleap.nn.evals:Saved predictions: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131621.centroid.n=149/labels_pr.val.slp
INFO:sleap.nn.evals:Saved metrics: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131621.centroid.n=149/metrics.val.npz
INFO:sleap.nn.evals:OKS mAP: 1.000000
INFO:sleap.nn.callbacks:Closing the reporter controller/context.
INFO:sleap.nn.callbacks:Closing the training controller socket/context.
Run Path: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131621.centroid.n=149
Finished training centroid.
Resetting monitor window.
Polling: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131840.centered_instance.n=149/viz/validation.*.png
Start training centered_instance...
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INFO:sleap.nn.training:Versions:
SLEAP: 1.4.1a3
TensorFlow: 2.9.2
Numpy: 1.22.4
Python: 3.9.20
OS: macOS-14.6.1-arm64-arm-64bit
INFO:sleap.nn.training:Training labels file: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/courtship_labels_1.4.1a3.slp
INFO:sleap.nn.training:Training profile: /var/folders/k4/_rfdxrp915b371f_6vf3fkjc0000gp/T/tmpq81bhqej/240927_131840_training_job.json
INFO:sleap.nn.training:
INFO:sleap.nn.training:Arguments:
INFO:sleap.nn.training:{
    "training_job_path": "/var/folders/k4/_rfdxrp915b371f_6vf3fkjc0000gp/T/tmpq81bhqej/240927_131840_training_job.json",
    "labels_path": "/Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/courtship_labels_1.4.1a3.slp",
    "video_paths": [
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    "val_labels": null,
    "test_labels": null,
    "base_checkpoint": null,
    "tensorboard": false,
    "save_viz": true,
    "keep_viz": false,
    "zmq": true,
    "publish_port": 9001,
    "controller_port": 9000,
    "run_name": "",
    "prefix": "",
    "suffix": "",
    "cpu": false,
    "first_gpu": false,
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    "gpu": "auto"
}
INFO:sleap.nn.training:
INFO:sleap.nn.training:Training job:
INFO:sleap.nn.training:{
    "data": {
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INFO:sleap.nn.training:
INFO:sleap.nn.training:Failed to query GPU memory from nvidia-smi. Defaulting to first GPU.
INFO:sleap.nn.training:Using GPU 0 for acceleration.
INFO:sleap.nn.training:Disabled GPU memory pre-allocation.
INFO:sleap.nn.training:System:
GPUs: 1/1 available
  Device: /physical_device:GPU:0
         Available: True
       Initialized: False
     Memory growth: True
INFO:sleap.nn.training:
INFO:sleap.nn.training:Initializing trainer...
INFO:sleap.nn.training:Loading training labels from: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/courtship_labels_1.4.1a3.slp
INFO:sleap.nn.training:Creating training and validation splits from validation fraction: 0.1
INFO:sleap.nn.training:  Splits: Training = 134 / Validation = 15.
INFO:sleap.nn.training:Setting up for training...
INFO:sleap.nn.training:Setting up pipeline builders...
INFO:sleap.nn.training:Setting up model...
INFO:sleap.nn.training:Building test pipeline...
Metal device set to: Apple M2

systemMemory: 8.00 GB
maxCacheSize: 2.67 GB

2024-09-27 13:18:46.339749: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:305] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.
2024-09-27 13:18:46.339933: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:271] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>)
2024-09-27 13:18:46.610915: W tensorflow/core/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz
2024-09-27 13:18:47.368048: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: 1 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 144 } dim { size: 144 } dim { size: 3 } } }
INFO:sleap.nn.training:Loaded test example. [1.199s]
INFO:sleap.nn.training:  Input shape: (144, 144, 3)
INFO:sleap.nn.training:Created Keras model.
INFO:sleap.nn.training:  Backbone: UNet(stacks=1, filters=24, filters_rate=2.0, kernel_size=3, stem_kernel_size=7, convs_per_block=2, stem_blocks=0, down_blocks=4, middle_block=True, up_blocks=2, up_interpolate=True, block_contraction=False)
INFO:sleap.nn.training:  Max stride: 16
INFO:sleap.nn.training:  Parameters: 4,311,877
INFO:sleap.nn.training:  Heads: 
INFO:sleap.nn.training:    [0] = CenteredInstanceConfmapsHead(part_names=['head', 'thorax', 'abdomen', 'wingL', 'wingR', 'forelegL4', 'forelegR4', 'midlegL4', 'midlegR4', 'hindlegL4', 'hindlegR4', 'eyeL', 'eyeR'], anchor_part=None, sigma=2.5, output_stride=4, loss_weight=1.0)
INFO:sleap.nn.training:  Outputs: 
INFO:sleap.nn.training:    [0] = KerasTensor(type_spec=TensorSpec(shape=(None, 36, 36, 13), dtype=tf.float32, name=None), name='CenteredInstanceConfmapsHead/BiasAdd:0', description="created by layer 'CenteredInstanceConfmapsHead'")
INFO:sleap.nn.training:Training from scratch
INFO:sleap.nn.training:Setting up data pipelines...
INFO:sleap.nn.training:Training set: n = 134
INFO:sleap.nn.training:Validation set: n = 15
INFO:sleap.nn.training:Setting up optimization...
INFO:sleap.nn.training:  Learning rate schedule: LearningRateScheduleConfig(reduce_on_plateau=True, reduction_factor=0.5, plateau_min_delta=1e-06, plateau_patience=5, plateau_cooldown=3, min_learning_rate=1e-08)
INFO:sleap.nn.training:  Early stopping: EarlyStoppingConfig(stop_training_on_plateau=True, plateau_min_delta=1e-08, plateau_patience=10)
INFO:sleap.nn.training:Setting up outputs...
INFO:sleap.nn.callbacks:Training controller subscribed to: tcp://127.0.0.1:9000 (topic: )
INFO:sleap.nn.training:  ZMQ controller subcribed to: tcp://127.0.0.1:9000
INFO:sleap.nn.callbacks:Progress reporter publishing on: tcp://127.0.0.1:9001 for: not_set
INFO:sleap.nn.training:  ZMQ progress reporter publish on: tcp://127.0.0.1:9001
INFO:sleap.nn.training:Created run path: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131840.centered_instance.n=149
INFO:sleap.nn.training:Setting up visualization...
2024-09-27 13:18:48.356588: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: 1 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 144 } dim { size: 144 } dim { size: 3 } } }
2024-09-27 13:18:48.948353: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: 1 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 144 } dim { size: 144 } dim { size: 3 } } }
INFO:sleap.nn.training:Finished trainer set up. [2.7s]
INFO:sleap.nn.training:Creating tf.data.Datasets for training data generation...
2024-09-27 13:18:54.282213: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: 1 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 144 } dim { size: 144 } dim { size: 3 } } }
2024-09-27 13:18:55.787276: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: 1 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 144 } dim { size: 144 } dim { size: 3 } } }
INFO:sleap.nn.training:Finished creating training datasets. [7.0s]
INFO:sleap.nn.training:Starting training loop...
2024-09-27 13:18:56.087534: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: 1 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 144 } dim { size: 144 } dim { size: 3 } } }
Epoch 1/2
2024-09-27 13:18:56.974594: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:19:12.534497: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: 1 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 144 } dim { size: 144 } dim { size: 3 } } }
2024-09-27 13:19:12.794824: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:19:14.100843: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:19:14.112985: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: 13 } dim { size: 36 } dim { size: 36 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: -5 } dim { size: -6 } dim { size: 1 } } }
200/200 - 19s - loss: 0.0109 - head: 0.0068 - thorax: 0.0058 - abdomen: 0.0111 - wingL: 0.0126 - wingR: 0.0131 - forelegL4: 0.0111 - forelegR4: 0.0110 - midlegL4: 0.0130 - midlegR4: 0.0131 - hindlegL4: 0.0132 - hindlegR4: 0.0130 - eyeL: 0.0088 - eyeR: 0.0089 - val_loss: 0.0089 - val_head: 0.0031 - val_thorax: 0.0033 - val_abdomen: 0.0085 - val_wingL: 0.0091 - val_wingR: 0.0102 - val_forelegL4: 0.0096 - val_forelegR4: 0.0088 - val_midlegL4: 0.0119 - val_midlegR4: 0.0124 - val_hindlegL4: 0.0129 - val_hindlegR4: 0.0119 - val_eyeL: 0.0070 - val_eyeR: 0.0072 - lr: 1.0000e-04 - 19s/epoch - 97ms/step
Polling: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131621.centroid.n=149/viz/validation.*.png
Polling: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131840.centered_instance.n=149/viz/validation.*.png
Epoch 2/2
2024-09-27 13:19:27.919520: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: 1 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 144 } dim { size: 144 } dim { size: 3 } } }
200/200 - 13s - loss: 0.0081 - head: 0.0019 - thorax: 0.0027 - abdomen: 0.0061 - wingL: 0.0069 - wingR: 0.0079 - forelegL4: 0.0096 - forelegR4: 0.0094 - midlegL4: 0.0118 - midlegR4: 0.0121 - hindlegL4: 0.0120 - hindlegR4: 0.0118 - eyeL: 0.0064 - eyeR: 0.0064 - val_loss: 0.0074 - val_head: 0.0012 - val_thorax: 0.0021 - val_abdomen: 0.0050 - val_wingL: 0.0053 - val_wingR: 0.0078 - val_forelegL4: 0.0093 - val_forelegR4: 0.0080 - val_midlegL4: 0.0112 - val_midlegR4: 0.0116 - val_hindlegL4: 0.0115 - val_hindlegR4: 0.0108 - val_eyeL: 0.0065 - val_eyeR: 0.0059 - lr: 1.0000e-04 - 13s/epoch - 65ms/step
Polling: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131621.centroid.n=149/viz/validation.*.png
Polling: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131840.centered_instance.n=149/viz/validation.*.png
INFO:sleap.nn.training:Finished training loop. [0.5 min]
INFO:sleap.nn.training:Deleting visualization directory: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131840.centered_instance.n=149/viz
INFO:sleap.nn.training:Saving evaluation metrics to model folder...
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% ETA: -:--:-- ?2024-09-27 13:19:29.915619: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:19:29.974161: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_UINT8 } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_UINT8 shape { dim { size: 4 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: -25 } dim { size: -26 } dim { size: 3 } } }
2024-09-27 13:19:29.978665: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -42 } dim { size: -43 } dim { size: -44 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -10 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -10 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -10 } dim { size: -46 } dim { size: -47 } dim { size: 1 } } }
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺  99% ETA: 0:00:01 28.8 FPS2024-09-27 13:19:35.906455: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:19:35.962298: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_UINT8 } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_UINT8 shape { dim { size: -13 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: -39 } dim { size: -40 } dim { size: 3 } } }
2024-09-27 13:19:35.966521: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -57 } dim { size: -58 } dim { size: -59 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -10 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -10 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -10 } dim { size: -61 } dim { size: -62 } dim { size: 1 } } }
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% ETA: 0:00:00 24.5 FPS
INFO:sleap.nn.evals:Saved predictions: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131840.centered_instance.n=149/labels_pr.train.slp
INFO:sleap.nn.evals:Saved metrics: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131840.centered_instance.n=149/metrics.train.npz
INFO:sleap.nn.evals:OKS mAP: 0.000655
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% ETA: -:--:-- ?2024-09-27 13:19:37.461789: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:19:37.519253: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_UINT8 } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_UINT8 shape { dim { size: 4 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: -25 } dim { size: -26 } dim { size: 3 } } }
2024-09-27 13:19:37.523521: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -42 } dim { size: -43 } dim { size: -44 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -10 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -10 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -10 } dim { size: -46 } dim { size: -47 } dim { size: 1 } } }
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━━━━  80% ETA: 0:00:01 68.1 FPS2024-09-27 13:19:38.299881: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:19:38.355471: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_UINT8 } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_UINT8 shape { dim { size: -13 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -2 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -2 } dim { size: -39 } dim { size: -40 } dim { size: 3 } } }
2024-09-27 13:19:38.359555: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -57 } dim { size: -58 } dim { size: -59 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -10 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -10 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -10 } dim { size: -61 } dim { size: -62 } dim { size: 1 } } }
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% ETA: 0:00:00 9.4 FPS
INFO:sleap.nn.evals:Saved predictions: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131840.centered_instance.n=149/labels_pr.val.slp
INFO:sleap.nn.evals:Saved metrics: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131840.centered_instance.n=149/metrics.val.npz
INFO:sleap.nn.evals:OKS mAP: 0.000686
INFO:sleap.nn.callbacks:Closing the reporter controller/context.
INFO:sleap.nn.callbacks:Closing the training controller socket/context.
Run Path: /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131840.centered_instance.n=149
Finished training centered_instance.
Command line call:
sleap-track /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/courtship_labels_1.4.1a3.slp --video.index 0 --frames 55,88,164,205,214,297,381,419,474,539,558,578,628,711,764,837,902,990 -m /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131621.centroid.n=149 -m /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131840.centered_instance.n=149 --controller_port 9000 --publish_port 9001 -o /Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/predictions/courtship_labels_1.4.1a3.slp.240927_131939.predictions.slp --verbosity json --no-empty-frames

Started inference at: 2024-09-27 13:19:44.409006
Args:
{
│   'data_path': '/Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/courtship_labels_1.4.1a3.slp',
│   'models': [
│   │   '/Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131621.centroid.n=149',
│   │   '/Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131840.centered_instance.n=149'
│   ],
│   'frames': '55,88,164,205,214,297,381,419,474,539,558,578,628,711,764,837,902,990',
│   'only_labeled_frames': False,
│   'only_suggested_frames': False,
│   'output': '/Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/predictions/courtship_labels_1.4.1a3.slp.240927_131939.predictions.slp',
│   'no_empty_frames': True,
2024-09-27 13:19:45.070889: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:305] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.
2024-09-27 13:19:45.071005: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:271] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>)
│   'verbosity': 'json',
│   'video.dataset': None,
│   'video.input_format': 'channels_last',
│   'video.index': '0',
│   'cpu': False,
│   'first_gpu': False,
│   'last_gpu': False,
│   'gpu': 'auto',
│   'max_edge_length_ratio': 0.25,
│   'dist_penalty_weight': 1.0,
│   'batch_size': 4,
│   'open_in_gui': False,
│   'peak_threshold': 0.2,
│   'max_instances': None,
│   'tracking.tracker': None,
│   'tracking.max_tracking': None,
│   'tracking.max_tracks': None,
│   'tracking.target_instance_count': None,
2024-09-27 13:19:45.984013: W tensorflow/core/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz
│   'tracking.pre_cull_to_target': None,
│   'tracking.pre_cull_iou_threshold': None,
│   'tracking.post_connect_single_breaks': None,
│   'tracking.clean_instance_count': None,
│   'tracking.clean_iou_threshold': None,
│   'tracking.similarity': None,
│   'tracking.match': None,
│   'tracking.robust': None,
│   'tracking.track_window': None,
│   'tracking.min_new_track_points': None,
│   'tracking.min_match_points': None,
│   'tracking.img_scale': None,
│   'tracking.of_window_size': None,
│   'tracking.of_max_levels': None,
│   'tracking.save_shifted_instances': None,
│   'tracking.kf_node_indices': None,
│   'tracking.kf_init_frame_count': None,
│   'tracking.oks_errors': None,
│   'tracking.oks_score_weighting': None,
│   'tracking.oks_normalization': None
}

INFO:sleap.nn.inference:Failed to query GPU memory from nvidia-smi. Defaulting to first GPU.
Metal device set to: Apple M2
2024-09-27 13:19:48.171053: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:19:48.228321: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -45 } dim { size: -46 } dim { size: -47 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -15 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -15 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -15 } dim { size: -48 } dim { size: -49 } dim { size: 1 } } }
2024-09-27 13:19:48.228528: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_UINT8 } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_UINT8 shape { dim { size: 4 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -15 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -15 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -15 } dim { size: -56 } dim { size: -57 } dim { size: 3 } } }
2024-09-27 13:19:48.230835: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -91 } dim { size: -92 } dim { size: -93 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -20 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -20 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -20 } dim { size: -95 } dim { size: -96 } dim { size: 1 } } }
Versions:
SLEAP: 1.4.1a3
TensorFlow: 2.9.2
Numpy: 1.22.4
Python: 3.9.20
OS: macOS-14.6.1-arm64-arm-64bit

System:
GPUs: 1/1 available
  Device: /physical_device:GPU:0
         Available: True
       Initialized: False
     Memory growth: True

2024-09-27 13:19:49.795057: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:113] Plugin optimizer for device_type GPU is enabled.
2024-09-27 13:19:49.864043: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -54 } dim { size: -55 } dim { size: -56 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -15 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -15 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -15 } dim { size: -57 } dim { size: -58 } dim { size: 1 } } }
2024-09-27 13:19:49.864349: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_UINT8 } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_UINT8 shape { dim { size: -22 } dim { size: 1024 } dim { size: 1024 } dim { size: 3 } } } inputs { dtype: DT_FLOAT shape { dim { size: -15 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -15 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -15 } dim { size: -65 } dim { size: -66 } dim { size: 3 } } }
2024-09-27 13:19:49.866931: W tensorflow/core/grappler/costs/op_level_cost_estimator.cc:690] Error in PredictCost() for the op: op: "CropAndResize" attr { key: "T" value { type: DT_FLOAT } } attr { key: "extrapolation_value" value { f: 0 } } attr { key: "method" value { s: "bilinear" } } inputs { dtype: DT_FLOAT shape { dim { size: -100 } dim { size: -101 } dim { size: -102 } dim { size: 1 } } } inputs { dtype: DT_FLOAT shape { dim { size: -20 } dim { size: 4 } } } inputs { dtype: DT_INT32 shape { dim { size: -20 } } } inputs { dtype: DT_INT32 shape { dim { size: 2 } } } device { type: "CPU" model: "0" num_cores: 8 environment { key: "cpu_instruction_set" value: "ARM NEON" } environment { key: "eigen" value: "3.4.90" } l1_cache_size: 16384 l2_cache_size: 524288 l3_cache_size: 524288 memory_size: 268435456 } outputs { dtype: DT_FLOAT shape { dim { size: -20 } dim { size: -104 } dim { size: -105 } dim { size: 1 } } }
Finished inference at: 2024-09-27 13:19:50.568276
Total runtime: 6.159277677536011 secs
Predicted frames: 18/18
Provenance:
{
│   'model_paths': [
│   │   '/Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131621.centroid.n=149/training_config.json',
│   │   '/Users/liezl/Projects/sleap-datasets/drosophila-melanogaster-courtship/models/240927_131840.centered_instance.n=149/training_config.json'
│   ],
Process return code: 0
skipped 98 redundant instances
Training Dialog

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sleap-label

image

(sleap_1.4) liezl:~$sleap-label
Saving config: /Users/liezl/.sleap/1.4.1a3/preferences.yaml
Restoring GUI state...

Software versions:
SLEAP: 1.4.1a3
TensorFlow: 2.9.2
Numpy: 1.22.4
Python: 3.9.20
OS: macOS-14.6.1-arm64-arm-64bit

Happy SLEAPing! :)
qt.qpa.fonts: Populating font family aliases took 54 ms. Replace uses of missing font family ".AppleSystemUIFont" with one that exists to avoid this cost. 
Restoring GUI state...
Installation
pip freeze 
(sleap_1.4) liezl:~$pip freeze  
absl-py==2.1.0
albumentations @ file:///home/conda/feedstock_root/build_artifacts/albumentations_1686576355052/work
astunparse==1.6.3
attrs @ file:///home/conda/feedstock_root/build_artifacts/attrs_1722977137225/work
cached-property @ file:///home/conda/feedstock_root/build_artifacts/cached_property_1615209429212/work
cachetools==5.5.0
cattrs @ file:///home/conda/feedstock_root/build_artifacts/cattrs_1604136207372/work
certifi @ file:///home/conda/feedstock_root/build_artifacts/certifi_1725278078093/work/certifi
charset-normalizer==3.3.2
contourpy @ file:///Users/runner/miniforge3/conda-bld/contourpy_1712429965428/work
cycler @ file:///home/conda/feedstock_root/build_artifacts/cycler_1696677705766/work
efficientnet==1.0.0
flatbuffers==1.12
fonttools @ file:///Users/runner/miniforge3/conda-bld/fonttools_1727206370939/work
gast==0.4.0
google-auth==2.35.0
google-auth-oauthlib==0.4.6
google-pasta==0.2.0
grpcio==1.66.1
h5py @ file:///Users/runner/miniforge3/conda-bld/h5py_1717665636416/work
hdmf @ file:///Users/runner/miniforge3/conda-bld/hdmf_1725567271720/work
idna==3.10
image-classifiers==1.0.0
imagecodecs @ file:///Users/runner/miniforge3/conda-bld/imagecodecs_1726939426532/work
imageio @ file:///home/conda/feedstock_root/build_artifacts/imageio_1724069053555/work
imageio-ffmpeg @ file:///home/conda/feedstock_root/build_artifacts/imageio-ffmpeg_1717461632069/work
imgstore==0.2.9
importlib_metadata @ file:///home/conda/feedstock_root/build_artifacts/importlib-metadata_1726082825846/work
importlib_resources @ file:///home/conda/feedstock_root/build_artifacts/importlib_resources_1725921340658/work
joblib @ file:///home/conda/feedstock_root/build_artifacts/joblib_1714665484399/work
jsmin @ file:///home/conda/feedstock_root/build_artifacts/jsmin_1642532731678/work
jsonpickle==1.2
jsonschema @ file:///home/conda/feedstock_root/build_artifacts/jsonschema_1720529478715/work
jsonschema-specifications @ file:///tmp/tmpkv1z7p57/src
keras @ file:///home/conda/feedstock_root/build_artifacts/keras_1652925255303/work/keras-2.9.0-py2.py3-none-any.whl
Keras-Applications==1.0.8
Keras-Preprocessing==1.1.2
kiwisolver @ file:///Users/runner/miniforge3/conda-bld/kiwisolver_1725459226886/work
lazy_loader @ file:///home/conda/feedstock_root/build_artifacts/lazy-loader_1723774329602/work
libclang==18.1.1
Markdown==3.7
markdown-it-py @ file:///home/conda/feedstock_root/build_artifacts/markdown-it-py_1686175045316/work
MarkupSafe==2.1.5
matplotlib @ file:///Users/runner/miniforge3/conda-bld/matplotlib-suite_1715976202591/work
mdurl @ file:///home/conda/feedstock_root/build_artifacts/mdurl_1704317613764/work
munkres==1.1.4
ndx-pose @ file:///home/conda/feedstock_root/build_artifacts/ndx-pose_1727393281100/work
networkx @ file:///home/conda/feedstock_root/build_artifacts/networkx_1698504735452/work
nixio==1.5.3
numpy @ file:///Users/runner/miniforge3/conda-bld/numpy_1653325964689/work
oauthlib==3.2.2
opencv-python==4.10.0
opencv-python-headless==4.10.0
opt_einsum==3.4.0
packaging @ file:///home/conda/feedstock_root/build_artifacts/packaging_1718189413536/work
pandas @ file:///Users/runner/miniforge3/conda-bld/pandas_1726878429351/work
patsy @ file:///home/conda/feedstock_root/build_artifacts/patsy_1704469236901/work
pillow @ file:///Users/runner/miniforge3/conda-bld/pillow_1726075095677/work
pkgutil_resolve_name @ file:///home/conda/feedstock_root/build_artifacts/pkgutil-resolve-name_1694617248815/work
protobuf==3.19.6
psutil @ file:///Users/runner/miniforge3/conda-bld/psutil_1725737869566/work
pyasn1==0.6.1
pyasn1_modules==0.4.1
Pygments @ file:///home/conda/feedstock_root/build_artifacts/pygments_1714846767233/work
pykalman @ file:///home/conda/feedstock_root/build_artifacts/pykalman_1711547707628/work
pynwb @ file:///Users/runner/miniforge3/conda-bld/pynwb_1725927435661/work
pyparsing @ file:///home/conda/feedstock_root/build_artifacts/pyparsing_1724616129934/work
PySide2==5.15.8
python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1709299778482/work
python-rapidjson @ file:///Users/runner/miniforge3/conda-bld/python-rapidjson_1722901830846/work
pytz @ file:///home/conda/feedstock_root/build_artifacts/pytz_1706886791323/work
PyWavelets==1.6.0
PyYAML @ file:///Users/runner/miniforge3/conda-bld/pyyaml_1725456248054/work
pyzmq @ file:///Users/runner/miniforge3/conda-bld/pyzmq_1725449041363/work
qimage2ndarray==1.10.0
QtPy @ file:///home/conda/feedstock_root/build_artifacts/qtpy_1698112029416/work
qudida @ file:///home/conda/feedstock_root/build_artifacts/qudida_1651101164121/work
referencing @ file:///home/conda/feedstock_root/build_artifacts/referencing_1714619483868/work
requests==2.32.3
requests-oauthlib==2.0.0
rich @ file:///home/conda/feedstock_root/build_artifacts/rich_1726066019428/work/dist
rpds-py @ file:///Users/runner/miniforge3/conda-bld/rpds-py_1725327067672/work
rsa==4.9
ruamel.yaml @ file:///Users/runner/miniforge3/conda-bld/ruamel.yaml_1707298177583/work
ruamel.yaml.clib @ file:///Users/runner/miniforge3/conda-bld/ruamel.yaml.clib_1707314608714/work
scikit-image @ file:///Users/runner/miniforge3/conda-bld/scikit-image_1719499452114/work/dist/scikit_image-0.24.0-cp39-cp39-macosx_11_0_arm64.whl#sha256=99a9d204a057340ff924741a9aa0c4fdd1ef9e918063988d46ba4645bcedbc64
scikit-learn @ file:///Users/runner/miniforge3/conda-bld/scikit-learn_1632611447519/work
scikit-video==1.1.11
scipy==1.9.0
seaborn @ file:///home/conda/feedstock_root/build_artifacts/seaborn-split_1714494649443/work
segmentation-models==1.0.1
shiboken2==5.15.8
six==1.15.0
sleap==1.4.1a3
statsmodels @ file:///Users/runner/miniforge3/conda-bld/statsmodels_1726899020978/work
tensorboard==2.9.1
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.1
tensorflow-estimator==2.9.0
tensorflow-hub==0.12.0
tensorflow-macos==2.9.2
tensorflow-metal==0.5.0
termcolor==2.4.0
threadpoolctl @ file:///home/conda/feedstock_root/build_artifacts/threadpoolctl_1714400101435/work
tifffile @ file:///home/conda/feedstock_root/build_artifacts/tifffile_1718963615451/work
typing_extensions @ file:///home/conda/feedstock_root/build_artifacts/typing_extensions_1717802530399/work
tzdata @ file:///home/conda/feedstock_root/build_artifacts/python-tzdata_1727140567071/work
tzlocal==5.2
unicodedata2 @ file:///Users/runner/miniforge3/conda-bld/unicodedata2_1695848020028/work
urllib3==2.2.3
Werkzeug==3.0.4
wrapt==1.16.0
zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1726248574750/work
mamba list 
(sleap_1.4) liezl:~$micromamba list
List of packages in environment: "/Users/liezl/micromamba/envs/sleap_1.4.1a3"

  Name                                  Version       Build                    Channel        
────────────────────────────────────────────────────────────────────────────────────────────────
  albumentations                        1.3.1         pyhd8ed1ab_0             conda-forge    
  aom                                   3.9.1         h7bae524_0               conda-forge    
  attrs                                 24.2.0        pyh71513ae_0             conda-forge    
  blosc                                 1.21.6        h5499902_0               conda-forge    
  brotli                                1.1.0         hd74edd7_2               conda-forge    
  brotli-bin                            1.1.0         hd74edd7_2               conda-forge    
  brunsli                               0.1           h9f76cd9_0               conda-forge    
  bzip2                                 1.0.8         h99b78c6_7               conda-forge    
  c-ares                                1.33.1        hd74edd7_0               conda-forge    
  c-blosc2                              2.15.1        h5063078_0               conda-forge    
  ca-certificates                       2024.8.30     hf0a4a13_0               conda-forge    
  cached-property                       1.5.2         hd8ed1ab_1               conda-forge    
  cached_property                       1.5.2         pyha770c72_1             conda-forge    
  cairo                                 1.18.0        hb4a6bf7_3               conda-forge    
  cattrs                                1.1.1         pyhd8ed1ab_0             conda-forge    
  certifi                               2024.8.30     pyhd8ed1ab_0             conda-forge    
  charls                                2.4.2         h13dd4ca_0               conda-forge    
  contourpy                             1.2.1         py39h48c5dd5_0           conda-forge    
  cycler                                0.12.1        pyhd8ed1ab_0             conda-forge    
  dav1d                                 1.2.1         hb547adb_0               conda-forge    
  expat                                 2.6.3         hf9b8971_0               conda-forge    
  ffmpeg                                6.1.2         gpl_he9820c9_105         conda-forge    
  font-ttf-dejavu-sans-mono             2.37          hab24e00_0               conda-forge    
  font-ttf-inconsolata                  3.000         h77eed37_0               conda-forge    
  font-ttf-source-code-pro              2.038         h77eed37_0               conda-forge    
  font-ttf-ubuntu                       0.83          h77eed37_2               conda-forge    
  fontconfig                            2.14.2        h82840c6_0               conda-forge    
  fonts-conda-ecosystem                 1             0                        conda-forge    
  fonts-conda-forge                     1             0                        conda-forge    
  fonttools                             4.54.1        py39h06df861_0           conda-forge    
  freetype                              2.12.1        hadb7bae_2               conda-forge    
  fribidi                               1.0.10        h27ca646_0               conda-forge    
  giflib                                5.2.2         h93a5062_0               conda-forge    
  glib                                  2.82.1        h4821c08_0               conda-forge    
  glib-tools                            2.82.1        he5bafa0_0               conda-forge    
  gmp                                   6.3.0         h7bae524_2               conda-forge    
  graphite2                             1.3.13        hebf3989_1003            conda-forge    
  gst-plugins-base                      1.24.7        hb49d354_0               conda-forge    
  gstreamer                             1.24.7        hc3f5269_0               conda-forge    
  h5py                                  3.11.0        nompi_py39h534c8c8_102   conda-forge    
  harfbuzz                              9.0.0         h997cde5_1               conda-forge    
  hdf5                                  1.14.3        nompi_hec07895_105       conda-forge    
  hdmf                                  3.14.4        pyhb401068_0             conda-forge    
  icu                                   75.1          hfee45f7_0               conda-forge    
  imagecodecs                           2024.6.1      py39h97ab222_4           conda-forge    
  imageio                               2.35.1        pyh12aca89_0             conda-forge    
  imageio-ffmpeg                        0.5.1         pyhd8ed1ab_0             conda-forge    
  imath                                 3.1.12        h025cafa_0               conda-forge    
  importlib-metadata                    8.5.0         pyha770c72_0             conda-forge    
  importlib-resources                   6.4.5         pyhd8ed1ab_0             conda-forge    
  importlib_resources                   6.4.5         pyhd8ed1ab_0             conda-forge    
  jasper                                4.2.4         h6c4e4ef_0               conda-forge    
  joblib                                1.4.2         pyhd8ed1ab_0             conda-forge    
  jsmin                                 3.0.1         pyhd8ed1ab_0             conda-forge    
  jsonpickle                            1.2           py_0                     conda-forge    
  jsonschema                            4.23.0        pyhd8ed1ab_0             conda-forge    
  jsonschema-specifications             2023.12.1     pyhd8ed1ab_0             conda-forge    
  jxrlib                                1.1           h93a5062_3               conda-forge    
  keras                                 2.9.0         pyhd8ed1ab_0             conda-forge    
  kiwisolver                            1.4.7         py39h157d57c_0           conda-forge    
  krb5                                  1.21.3        h237132a_0               conda-forge    
  lame                                  3.100         h1a8c8d9_1003            conda-forge    
  lazy-loader                           0.4           pyhd8ed1ab_1             conda-forge    
  lazy_loader                           0.4           pyhd8ed1ab_1             conda-forge    
  lcms2                                 2.16          ha0e7c42_0               conda-forge    
  lerc                                  4.0.0         h9a09cb3_0               conda-forge    
  libabseil                             20240116.2    cxx17_h00cdb27_1         conda-forge    
  libaec                                1.1.3         hebf3989_0               conda-forge    
  libasprintf                           0.22.5        h8414b35_3               conda-forge    
  libass                                0.17.3        hf20b609_0               conda-forge    
  libavif16                             1.1.1         ha4d98b1_1               conda-forge    
  libblas                               3.9.0         20_osxarm64_openblas     conda-forge    
  libbrotlicommon                       1.1.0         hd74edd7_2               conda-forge    
  libbrotlidec                          1.1.0         hd74edd7_2               conda-forge    
  libbrotlienc                          1.1.0         hd74edd7_2               conda-forge    
  libcblas                              3.9.0         20_osxarm64_openblas     conda-forge    
  libclang-cpp15                        15.0.7        default_he012953_5       conda-forge    
  libclang13                            19.1.0        default_h17c4df3_0       conda-forge    
  libcurl                               8.10.1        h13a7ad3_0               conda-forge    
  libcxx                                19.1.0        ha82da77_0               conda-forge    
  libdeflate                            1.21          h99b78c6_0               conda-forge    
  libedit                               3.1.20191231  hc8eb9b7_2               conda-forge    
  libev                                 4.33          h93a5062_2               conda-forge    
  libexpat                              2.6.3         hf9b8971_0               conda-forge    
  libffi                                3.4.2         h3422bc3_5               conda-forge    
  libgettextpo                          0.22.5        h8414b35_3               conda-forge    
  libgfortran                           5.0.0         13_2_0_hd922786_3        conda-forge    
  libgfortran5                          13.2.0        hf226fd6_3               conda-forge    
  libglib                               2.82.1        h4821c08_0               conda-forge    
  libhwloc                              2.11.1        default_h7685b71_1000    conda-forge    
  libhwy                                1.1.0         h2ffa867_0               conda-forge    
  libiconv                              1.17          h0d3ecfb_2               conda-forge    
  libintl                               0.22.5        h8414b35_3               conda-forge    
  libintl-devel                         0.22.5        h8414b35_3               conda-forge    
  libjpeg-turbo                         3.0.0         hb547adb_1               conda-forge    
  libjxl                                0.11.0        ha38c0f0_0               conda-forge    
  liblapack                             3.9.0         20_osxarm64_openblas     conda-forge    
  liblapacke                            3.9.0         20_osxarm64_openblas     conda-forge    
  libllvm15                             15.0.7        h2621b3d_4               conda-forge    
  libllvm19                             19.1.0        hbfa8675_0               conda-forge    
  libnghttp2                            1.58.0        ha4dd798_1               conda-forge    
  libogg                                1.3.5         h99b78c6_0               conda-forge    
  libopenblas                           0.3.25        openmp_h6c19121_0        conda-forge    
  libopencv                             4.10.0        headless_py39hc9efabb_4  conda-forge    
  libopenvino                           2024.4.0      h49f535f_0               conda-forge    
  libopenvino-arm-cpu-plugin            2024.4.0      h49f535f_0               conda-forge    
  libopenvino-auto-batch-plugin         2024.4.0      h8a2fcec_0               conda-forge    
  libopenvino-auto-plugin               2024.4.0      h8a2fcec_0               conda-forge    
  libopenvino-hetero-plugin             2024.4.0      h868cbb4_0               conda-forge    
  libopenvino-ir-frontend               2024.4.0      h868cbb4_0               conda-forge    
  libopenvino-onnx-frontend             2024.4.0      hf4ed89a_0               conda-forge    
  libopenvino-paddle-frontend           2024.4.0      hf4ed89a_0               conda-forge    
  libopenvino-pytorch-frontend          2024.4.0      hf9b8971_0               conda-forge    
  libopenvino-tensorflow-frontend       2024.4.0      h94307f2_0               conda-forge    
  libopenvino-tensorflow-lite-frontend  2024.4.0      hf9b8971_0               conda-forge    
  libopus                               1.3.1         h27ca646_1               conda-forge    
  libpng                                1.6.44        hc14010f_0               conda-forge    
  libpq                                 16.4          h671472c_1               conda-forge    
  libprotobuf                           4.25.3        hc39d83c_1               conda-forge    
  libsodium                             1.0.20        h99b78c6_0               conda-forge    
  libsqlite                             3.46.1        hc14010f_0               conda-forge    
  libssh2                               1.11.0        h7a5bd25_0               conda-forge    
  libtiff                               4.7.0         h9c1d414_0               conda-forge    
  libvorbis                             1.3.7         h9f76cd9_0               conda-forge    
  libvpx                                1.14.1        h7bae524_0               conda-forge    
  libwebp-base                          1.4.0         h93a5062_0               conda-forge    
  libxcb                                1.17.0        hdb1d25a_0               conda-forge    
  libxml2                               2.12.7        h01dff8b_4               conda-forge    
  libxslt                               1.1.39        h223e5b9_0               conda-forge    
  libzlib                               1.3.1         hfb2fe0b_1               conda-forge    
  libzopfli                             1.0.3         h9f76cd9_0               conda-forge    
  llvm-openmp                           18.1.8        hde57baf_1               conda-forge    
  lz4-c                                 1.9.4         hb7217d7_0               conda-forge    
  markdown-it-py                        3.0.0         pyhd8ed1ab_0             conda-forge    
  matplotlib-base                       3.8.4         py39h15359f4_2           conda-forge    
  mdurl                                 0.1.2         pyhd8ed1ab_0             conda-forge    
  munkres                               1.1.4         pyh9f0ad1d_0             conda-forge    
  mysql-common                          9.0.1         h5246617_1               conda-forge    
  mysql-libs                            9.0.1         hb96318c_1               conda-forge    
  ncurses                               6.5           h7bae524_1               conda-forge    
  ndx-pose                              0.2.1         pyhd8ed1ab_0             conda-forge    
  networkx                              3.2.1         pyhd8ed1ab_0             conda-forge    
  nspr                                  4.35          hb7217d7_0               conda-forge    
  nss                                   3.105         hd1ce637_0               conda-forge    
  numpy                                 1.22.4        py39h7df2422_0           conda-forge    
  opencv                                4.10.0        headless_py39h38a9fee_4  conda-forge    
  openexr                               3.2.2         hab01212_2               conda-forge    
  openh264                              2.4.1         hebf3989_0               conda-forge    
  openjpeg                              2.5.2         h9f1df11_0               conda-forge    
  openssl                               3.3.2         h8359307_0               conda-forge    
  packaging                             24.1          pyhd8ed1ab_0             conda-forge    
  pandas                                2.2.3         py39hc5ad87a_1           conda-forge    
  patsy                                 0.5.6         pyhd8ed1ab_0             conda-forge    
  pcre2                                 10.44         h297a79d_2               conda-forge    
  pillow                                10.4.0        py39hab9ce06_1           conda-forge    
  pip                                   24.2          pyh8b19718_1             conda-forge    
  pixman                                0.43.4        hebf3989_0               conda-forge    
  pkgutil-resolve-name                  1.3.10        pyhd8ed1ab_1             conda-forge    
  psutil                                6.0.0         py39h06df861_1           conda-forge    
  pthread-stubs                         0.4           hd74edd7_1002            conda-forge    
  pugixml                               1.14          h13dd4ca_0               conda-forge    
  py-opencv                             4.10.0        headless_py39hef12fc8_4  conda-forge    
  pygments                              2.18.0        pyhd8ed1ab_0             conda-forge    
  pykalman                              0.9.7         pyhd8ed1ab_0             conda-forge    
  pynwb                                 2.8.2         pyhb401068_0             conda-forge    
  pyparsing                             3.1.4         pyhd8ed1ab_0             conda-forge    
  pyside2                               5.15.8        py39hdd1c371_4           conda-forge    
  python                                3.9.20        h9e33284_0_cpython       conda-forge    
  python-dateutil                       2.9.0         pyhd8ed1ab_0             conda-forge    
  python-rapidjson                      1.20          py39hbf7db11_0           conda-forge    
  python-tzdata                         2024.2        pyhd8ed1ab_0             conda-forge    
  python_abi                            3.9           5_cp39                   conda-forge    
  pytz                                  2024.1        pyhd8ed1ab_0             conda-forge    
  pywavelets                            1.6.0         py39h161d348_0           conda-forge    
  pyyaml                                6.0.2         py39h06df861_1           conda-forge    
  pyzmq                                 26.2.0        py39h6f9cb01_2           conda-forge    
  qt-main                               5.15.8        h1c95b31_26              conda-forge    
  qtpy                                  2.4.1         pyhd8ed1ab_0             conda-forge    
  qudida                                0.0.4         pyhd8ed1ab_0             conda-forge    
  rav1e                                 0.6.6         h69fbcac_2               conda-forge    
  readline                              8.2           h92ec313_1               conda-forge    
  referencing                           0.35.1        pyhd8ed1ab_0             conda-forge    
  rich                                  13.8.1        pyhd8ed1ab_0             conda-forge    
  rpds-py                               0.20.0        py39h9c3e640_1           conda-forge    
  ruamel.yaml                           0.18.6        py39h17cfd9d_0           conda-forge    
  ruamel.yaml.clib                      0.2.8         py39h17cfd9d_0           conda-forge    
  scikit-image                          0.24.0        py39h998126f_1           conda-forge    
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@roomrys
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roomrys commented Sep 27, 2024 •
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Loading

Linux (manual test)

Training/Inference via GUI

image

image

image

Resetting monitor window.
Polling: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100/viz/validation.*.png
Start training centroid...
['sleap-train', '/tmp/tmp24yhxdmr/241002_154718_training_job.json', '/home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/courtship_labels.slp', '--zmq', '--controller_port', '9000', '--publish_port', '9001', '--save_viz']
INFO:sleap.nn.training:Versions:
SLEAP: 1.4.1a3
TensorFlow: 2.7.0
Numpy: 1.19.5
Python: 3.7.12
OS: Linux-5.15.0-78-generic-x86_64-with-debian-bookworm-sid
INFO:sleap.nn.training:Training labels file: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/courtship_labels.slp
INFO:sleap.nn.training:Training profile: /tmp/tmp24yhxdmr/241002_154718_training_job.json
INFO:sleap.nn.training:
INFO:sleap.nn.training:Arguments:
INFO:sleap.nn.training:{
    "training_job_path": "/tmp/tmp24yhxdmr/241002_154718_training_job.json",
    "labels_path": "/home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/courtship_labels.slp",
    "video_paths": [
        ""
    ],
    "val_labels": null,
    "test_labels": null,
    "base_checkpoint": null,
    "tensorboard": false,
    "save_viz": true,
    "keep_viz": false,
    "zmq": true,
    "publish_port": 9001,
    "controller_port": 9000,
    "run_name": "",
    "prefix": "",
    "suffix": "",
    "cpu": false,
    "first_gpu": false,
    "last_gpu": false,
    "gpu": "auto"
}
INFO:sleap.nn.training:
INFO:sleap.nn.training:Training job:
INFO:sleap.nn.training:{
    "data": {
        "labels": {
            "training_labels": "/home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/courtship_labels.slp",
            "validation_labels": null,
            "validation_fraction": 0.1,
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            "split_by_inds": false,
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            "validation_inds": [
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            "test_inds": null,
            "search_path_hints": [
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            ],
            "skeletons": []
        },
        "preprocessing": {
            "ensure_rgb": false,
            "ensure_grayscale": false,
            "imagenet_mode": null,
            "input_scaling": 0.5,
            "pad_to_stride": 16,
            "resize_and_pad_to_target": true,
            "target_height": 1024,
            "target_width": 1024
        },
        "instance_cropping": {
            "center_on_part": "thorax",
            "crop_size": null,
            "crop_size_detection_padding": 16
        }
    },
    "model": {
        "backbone": {
            "leap": null,
            "unet": {
                "stem_stride": null,
                "max_stride": 16,
                "output_stride": 2,
                "filters": 16,
                "filters_rate": 2.0,
                "middle_block": true,
                "up_interpolate": true,
                "stacks": 1
            },
            "hourglass": null,
            "resnet": null,
            "pretrained_encoder": null
        },
        "heads": {
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            "centroid": {
                "anchor_part": "thorax",
                "sigma": 2.5,
                "output_stride": 2,
                "loss_weight": 1.0,
                "offset_refinement": false
            },
            "centered_instance": null,
            "multi_instance": null,
            "multi_class_bottomup": null,
            "multi_class_topdown": null
        },
        "base_checkpoint": null
    },
    "optimization": {
        "preload_data": true,
        "augmentation_config": {
            "rotate": true,
            "rotation_min_angle": -180.0,
            "rotation_max_angle": 180.0,
            "translate": false,
            "translate_min": -5,
            "translate_max": 5,
            "scale": false,
            "scale_min": 0.9,
            "scale_max": 1.1,
            "uniform_noise": false,
            "uniform_noise_min_val": 0.0,
            "uniform_noise_max_val": 10.0,
            "gaussian_noise": false,
            "gaussian_noise_mean": 5.0,
            "gaussian_noise_stddev": 1.0,
            "contrast": false,
            "contrast_min_gamma": 0.5,
            "contrast_max_gamma": 2.0,
            "brightness": false,
            "brightness_min_val": 0.0,
            "brightness_max_val": 10.0,
            "random_crop": false,
            "random_crop_height": 256,
            "random_crop_width": 256,
            "random_flip": false,
            "flip_horizontal": false
        },
        "online_shuffling": true,
        "shuffle_buffer_size": 128,
        "prefetch": true,
        "batch_size": 4,
        "batches_per_epoch": 200,
        "min_batches_per_epoch": 200,
        "val_batches_per_epoch": 10,
        "min_val_batches_per_epoch": 10,
        "epochs": 2,
        "optimizer": "adam",
        "initial_learning_rate": 0.0001,
        "learning_rate_schedule": {
            "reduce_on_plateau": true,
            "reduction_factor": 0.5,
            "plateau_min_delta": 1e-06,
            "plateau_patience": 5,
            "plateau_cooldown": 3,
            "min_learning_rate": 1e-08
        },
        "hard_keypoint_mining": {
            "online_mining": false,
            "hard_to_easy_ratio": 2.0,
            "min_hard_keypoints": 2,
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        },
        "early_stopping": {
            "stop_training_on_plateau": true,
            "plateau_min_delta": 1e-08,
            "plateau_patience": 20
        }
    },
    "outputs": {
        "save_outputs": true,
        "run_name": "241002_154718.centroid.n=100",
        "run_name_prefix": "",
        "run_name_suffix": "",
        "runs_folder": "/home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models",
        "tags": [
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        ],
        "save_visualizations": true,
        "keep_viz_images": false,
        "zip_outputs": false,
        "log_to_csv": true,
        "checkpointing": {
            "initial_model": false,
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            "every_epoch": false,
            "latest_model": false,
            "final_model": false
        },
        "tensorboard": {
            "write_logs": false,
            "loss_frequency": "epoch",
            "architecture_graph": false,
            "profile_graph": false,
            "visualizations": true
        },
        "zmq": {
            "subscribe_to_controller": true,
            "controller_address": "tcp://127.0.0.1:9000",
            "controller_polling_timeout": 10,
            "publish_updates": true,
            "publish_address": "tcp://127.0.0.1:9001"
        }
    },
    "name": "",
    "description": "",
    "sleap_version": "1.3.4",
    "filename": "/tmp/tmp24yhxdmr/241002_154718_training_job.json"
}
INFO:sleap.nn.training:
2024-10-02 15:47:20.154722: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:47:20.158588: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:47:20.159351: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
INFO:sleap.nn.training:Auto-selected GPU 0 with 23595 MiB of free memory.
INFO:sleap.nn.training:Using GPU 0 for acceleration.
INFO:sleap.nn.training:Disabled GPU memory pre-allocation.
INFO:sleap.nn.training:System:
GPUs: 1/1 available
  Device: /physical_device:GPU:0
         Available: True
       Initialized: False
     Memory growth: True
INFO:sleap.nn.training:
INFO:sleap.nn.training:Initializing trainer...
INFO:sleap.nn.training:Loading training labels from: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/courtship_labels.slp
INFO:sleap.nn.training:Creating training and validation splits from validation fraction: 0.1
INFO:sleap.nn.training:  Splits: Training = 90 / Validation = 10.
INFO:sleap.nn.training:Setting up for training...
INFO:sleap.nn.training:Setting up pipeline builders...
INFO:sleap.nn.training:Setting up model...
INFO:sleap.nn.training:Building test pipeline...
2024-10-02 15:47:21.010507: I tensorflow/core/platform/cpu_feature_guard.cc:151] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-10-02 15:47:21.011213: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:47:21.012052: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:47:21.012805: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:47:21.495290: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:47:21.496091: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:47:21.496837: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:47:21.497729: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1525] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 21690 MB memory:  -> device: 0, name: NVIDIA RTX A5000, pci bus id: 0000:01:00.0, compute capability: 8.6
INFO:sleap.nn.training:Loaded test example. [1.592s]
INFO:sleap.nn.training:  Input shape: (512, 512, 1)
INFO:sleap.nn.training:Created Keras model.
INFO:sleap.nn.training:  Backbone: UNet(stacks=1, filters=16, filters_rate=2.0, kernel_size=3, stem_kernel_size=7, convs_per_block=2, stem_blocks=0, down_blocks=4, middle_block=True, up_blocks=3, up_interpolate=True, block_contraction=False)
INFO:sleap.nn.training:  Max stride: 16
INFO:sleap.nn.training:  Parameters: 1,953,105
INFO:sleap.nn.training:  Heads: 
INFO:sleap.nn.training:    [0] = CentroidConfmapsHead(anchor_part='thorax', sigma=2.5, output_stride=2, loss_weight=1.0)
INFO:sleap.nn.training:  Outputs: 
INFO:sleap.nn.training:    [0] = KerasTensor(type_spec=TensorSpec(shape=(None, 256, 256, 1), dtype=tf.float32, name=None), name='CentroidConfmapsHead/BiasAdd:0', description="created by layer 'CentroidConfmapsHead'")
INFO:sleap.nn.training:Training from scratch
INFO:sleap.nn.training:Setting up data pipelines...
INFO:sleap.nn.training:Training set: n = 90
INFO:sleap.nn.training:Validation set: n = 10
INFO:sleap.nn.training:Setting up optimization...
INFO:sleap.nn.training:  Learning rate schedule: LearningRateScheduleConfig(reduce_on_plateau=True, reduction_factor=0.5, plateau_min_delta=1e-06, plateau_patience=5, plateau_cooldown=3, min_learning_rate=1e-08)
INFO:sleap.nn.training:  Early stopping: EarlyStoppingConfig(stop_training_on_plateau=True, plateau_min_delta=1e-08, plateau_patience=20)
INFO:sleap.nn.training:Setting up outputs...
INFO:sleap.nn.callbacks:Training controller subscribed to: tcp://127.0.0.1:9000 (topic: )
INFO:sleap.nn.training:  ZMQ controller subcribed to: tcp://127.0.0.1:9000
INFO:sleap.nn.callbacks:Progress reporter publishing on: tcp://127.0.0.1:9001 for: not_set
INFO:sleap.nn.training:  ZMQ progress reporter publish on: tcp://127.0.0.1:9001
INFO:sleap.nn.training:Created run path: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100
INFO:sleap.nn.training:Setting up visualization...
INFO:sleap.nn.training:Finished trainer set up. [3.7s]
INFO:sleap.nn.training:Creating tf.data.Datasets for training data generation...
INFO:sleap.nn.training:Finished creating training datasets. [3.9s]
INFO:sleap.nn.training:Starting training loop...
Epoch 1/2
2024-10-02 15:47:29.901992: I tensorflow/stream_executor/cuda/cuda_dnn.cc:366] Loaded cuDNN version 8201
WARNING:tensorflow:Callback method `on_train_batch_end` is slow compared to the batch time (batch time: 0.0070s vs `on_train_batch_end` time: 0.0272s). Check your callbacks.
2024-10-02 15:47:45.026376: I tensorflow/stream_executor/cuda/cuda_blas.cc:1774] TensorFloat-32 will be used for the matrix multiplication. This will only be logged once.
200/200 - 17s - loss: 2.0596e-04 - val_loss: 6.9952e-05 - lr: 1.0000e-04 - 17s/epoch - 85ms/step
Epoch 2/2
Polling: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100/viz/validation.*.png
200/200 - 9s - loss: 5.8520e-05 - val_loss: 3.3068e-05 - lr: 1.0000e-04 - 9s/epoch - 44ms/step
INFO:sleap.nn.training:Finished training loop. [0.4 min]
INFO:sleap.nn.training:Deleting visualization directory: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100/viz
INFO:sleap.nn.training:Saving evaluation metrics to model folder...
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% ETA: -:--:-- ?Polling: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100/viz/validation.*.png
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% ETA: 0:00:00 32.3 FPS
INFO:sleap.nn.evals:Saved predictions: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100/labels_pr.train.slp
INFO:sleap.nn.evals:Saved metrics: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100/metrics.train.npz
INFO:sleap.nn.evals:OKS mAP: 0.739213
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% ETA: 0:00:00 6.5 FPS
INFO:sleap.nn.evals:Saved predictions: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100/labels_pr.val.slp
INFO:sleap.nn.evals:Saved metrics: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100/metrics.val.npz
INFO:sleap.nn.evals:OKS mAP: 0.762445
INFO:sleap.nn.callbacks:Closing the reporter controller/context.
INFO:sleap.nn.callbacks:Closing the training controller socket/context.
Run Path: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100
Finished training centroid.
Resetting monitor window.
Polling: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154803.centered_instance.n=100/viz/validation.*.png
Start training centered_instance...
['sleap-train', '/tmp/tmpgru1wupt/241002_154803_training_job.json', '/home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/courtship_labels.slp', '--zmq', '--controller_port', '9000', '--publish_port', '9001', '--save_viz']
INFO:sleap.nn.training:Versions:
SLEAP: 1.4.1a3
TensorFlow: 2.7.0
Numpy: 1.19.5
Python: 3.7.12
OS: Linux-5.15.0-78-generic-x86_64-with-debian-bookworm-sid
INFO:sleap.nn.training:Training labels file: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/courtship_labels.slp
INFO:sleap.nn.training:Training profile: /tmp/tmpgru1wupt/241002_154803_training_job.json
INFO:sleap.nn.training:
INFO:sleap.nn.training:Arguments:
INFO:sleap.nn.training:{
    "training_job_path": "/tmp/tmpgru1wupt/241002_154803_training_job.json",
    "labels_path": "/home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/courtship_labels.slp",
    "video_paths": [
        ""
    ],
    "val_labels": null,
    "test_labels": null,
    "base_checkpoint": null,
    "tensorboard": false,
    "save_viz": true,
    "keep_viz": false,
    "zmq": true,
    "publish_port": 9001,
    "controller_port": 9000,
    "run_name": "",
    "prefix": "",
    "suffix": "",
    "cpu": false,
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INFO:sleap.nn.training:
INFO:sleap.nn.training:Training job:
INFO:sleap.nn.training:{
    "data": {
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        "preprocessing": {
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            "imagenet_mode": null,
            "input_scaling": 1.0,
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            "resize_and_pad_to_target": true,
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        "instance_cropping": {
            "center_on_part": "thorax",
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    "model": {
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                "part_names": [
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            "multi_class_topdown": null
        },
        "base_checkpoint": null
    },
    "optimization": {
        "preload_data": true,
        "augmentation_config": {
            "rotate": true,
            "rotation_min_angle": -180.0,
            "rotation_max_angle": 180.0,
            "translate": false,
            "translate_min": -5,
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            "scale_min": 0.9,
            "scale_max": 1.1,
            "uniform_noise": false,
            "uniform_noise_min_val": 0.0,
            "uniform_noise_max_val": 10.0,
            "gaussian_noise": false,
            "gaussian_noise_mean": 5.0,
            "gaussian_noise_stddev": 1.0,
            "contrast": false,
            "contrast_min_gamma": 0.5,
            "contrast_max_gamma": 2.0,
            "brightness": false,
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            "random_crop": false,
            "random_crop_height": 256,
            "random_crop_width": 256,
            "random_flip": false,
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        },
        "online_shuffling": true,
        "shuffle_buffer_size": 128,
        "prefetch": true,
        "batch_size": 4,
        "batches_per_epoch": 200,
        "min_batches_per_epoch": 200,
        "val_batches_per_epoch": 10,
        "min_val_batches_per_epoch": 10,
        "epochs": 2,
        "optimizer": "adam",
        "initial_learning_rate": 0.0001,
        "learning_rate_schedule": {
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            "plateau_min_delta": 1e-06,
            "plateau_patience": 5,
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            "min_learning_rate": 1e-08
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        "hard_keypoint_mining": {
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        "early_stopping": {
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            "plateau_min_delta": 1e-08,
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    "outputs": {
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        "run_name": "241002_154803.centered_instance.n=100",
        "run_name_prefix": "",
        "run_name_suffix": "",
        "runs_folder": "/home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models",
        "tags": [
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        "save_visualizations": true,
        "keep_viz_images": false,
        "zip_outputs": false,
        "log_to_csv": true,
        "checkpointing": {
            "initial_model": false,
            "best_model": true,
            "every_epoch": false,
            "latest_model": false,
            "final_model": false
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        "tensorboard": {
            "write_logs": false,
            "loss_frequency": "epoch",
            "architecture_graph": false,
            "profile_graph": false,
            "visualizations": true
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        "zmq": {
            "subscribe_to_controller": true,
            "controller_address": "tcp://127.0.0.1:9000",
            "controller_polling_timeout": 10,
            "publish_updates": true,
            "publish_address": "tcp://127.0.0.1:9001"
        }
    },
    "name": "",
    "description": "",
    "sleap_version": "1.3.4",
    "filename": "/tmp/tmpgru1wupt/241002_154803_training_job.json"
}
INFO:sleap.nn.training:
2024-10-02 15:48:05.274516: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:48:05.278622: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:48:05.279398: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
INFO:sleap.nn.training:Auto-selected GPU 0 with 23561 MiB of free memory.
INFO:sleap.nn.training:Using GPU 0 for acceleration.
INFO:sleap.nn.training:Disabled GPU memory pre-allocation.
INFO:sleap.nn.training:System:
GPUs: 1/1 available
  Device: /physical_device:GPU:0
         Available: True
       Initialized: False
     Memory growth: True
INFO:sleap.nn.training:
INFO:sleap.nn.training:Initializing trainer...
INFO:sleap.nn.training:Loading training labels from: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/courtship_labels.slp
INFO:sleap.nn.training:Creating training and validation splits from validation fraction: 0.1
INFO:sleap.nn.training:  Splits: Training = 90 / Validation = 10.
INFO:sleap.nn.training:Setting up for training...
INFO:sleap.nn.training:Setting up pipeline builders...
INFO:sleap.nn.training:Setting up model...
INFO:sleap.nn.training:Building test pipeline...
2024-10-02 15:48:06.162074: I tensorflow/core/platform/cpu_feature_guard.cc:151] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-10-02 15:48:06.162592: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:48:06.163453: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:48:06.164197: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:48:06.444211: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:48:06.445005: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:48:06.445731: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:48:06.446434: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1525] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 21676 MB memory:  -> device: 0, name: NVIDIA RTX A5000, pci bus id: 0000:01:00.0, compute capability: 8.6
INFO:sleap.nn.training:Loaded test example. [1.776s]
INFO:sleap.nn.training:  Input shape: (144, 144, 1)
INFO:sleap.nn.training:Created Keras model.
INFO:sleap.nn.training:  Backbone: UNet(stacks=1, filters=24, filters_rate=2.0, kernel_size=3, stem_kernel_size=7, convs_per_block=2, stem_blocks=0, down_blocks=4, middle_block=True, up_blocks=2, up_interpolate=True, block_contraction=False)
INFO:sleap.nn.training:  Max stride: 16
INFO:sleap.nn.training:  Parameters: 4,311,445
INFO:sleap.nn.training:  Heads: 
INFO:sleap.nn.training:    [0] = CenteredInstanceConfmapsHead(part_names=['head', 'thorax', 'abdomen', 'wingL', 'wingR', 'forelegL4', 'forelegR4', 'midlegL4', 'midlegR4', 'hindlegL4', 'hindlegR4', 'eyeL', 'eyeR'], anchor_part='thorax', sigma=2.5, output_stride=4, loss_weight=1.0)
INFO:sleap.nn.training:  Outputs: 
INFO:sleap.nn.training:    [0] = KerasTensor(type_spec=TensorSpec(shape=(None, 36, 36, 13), dtype=tf.float32, name=None), name='CenteredInstanceConfmapsHead/BiasAdd:0', description="created by layer 'CenteredInstanceConfmapsHead'")
INFO:sleap.nn.training:Training from scratch
INFO:sleap.nn.training:Setting up data pipelines...
INFO:sleap.nn.training:Training set: n = 90
INFO:sleap.nn.training:Validation set: n = 10
INFO:sleap.nn.training:Setting up optimization...
INFO:sleap.nn.training:  Learning rate schedule: LearningRateScheduleConfig(reduce_on_plateau=True, reduction_factor=0.5, plateau_min_delta=1e-06, plateau_patience=5, plateau_cooldown=3, min_learning_rate=1e-08)
INFO:sleap.nn.training:  Early stopping: EarlyStoppingConfig(stop_training_on_plateau=True, plateau_min_delta=1e-08, plateau_patience=10)
INFO:sleap.nn.training:Setting up outputs...
INFO:sleap.nn.callbacks:Training controller subscribed to: tcp://127.0.0.1:9000 (topic: )
INFO:sleap.nn.training:  ZMQ controller subcribed to: tcp://127.0.0.1:9000
INFO:sleap.nn.callbacks:Progress reporter publishing on: tcp://127.0.0.1:9001 for: not_set
INFO:sleap.nn.training:  ZMQ progress reporter publish on: tcp://127.0.0.1:9001
INFO:sleap.nn.training:Created run path: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154803.centered_instance.n=100
INFO:sleap.nn.training:Setting up visualization...
INFO:sleap.nn.training:Finished trainer set up. [3.3s]
INFO:sleap.nn.training:Creating tf.data.Datasets for training data generation...
INFO:sleap.nn.training:Finished creating training datasets. [4.5s]
INFO:sleap.nn.training:Starting training loop...
Epoch 1/2
2024-10-02 15:48:15.421387: I tensorflow/stream_executor/cuda/cuda_dnn.cc:366] Loaded cuDNN version 8201
WARNING:tensorflow:Callback method `on_train_batch_end` is slow compared to the batch time (batch time: 0.0088s vs `on_train_batch_end` time: 0.0111s). Check your callbacks.
2024-10-02 15:48:21.934996: I tensorflow/stream_executor/cuda/cuda_blas.cc:1774] TensorFloat-32 will be used for the matrix multiplication. This will only be logged once.
200/200 - 9s - loss: 0.0110 - head: 0.0078 - thorax: 0.0065 - abdomen: 0.0110 - wingL: 0.0124 - wingR: 0.0126 - forelegL4: 0.0113 - forelegR4: 0.0108 - midlegL4: 0.0130 - midlegR4: 0.0131 - hindlegL4: 0.0132 - hindlegR4: 0.0132 - eyeL: 0.0093 - eyeR: 0.0088 - val_loss: 0.0083 - val_head: 0.0028 - val_thorax: 0.0034 - val_abdomen: 0.0071 - val_wingL: 0.0087 - val_wingR: 0.0088 - val_forelegL4: 0.0095 - val_forelegR4: 0.0098 - val_midlegL4: 0.0111 - val_midlegR4: 0.0121 - val_hindlegL4: 0.0121 - val_hindlegR4: 0.0128 - val_eyeL: 0.0052 - val_eyeR: 0.0051 - lr: 1.0000e-04 - 9s/epoch - 43ms/step
Polling: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100/viz/validation.*.png
Polling: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154803.centered_instance.n=100/viz/validation.*.png
Epoch 2/2
200/200 - 5s - loss: 0.0069 - head: 0.0020 - thorax: 0.0027 - abdomen: 0.0058 - wingL: 0.0069 - wingR: 0.0075 - forelegL4: 0.0078 - forelegR4: 0.0079 - midlegL4: 0.0104 - midlegR4: 0.0104 - hindlegL4: 0.0112 - hindlegR4: 0.0111 - eyeL: 0.0029 - eyeR: 0.0027 - val_loss: 0.0056 - val_head: 8.2737e-04 - val_thorax: 0.0018 - val_abdomen: 0.0040 - val_wingL: 0.0047 - val_wingR: 0.0053 - val_forelegL4: 0.0083 - val_forelegR4: 0.0076 - val_midlegL4: 0.0074 - val_midlegR4: 0.0090 - val_hindlegL4: 0.0096 - val_hindlegR4: 0.0102 - val_eyeL: 0.0020 - val_eyeR: 0.0017 - lr: 1.0000e-04 - 5s/epoch - 23ms/step
INFO:sleap.nn.training:Finished training loop. [0.2 min]
INFO:sleap.nn.training:Deleting visualization directory: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154803.centered_instance.n=100/viz
INFO:sleap.nn.training:Saving evaluation metrics to model folder...
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   0% ETA: -:--:-- ?Polling: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100/viz/validation.*.png
Polling: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154803.centered_instance.n=100/viz/validation.*.png
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% ETA: 0:00:00 47.6 FPS
INFO:sleap.nn.evals:Saved predictions: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154803.centered_instance.n=100/labels_pr.train.slp
INFO:sleap.nn.evals:Saved metrics: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154803.centered_instance.n=100/metrics.train.npz
INFO:sleap.nn.evals:OKS mAP: 0.011421
Predicting... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% ETA: 0:00:00 10.4 FPS
INFO:sleap.nn.evals:Saved predictions: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154803.centered_instance.n=100/labels_pr.val.slp
INFO:sleap.nn.evals:Saved metrics: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154803.centered_instance.n=100/metrics.val.npz
INFO:sleap.nn.evals:OKS mAP: 0.029356
INFO:sleap.nn.callbacks:Closing the reporter controller/context.
INFO:sleap.nn.callbacks:Closing the training controller socket/context.
Run Path: /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154803.centered_instance.n=100
Finished training centered_instance.
Command line call:
sleap-track /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/courtship_labels.slp --video.index 0 --frames 37,72,84,188,324,444,453,473,513,588,598,623,823,859,954,955,1022,1083,1088 -m /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100 -m /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154803.centered_instance.n=100 --controller_port 9000 --publish_port 9001 -o /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/predictions/courtship_labels.slp.241002_154834.predictions.slp --verbosity json --no-empty-frames

Started inference at: 2024-10-02 15:48:36.331737
2024-10-02 15:48:36.358515: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:48:36.362516: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:48:36.363263: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
Args:
{
│   'data_path': '/home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/courtship_labels.slp',
│   'models': [
│   │   '/home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100',
│   │   '/home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154803.centered_instance.n=100'
│   ],
│   'frames': '37,72,84,188,324,444,453,473,513,588,598,623,823,859,954,955,1022,1083,1088',
│   'only_labeled_frames': False,
│   'only_suggested_frames': False,
│   'output': '/home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/predictions/courtship_labels.slp.241002_154834.predictions.slp',
│   'no_empty_frames': True,
│   'verbosity': 'json',
│   'video.dataset': None,
2024-10-02 15:48:37.050031: I tensorflow/core/platform/cpu_feature_guard.cc:151] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-10-02 15:48:37.050547: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:48:37.051526: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:48:37.052260: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
│   'video.input_format': 'channels_last',
│   'video.index': '0',
│   'cpu': False,
│   'first_gpu': False,
│   'last_gpu': False,
│   'gpu': 'auto',
2024-10-02 15:48:37.347401: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:48:37.348168: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:48:37.348863: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:48:37.349535: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1525] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 21581 MB memory:  -> device: 0, name: NVIDIA RTX A5000, pci bus id: 0000:01:00.0, compute capability: 8.6
│   'max_edge_length_ratio': 0.25,
│   'dist_penalty_weight': 1.0,
│   'batch_size': 4,
│   'open_in_gui': False,
│   'peak_threshold': 0.2,
│   'max_instances': None,
│   'tracking.tracker': None,
│   'tracking.max_tracking': None,
│   'tracking.max_tracks': None,
│   'tracking.target_instance_count': None,
│   'tracking.pre_cull_to_target': None,
│   'tracking.pre_cull_iou_threshold': None,
│   'tracking.post_connect_single_breaks': None,
│   'tracking.clean_instance_count': None,
│   'tracking.clean_iou_threshold': None,
│   'tracking.similarity': None,
│   'tracking.match': None,
│   'tracking.robust': None,
│   'tracking.track_window': None,
│   'tracking.min_new_track_points': None,
│   'tracking.min_match_points': None,
│   'tracking.img_scale': None,
│   'tracking.of_window_size': None,
│   'tracking.of_max_levels': None,
│   'tracking.save_shifted_instances': None,
│   'tracking.kf_node_indices': None,
│   'tracking.kf_init_frame_count': None,
│   'tracking.oks_errors': None,
│   'tracking.oks_score_weighting': None,
│   'tracking.oks_normalization': None
}

INFO:sleap.nn.inference:Auto-selected GPU 0 with 23486 MiB of free memory.
2024-10-02 15:48:41.109110: I tensorflow/stream_executor/cuda/cuda_dnn.cc:366] Loaded cuDNN version 8201
Versions:
SLEAP: 1.4.1a3
TensorFlow: 2.7.0
Numpy: 1.19.5
Python: 3.7.12
OS: Linux-5.15.0-78-generic-x86_64-with-debian-bookworm-sid

System:
GPUs: 1/1 available
  Device: /physical_device:GPU:0
         Available: True
       Initialized: False
     Memory growth: True

Finished inference at: 2024-10-02 15:48:44.303228
Total runtime: 7.971500873565674 secs
Predicted frames: 19/19
Provenance:
{
│   'model_paths': [
│   │   '/home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100/training_config.json',
│   │   '/home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154803.centered_instance.n=100/training_config.json'
│   ],
│   'predictor': 'TopDownPredictor',
│   'sleap_version': '1.4.1a3',
│   'platform': 'Linux-5.15.0-78-generic-x86_64-with-debian-bookworm-sid',
│   'command': '/home/talmolab/micromamba/envs/sleap_1.4.1a3/bin/sleap-track /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/courtship_labels.slp --video.index 0 --frames 37,72,84,188,324,444,453,473,513,588,598,623,823,859,954,955,1022,1083,1088 -m /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154718.centroid.n=100 -m /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/models/241002_154803.centered_instance.n=100 --controller_port 9000 --publish_port 9001 -o /home/talmolab/sleap-estimates-animal-poses/datasets/drosophila-melanogaster-courtship/drosophila-melanogaster-courtship/predictions/courtship_labels.slp.241002_154834.predictions.slp --verbosity json --no-empty-frames',
Process return code: 0
Training Dialog

image

No terminal output when opening training dialog.





sleap-label

image


(sleap_1.4) talmolab@talmolab-01-ubuntu:~/Downloads$ sleap-label
Saving config: /home/talmolab/.sleap/1.4.1a3/preferences.yaml
2024-10-02 15:45:03.931824: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:45:03.959522: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2024-10-02 15:45:03.960304: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:939] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero

Software versions:
SLEAP: 1.4.1a3
TensorFlow: 2.7.0
Numpy: 1.19.5
Python: 3.7.12
OS: Linux-5.15.0-78-generic-x86_64-with-debian-bookworm-sid

Happy SLEAPing! :)




Installation

talmolab@talmolab-01-ubuntu:~/Downloads$ mm create -n sleap_1.4.1a3 -c conda-forge -c nvidia -c ./sleap-build-linux -c anaconda sleap=1.4.1a3
file:///home/talmolab/Downloads/sleap-build-linu.. Checked  0.0s
file:///home/talmolab/Downloads/sleap-build-linu.. Checked  0.0s
nvidia/linux-64 (check zst)                        Checked  0.1s
anaconda/linux-64 (check zst)                      Checked  0.1s
nvidia/noarch (check zst)                          Checked  0.1s
anaconda/noarch (check zst)                         Checked  0.1s
sleap/linux-64 (check zst)                          Checked  0.2s
sleap/noarch (check zst)                            Checked  0.1s
file:///home/talmolab/Downloads/sleap-build-linu.. 981.0 B @  35.0MB/s  0.0s
file:///home/talmolab/Downloads/sleap-build-linu..  96.0 B @   7.4MB/s  0.0s
nvidia/noarch                                       17.0kB @ 354.4kB/s  0.0s
nvidia/linux-64                                    191.0kB @   2.4MB/s  0.1s
anaconda/noarch                                    403.2kB @   2.6MB/s  0.1s
anaconda/linux-64                                    3.1MB @  17.7MB/s  0.2s
sleap/linux-64                                       2.5kB @  11.0kB/s  0.2s
conda-forge/noarch                                  16.7MB @  54.8MB/s  0.3s
sleap/noarch                                       116.0 B @ 251.0 B/s  0.3s
conda-forge/linux-64                               @  75.9MB/s  0.6s

Transaction

  Prefix: /home/talmolab/micromamba/envs/sleap_1.4.1a3

  Updating specs:

   - sleap=1.4.1a3


  Package                           Version  Build                   Channel                                          Size
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
  Install:
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────

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  + libopenblas                      0.3.27  pthreads_hac2b453_1     conda-forge                                    Cached
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  + python                           3.7.12  hb7a2778_100_cpython    conda-forge                                    Cached
  + blas                                1.1  openblas                conda-forge                                    Cached
  + libcblas                          3.9.0  24_linux64_openblas     conda-forge                                      15kB
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  + libidn2                           2.3.7  hd590300_0              conda-forge                                     127kB
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  + six                              1.16.0  pyh6c4a22f_0            conda-forge                                    Cached
  + jsonpickle                          1.2  py_0                    conda-forge                                    Cached
  + attrs                            21.4.0  pyhd8ed1ab_0            conda-forge                                    Cached
  + jsmin                             3.0.1  pyhd8ed1ab_0            conda-forge                                    Cached
  + fonts-conda-ecosystem                 1  0                       conda-forge                                    Cached
  + cached-property                   1.5.2  hd8ed1ab_1              conda-forge                                    Cached
  + importlib_resources               6.0.0  pyhd8ed1ab_0            conda-forge                                      27kB
  + partd                             1.4.1  pyhd8ed1ab_0            conda-forge                                    Cached
  + qtpy                              2.4.1  pyhd8ed1ab_0            conda-forge                                    Cached
  + typing-extensions                 4.7.1  hd8ed1ab_0              conda-forge                                    Cached
  + markdown-it-py                    2.2.0  pyhd8ed1ab_0            conda-forge                                    Cached
  + python-dateutil                   2.9.0  pyhd8ed1ab_0            conda-forge                                    Cached
  + cattrs                            1.1.1  pyhd8ed1ab_0            conda-forge                                    Cached
  + rich                             13.8.1  pyhd8ed1ab_0            conda-forge                                     185kB
  + unicodedata2                     14.0.0  py37h540881e_1          conda-forge                                    Cached
  + pyrsistent                       0.18.1  py37h540881e_1          conda-forge                                      93kB
  + glib                             2.80.2  hf974151_0              conda-forge                                     600kB
  + ruamel.yaml.clib                  0.2.6  py37h540881e_1          conda-forge                                     152kB
  + pyzmq                            24.0.1  py37h0c0c2a8_0          conda-forge                                    Cached
  + pyyaml                              6.0  py37h540881e_4          conda-forge                                    Cached
  + python-rapidjson                    1.9  py37hd23a5d3_0          conda-forge                                    Cached
  + psutil                            5.9.3  py37h540881e_0          conda-forge                                    Cached
  + pillow                            9.2.0  py37h850a105_2          conda-forge                                    Cached
  + numpy                            1.21.6  py37h976b520_0          conda-forge                                    Cached
  + cytoolz                          0.12.0  py37h540881e_0          conda-forge                                    Cached
  + importlib-metadata               4.11.4  py37h89c1867_0          conda-forge                                    Cached
  + protobuf                         3.20.1  py37hd23a5d3_0          conda-forge                                     336kB
  + cairo                            1.16.0  ha12eb4b_1010           conda-forge                                       2MB
  + ffmpeg                            4.4.2  gpl_hbd009f3_109        conda-forge                                      10MB
  + kiwisolver                        1.4.4  py37h7cecad7_0          conda-forge                                    Cached
  + fonttools                        4.38.0  py37h540881e_0          conda-forge                                    Cached
  + gstreamer                        1.20.3  hd4edc92_2              conda-forge                                       2MB
  + ruamel.yaml                     0.17.21  py37h540881e_1          conda-forge                                     175kB
  + imagecodecs                  2021.11.20  py37h119f88a_2          conda-forge                                    Cached
  + pywavelets                        1.3.0  py37hda87dfa_1          conda-forge                                    Cached
  + pandas                            1.3.5  py37he8f5f7f_0          conda-forge                                    Cached
  + h5py                              3.7.0  nompi_py37hc97082c_100  conda-forge                                       1MB
  + harfbuzz                          4.2.0  h40b6f09_0              conda-forge                                       2MB
  + matplotlib-base                   3.5.3  py37hf395dca_2          conda-forge                                    Cached
  + gst-plugins-base                 1.20.3  h57caac4_2              conda-forge                                       3MB
  + qt                               5.12.9  h1304e3e_6              conda-forge                                     103MB
  + pyside2                          5.13.2  py37h3927acf_8          conda-forge                                      14MB
  + libopencv                         4.5.5  py37h780a5f5_10         conda-forge                                      37MB
  + py-opencv                         4.5.5  py37h25bab4e_10         conda-forge                                       1MB
  + opencv                            4.5.5  py37h89c1867_10         conda-forge                                      23kB
  + tensorflow                        2.7.0  py37hb93dfd8_3          sleap                                          Cached
  + dask-core                      2022.2.0  pyhd8ed1ab_0            conda-forge                                    Cached
  + imageio                          2.35.1  pyh12aca89_0            conda-forge                                    Cached
  + patsy                             0.5.6  pyhd8ed1ab_0            conda-forge                                    Cached
  + jsonschema                       4.17.3  pyhd8ed1ab_0            conda-forge                                      70kB
  + imageio-ffmpeg                    0.5.1  pyhd8ed1ab_0            conda-forge                                      21kB
  + tifffile                      2021.11.2  pyhd8ed1ab_0            conda-forge                                    Cached
  + tensorflow-hub                   0.13.0  pyh56297ac_0            conda-forge                                    Cached
  + scipy                             1.7.3  py37hf838250_2          anaconda                                       Cached
  + hdmf                              3.6.1  pyh1a96a4e_0            conda-forge                                     155kB
  + seaborn-base                     0.12.2  pyhd8ed1ab_0            conda-forge                                    Cached
  + pykalman                          0.9.7  pyhd8ed1ab_0            conda-forge                                    Cached
  + networkx                            2.7  pyhd8ed1ab_0            conda-forge                                    Cached
  + scikit-video                     1.1.11  pyh24bf2e0_0            conda-forge                                    Cached
  + statsmodels                      0.13.2  py37hda87dfa_0          conda-forge                                    Cached
  + scikit-learn                        1.0  py37hf0f1638_1          conda-forge                                    Cached
  + pynwb                             2.2.0  py37h89c1867_0          conda-forge                                     313kB
  + scikit-image                     0.19.2  py37he8f5f7f_0          conda-forge                                    Cached
  + seaborn                          0.12.2  hd8ed1ab_0              conda-forge                                    Cached
  + qudida                            0.0.4  pyhd8ed1ab_0            conda-forge                                       7kB
  + ndx-pose                          0.1.1  pyhd8ed1ab_0            conda-forge                                      13kB
  + albumentations                    1.3.1  pyhd8ed1ab_0            conda-forge                                      97kB
  + sleap                           1.4.1a3  py37_0                  /home/talmolab/Downloads/sleap-build-linux        3MB

  Summary:

  Install: 242 packages

  Total download: 263MB


pip freeze

(sleap_1.4) talmolab@talmolab-01-ubuntu:~/Downloads$ pip freeze
absl-py==1.0.0
albumentations @ file:///home/conda/feedstock_root/build_artifacts/albumentations_1686576355052/work
astunparse==1.6.3
attrs @ file:///home/conda/feedstock_root/build_artifacts/attrs_1640799537051/work
backports.zoneinfo==0.2.1
cached-property @ file:///home/conda/feedstock_root/build_artifacts/cached_property_1615209429212/work
cachetools==4.2.4
cattrs @ file:///home/conda/feedstock_root/build_artifacts/cattrs_1604136207372/work
certifi @ file:///home/conda/feedstock_root/build_artifacts/certifi_1725278078093/work/certifi
charset-normalizer==2.0.9
cloudpickle @ file:///home/conda/feedstock_root/build_artifacts/cloudpickle_1674202310934/work
cycler @ file:///home/conda/feedstock_root/build_artifacts/cycler_1635519461629/work
cytoolz @ file:///home/conda/feedstock_root/build_artifacts/cytoolz_1657553457169/work
dask @ file:///home/conda/feedstock_root/build_artifacts/dask-core_1644602974678/work
efficientnet==1.0.0
flatbuffers==2.0
fonttools @ file:///home/conda/feedstock_root/build_artifacts/fonttools_1666389892786/work
fsspec @ file:///home/conda/feedstock_root/build_artifacts/fsspec_1674184942191/work
gast==0.4.0
google-auth==2.3.3
google-auth-oauthlib==0.4.6
google-pasta==0.2.0
grpcio==1.43.0
h5py==3.1.0
hdmf @ file:///home/conda/feedstock_root/build_artifacts/hdmf_1684510272253/work
idna==3.3
image-classifiers==1.0.0
imagecodecs @ file:///home/conda/feedstock_root/build_artifacts/imagecodecs_1644819473370/work
imageio @ file:///home/conda/feedstock_root/build_artifacts/imageio_1724069053555/work
imageio-ffmpeg @ file:///home/conda/feedstock_root/build_artifacts/imageio-ffmpeg_1717461632069/work
imgstore==0.2.9
importlib-metadata==4.10.0
importlib-resources @ file:///home/conda/feedstock_root/build_artifacts/importlib_resources_1688813467203/work
joblib @ file:///home/conda/feedstock_root/build_artifacts/joblib_1691577114857/work
jsmin @ file:///home/conda/feedstock_root/build_artifacts/jsmin_1642532731678/work
jsonpickle==1.2
jsonschema @ file:///home/conda/feedstock_root/build_artifacts/jsonschema-meta_1669810440410/work
keras==2.7.0
Keras-Applications==1.0.8
Keras-Preprocessing==1.1.2
kiwisolver @ file:///home/conda/feedstock_root/build_artifacts/kiwisolver_1657953088445/work
libclang==12.0.0
locket @ file:///home/conda/feedstock_root/build_artifacts/locket_1650660393415/work
Markdown==3.3.6
markdown-it-py @ file:///home/conda/feedstock_root/build_artifacts/markdown-it-py_1677100944732/work
matplotlib @ file:///home/conda/feedstock_root/build_artifacts/matplotlib-suite_1661439848456/work
mdurl @ file:///home/conda/feedstock_root/build_artifacts/mdurl_1704317613764/work
munkres==1.1.4
ndx-pose @ file:///home/conda/feedstock_root/build_artifacts/ndx-pose_1706810229855/work
networkx @ file:///home/conda/feedstock_root/build_artifacts/networkx_1646092782768/work
nixio==1.5.3
numpy==1.19.5
oauthlib==3.1.1
opencv-python==4.5.5
opencv-python-headless==4.2.0.34
opt-einsum==3.3.0
packaging==21.3
pandas==1.3.5
partd @ file:///home/conda/feedstock_root/build_artifacts/partd_1695667515973/work
patsy @ file:///home/conda/feedstock_root/build_artifacts/patsy_1704469236901/work
Pillow @ file:///home/conda/feedstock_root/build_artifacts/pillow_1660385854171/work
pkgutil_resolve_name @ file:///home/conda/feedstock_root/build_artifacts/pkgutil-resolve-name_1694617248815/work
protobuf==3.19.1
psutil @ file:///home/conda/feedstock_root/build_artifacts/psutil_1666155398032/work
pyasn1==0.4.8
pyasn1-modules==0.2.8
Pygments @ file:///home/conda/feedstock_root/build_artifacts/pygments_1700607939962/work
pykalman @ file:///home/conda/feedstock_root/build_artifacts/pykalman_1711547707628/work
pynwb @ file:///home/conda/feedstock_root/build_artifacts/pynwb_1666675085499/work
pyparsing==3.0.6
pyrsistent @ file:///home/conda/feedstock_root/build_artifacts/pyrsistent_1649013358450/work
PySide2==5.13.2
python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1709299778482/work
python-rapidjson @ file:///home/conda/feedstock_root/build_artifacts/python-rapidjson_1665999896718/work
pytz @ file:///home/conda/feedstock_root/build_artifacts/pytz_1726055524169/work
PyWavelets @ file:///home/conda/feedstock_root/build_artifacts/pywavelets_1649616401885/work
PyYAML @ file:///home/conda/feedstock_root/build_artifacts/pyyaml_1648757092905/work
pyzmq @ file:///home/conda/feedstock_root/build_artifacts/pyzmq_1663830492333/work
qimage2ndarray==1.10.0
QtPy @ file:///home/conda/feedstock_root/build_artifacts/qtpy_1698112029416/work
qudida @ file:///home/conda/feedstock_root/build_artifacts/qudida_1651101164121/work
requests==2.26.0
requests-oauthlib==1.3.0
rich @ file:///home/conda/feedstock_root/build_artifacts/rich_1726066019428/work/dist
rsa==4.8
ruamel.yaml @ file:///home/conda/feedstock_root/build_artifacts/ruamel.yaml_1649033206568/work
ruamel.yaml.clib @ file:///home/conda/feedstock_root/build_artifacts/ruamel.yaml.clib_1649013068865/work
scikit-image @ file:///home/conda/feedstock_root/build_artifacts/scikit-image_1645196656256/work
scikit-learn @ file:///home/conda/feedstock_root/build_artifacts/scikit-learn_1632611341839/work
scikit-video==1.1.11
scipy @ file:///opt/conda/conda-bld/scipy_1661390393401/work
seaborn @ file:///home/conda/feedstock_root/build_artifacts/seaborn-split_1672497695270/work
segmentation-models==1.0.1
setuptools-scm==6.3.2
shiboken2==5.13.2
six @ file:///home/conda/feedstock_root/build_artifacts/six_1620240208055/work
sleap==1.4.1a3
statsmodels @ file:///home/conda/feedstock_root/build_artifacts/statsmodels_1654787101575/work
tensorboard==2.7.0
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.0
tensorflow==2.7.0
tensorflow-estimator==2.7.0
tensorflow-hub @ file:///home/conda/feedstock_root/build_artifacts/tensorflow-hub_1678880940235/work/wheel_dir/tensorflow_hub-0.13.0-py2.py3-none-any.whl
tensorflow-io-gcs-filesystem==0.23.1
termcolor==1.1.0
threadpoolctl @ file:///home/conda/feedstock_root/build_artifacts/threadpoolctl_1643647933166/work
tifffile @ file:///home/conda/feedstock_root/build_artifacts/tifffile_1635944860688/work
tomli==2.0.0
toolz @ file:///home/conda/feedstock_root/build_artifacts/toolz_1706112571092/work
typing_extensions==4.0.1
tzlocal==5.1
unicodedata2 @ file:///home/conda/feedstock_root/build_artifacts/unicodedata2_1649111917568/work
urllib3==1.26.7
Werkzeug==2.0.2
wrapt==1.13.3
zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1677313463193/work




mamba list

(sleap_1.4) talmolab@talmolab-01-ubuntu:~/Downloads$ mm list
List of packages in environment: "/home/talmolab/micromamba/envs/sleap_1.4.1a3"

  Name                       Version       Build                   Channel          
──────────────────────────────────────────────────────────────────────────────────────
  _libgcc_mutex              0.1           conda_forge             conda-forge      
  _openmp_mutex              4.5           2_gnu                   conda-forge      
  albumentations             1.3.1         pyhd8ed1ab_0            conda-forge      
  alsa-lib                   1.2.7.2       h166bdaf_0              conda-forge      
  aom                        3.5.0         h27087fc_0              conda-forge      
  attrs                      21.4.0        pyhd8ed1ab_0            conda-forge      
  blas                       1.1           openblas                conda-forge      
  blosc                      1.21.5        h0f2a231_0              conda-forge      
  brotli                     1.0.9         h166bdaf_9              conda-forge      
  brotli-bin                 1.0.9         h166bdaf_9              conda-forge      
  brunsli                    0.1           h9c3ff4c_0              conda-forge      
  bzip2                      1.0.8         h4bc722e_7              conda-forge      
  c-ares                     1.33.1        heb4867d_0              conda-forge      
  c-blosc2                   2.12.0        hb4ffafa_0              conda-forge      
  ca-certificates            2024.8.30     hbcca054_0              conda-forge      
  cached-property            1.5.2         hd8ed1ab_1              conda-forge      
  cached_property            1.5.2         pyha770c72_1            conda-forge      
  cairo                      1.16.0        ha12eb4b_1010           conda-forge      
  cattrs                     1.1.1         pyhd8ed1ab_0            conda-forge      
  certifi                    2024.8.30     pyhd8ed1ab_0            conda-forge      
  cfitsio                    4.0.0         h9a35b8e_0              conda-forge      
  charls                     2.3.4         h9c3ff4c_0              conda-forge      
  cloudpickle                2.2.1         pyhd8ed1ab_0            conda-forge      
  cuda-nvcc                  11.3.58       h2467b9f_0              nvidia           
  cudatoolkit                11.3.1        hb98b00a_13             conda-forge      
  cudnn                      8.2.1.32      h86fa8c9_0              conda-forge      
  cycler                     0.11.0        pyhd8ed1ab_0            conda-forge      
  cytoolz                    0.12.0        py37h540881e_0          conda-forge      
  dask-core                  2022.2.0      pyhd8ed1ab_0            conda-forge      
  dbus                       1.13.6        h5008d03_3              conda-forge      
  expat                      2.6.3         h5888daf_0              conda-forge      
  ffmpeg                     4.4.2         gpl_hbd009f3_109        conda-forge      
  fftw                       3.3.10        nompi_hf1063bd_110      conda-forge      
  font-ttf-dejavu-sans-mono  2.37          hab24e00_0              conda-forge      
  font-ttf-inconsolata       3.000         h77eed37_0              conda-forge      
  font-ttf-source-code-pro   2.038         h77eed37_0              conda-forge      
  font-ttf-ubuntu            0.83          h77eed37_3              conda-forge      
  fontconfig                 2.14.2        h14ed4e7_0              conda-forge      
  fonts-conda-ecosystem      1             0                       conda-forge      
  fonts-conda-forge          1             0                       conda-forge      
  fonttools                  4.38.0        py37h540881e_0          conda-forge      
  freeglut                   3.2.2         h9c3ff4c_1              conda-forge      
  freetype                   2.12.1        h267a509_2              conda-forge      
  fsspec                     2023.1.0      pyhd8ed1ab_0            conda-forge      
  gettext                    0.22.5        he02047a_3              conda-forge      
  gettext-tools              0.22.5        he02047a_3              conda-forge      
  giflib                     5.2.2         hd590300_0              conda-forge      
  glib                       2.80.2        hf974151_0              conda-forge      
  glib-tools                 2.80.2        hb6ce0ca_0              conda-forge      
  gmp                        6.3.0         hac33072_2              conda-forge      
  gnutls                     3.7.9         hb077bed_0              conda-forge      
  graphite2                  1.3.13        h59595ed_1003           conda-forge      
  gst-plugins-base           1.20.3        h57caac4_2              conda-forge      
  gstreamer                  1.20.3        hd4edc92_2              conda-forge      
  h5py                       3.7.0         nompi_py37hc97082c_100  conda-forge      
  harfbuzz                   4.2.0         h40b6f09_0              conda-forge      
  hdf5                       1.12.1        nompi_h2386368_104      conda-forge      
  hdmf                       3.6.1         pyh1a96a4e_0            conda-forge      
  icu                        69.1          h9c3ff4c_0              conda-forge      
  imagecodecs                2021.11.20    py37h119f88a_2          conda-forge      
  imageio                    2.35.1        pyh12aca89_0            conda-forge      
  imageio-ffmpeg             0.5.1         pyhd8ed1ab_0            conda-forge      
  importlib-metadata         4.11.4        py37h89c1867_0          conda-forge      
  importlib_resources        6.0.0         pyhd8ed1ab_0            conda-forge      
  jasper                     2.0.33        h0ff4b12_1              conda-forge      
  joblib                     1.3.2         pyhd8ed1ab_0            conda-forge      
  jpeg                       9e            h0b41bf4_3              conda-forge      
  jsmin                      3.0.1         pyhd8ed1ab_0            conda-forge      
  jsonpickle                 1.2           py_0                    conda-forge      
  jsonschema                 4.17.3        pyhd8ed1ab_0            conda-forge      
  jxrlib                     1.1           hd590300_3              conda-forge      
  keyutils                   1.6.1         h166bdaf_0              conda-forge      
  kiwisolver                 1.4.4         py37h7cecad7_0          conda-forge      
  krb5                       1.20.1        hf9c8cef_0              conda-forge      
  lame                       3.100         h166bdaf_1003           conda-forge      
  lcms2                      2.14          h6ed2654_0              conda-forge      
  ld_impl_linux-64           2.43          h712a8e2_1              conda-forge      
  lerc                       3.0           h9c3ff4c_0              conda-forge      
  libaec                     1.1.3         h59595ed_0              conda-forge      
  libasprintf                0.22.5        he8f35ee_3              conda-forge      
  libasprintf-devel          0.22.5        he8f35ee_3              conda-forge      
  libblas                    3.9.0         24_linux64_openblas     conda-forge      
  libbrotlicommon            1.0.9         h166bdaf_9              conda-forge      
  libbrotlidec               1.0.9         h166bdaf_9              conda-forge      
  libbrotlienc               1.0.9         h166bdaf_9              conda-forge      
  libcblas                   3.9.0         24_linux64_openblas     conda-forge      
  libclang                   13.0.1        default_h7634d5b_6      conda-forge      
  libcurl                    7.87.0        h6312ad2_0              conda-forge      
  libdeflate                 1.10          h7f98852_0              conda-forge      
  libdrm                     2.4.123       hb9d3cd8_0              conda-forge      
  libedit                    3.1.20191231  he28a2e2_2              conda-forge      
  libev                      4.33          hd590300_2              conda-forge      
  libevent                   2.1.10        h9b69904_4              conda-forge      
  libexpat                   2.6.3         h5888daf_0              conda-forge      
  libffi                     3.4.2         h7f98852_5              conda-forge      
  libgcc                     14.1.0        h77fa898_1              conda-forge      
  libgcc-ng                  14.1.0        h69a702a_1              conda-forge      
  libgettextpo               0.22.5        he02047a_3              conda-forge      
  libgettextpo-devel         0.22.5        he02047a_3              conda-forge      
  libgfortran                14.1.0        h69a702a_1              conda-forge      
  libgfortran-ng             14.1.0        h69a702a_1              conda-forge      
  libgfortran5               14.1.0        hc5f4f2c_1              conda-forge      
  libglib                    2.80.2        hf974151_0              conda-forge      
  libglu                     9.0.0         he1b5a44_1001           conda-forge      
  libgomp                    14.1.0        h77fa898_1              conda-forge      
  libiconv                   1.17          hd590300_2              conda-forge      
  libidn2                    2.3.7         hd590300_0              conda-forge      
  liblapack                  3.9.0         24_linux64_openblas     conda-forge      
  liblapacke                 3.9.0         24_linux64_openblas     conda-forge      
  libllvm13                  13.0.1        hf817b99_2              conda-forge      
  libnghttp2                 1.51.0        hdcd2b5c_0              conda-forge      
  libnsl                     2.0.1         hd590300_0              conda-forge      
  libogg                     1.3.5         h4ab18f5_0              conda-forge      
  libopenblas                0.3.27        pthreads_hac2b453_1     conda-forge      
  libopencv                  4.5.5         py37h780a5f5_10         conda-forge      
  libopus                    1.3.1         h7f98852_1              conda-forge      
  libpciaccess               0.18          hd590300_0              conda-forge      
  libpng                     1.6.43        h2797004_0              conda-forge      
  libpq                      14.5          h2baec63_5              conda-forge      
  libprotobuf                3.20.1        h6239696_4              conda-forge      
  libsodium                  1.0.18        h36c2ea0_1              conda-forge      
  libsqlite                  3.46.0        hde9e2c9_0              conda-forge      
  libssh2                    1.10.0        haa6b8db_3              conda-forge      
  libstdcxx                  14.1.0        hc0a3c3a_1              conda-forge      
  libstdcxx-ng               14.1.0        h4852527_1              conda-forge      
  libtasn1                   4.19.0        h166bdaf_0              conda-forge      
  libtiff                    4.4.0         h0fcbabc_0              conda-forge      
  libunistring               0.9.10        h7f98852_0              conda-forge      
  libuuid                    2.38.1        h0b41bf4_0              conda-forge      
  libva                      2.18.0        h0b41bf4_0              conda-forge      
  libvorbis                  1.3.7         h9c3ff4c_0              conda-forge      
  libvpx                     1.11.0        h9c3ff4c_3              conda-forge      
  libwebp-base               1.4.0         hd590300_0              conda-forge      
  libxcb                     1.13          h7f98852_1004           conda-forge      
  libxkbcommon               1.0.3         he3ba5ed_0              conda-forge      
  libxml2                    2.9.14        haae042b_4              conda-forge      
  libxslt                    1.1.33        h0ef7038_3              conda-forge      
  libzlib                    1.2.13        h4ab18f5_6              conda-forge      
  libzopfli                  1.0.3         h9c3ff4c_0              conda-forge      
  locket                     1.0.0         pyhd8ed1ab_0            conda-forge      
  lz4-c                      1.9.3         h9c3ff4c_1              conda-forge      
  markdown-it-py             2.2.0         pyhd8ed1ab_0            conda-forge      
  matplotlib-base            3.5.3         py37hf395dca_2          conda-forge      
  mdurl                      0.1.2         pyhd8ed1ab_0            conda-forge      
  munkres                    1.1.4         pyh9f0ad1d_0            conda-forge      
  mysql-common               8.0.32        h14678bc_0              conda-forge      
  mysql-libs                 8.0.32        h54cf53e_0              conda-forge      
  ncurses                    6.5           he02047a_1              conda-forge      
  ndx-pose                   0.1.1         pyhd8ed1ab_0            conda-forge      
  nettle                     3.9.1         h7ab15ed_0              conda-forge      
  networkx                   2.7           pyhd8ed1ab_0            conda-forge      
  nspr                       4.35          h27087fc_0              conda-forge      
  nss                        3.100         hca3bf56_0              conda-forge      
  numpy                      1.21.6        py37h976b520_0          conda-forge      
  openblas                   0.3.27        pthreads_h9eca1d5_1     conda-forge      
  opencv                     4.5.5         py37h89c1867_10         conda-forge      
  openh264                   2.3.1         hcb278e6_2              conda-forge      
  openjpeg                   2.5.0         h7d73246_1              conda-forge      
  openssl                    1.1.1w        hd590300_0              conda-forge      
  p11-kit                    0.24.1        hc5aa10d_0              conda-forge      
  packaging                  23.2          pyhd8ed1ab_0            conda-forge      
  pandas                     1.3.5         py37he8f5f7f_0          conda-forge      
  partd                      1.4.1         pyhd8ed1ab_0            conda-forge      
  patsy                      0.5.6         pyhd8ed1ab_0            conda-forge      
  pcre2                      10.43         hcad00b1_0              conda-forge      
  pillow                     9.2.0         py37h850a105_2          conda-forge      
  pip                        24.0          pyhd8ed1ab_0            conda-forge      
  pixman                     0.43.2        h59595ed_0              conda-forge      
  pkgutil-resolve-name       1.3.10        pyhd8ed1ab_1            conda-forge      
  protobuf                   3.20.1        py37hd23a5d3_0          conda-forge      
  psutil                     5.9.3         py37h540881e_0          conda-forge      
  pthread-stubs              0.4           hb9d3cd8_1002           conda-forge      
  py-opencv                  4.5.5         py37h25bab4e_10         conda-forge      
  pygments                   2.17.2        pyhd8ed1ab_0            conda-forge      
  pykalman                   0.9.7         pyhd8ed1ab_0            conda-forge      
  pynwb                      2.2.0         py37h89c1867_0          conda-forge      
  pyparsing                  3.1.4         pyhd8ed1ab_0            conda-forge      
  pyrsistent                 0.18.1        py37h540881e_1          conda-forge      
  pyside2                    5.13.2        py37h3927acf_8          conda-forge      
  python                     3.7.12        hb7a2778_100_cpython    conda-forge      
  python-dateutil            2.9.0         pyhd8ed1ab_0            conda-forge      
  python-rapidjson           1.9           py37hd23a5d3_0          conda-forge      
  python_abi                 3.7           4_cp37m                 conda-forge      
  pytz                       2024.2        pyhd8ed1ab_0            conda-forge      
  pywavelets                 1.3.0         py37hda87dfa_1          conda-forge      
  pyyaml                     6.0           py37h540881e_4          conda-forge      
  pyzmq                      24.0.1        py37h0c0c2a8_0          conda-forge      
  qt                         5.12.9        h1304e3e_6              conda-forge      
  qtpy                       2.4.1         pyhd8ed1ab_0            conda-forge      
  qudida                     0.0.4         pyhd8ed1ab_0            conda-forge      
  readline                   8.2           h8228510_1              conda-forge      
  rich                       13.8.1        pyhd8ed1ab_0            conda-forge      
  ruamel.yaml                0.17.21       py37h540881e_1          conda-forge      
  ruamel.yaml.clib           0.2.6         py37h540881e_1          conda-forge      
  scikit-image               0.19.2        py37he8f5f7f_0          conda-forge      
  scikit-learn               1.0           py37hf0f1638_1          conda-forge      
  scikit-video               1.1.11        pyh24bf2e0_0            conda-forge      
  scipy                      1.7.3         py37hf838250_2          anaconda         
  seaborn                    0.12.2        hd8ed1ab_0              conda-forge      
  seaborn-base               0.12.2        pyhd8ed1ab_0            conda-forge      
  setuptools                 59.8.0        py37h89c1867_1          conda-forge      
  six                        1.16.0        pyh6c4a22f_0            conda-forge      
  sleap                      1.4.1a3       py37_0                  sleap-build-linux
  snappy                     1.1.10        hdb0a2a9_1              conda-forge      
  sqlite                     3.46.0        h6d4b2fc_0              conda-forge      
  statsmodels                0.13.2        py37hda87dfa_0          conda-forge      
  svt-av1                    1.3.0         h27087fc_0              conda-forge      
  tensorflow                 2.7.0         py37hb93dfd8_3          sleap            
  tensorflow-hub             0.13.0        pyh56297ac_0            conda-forge      
  threadpoolctl              3.1.0         pyh8a188c0_0            conda-forge      
  tifffile                   2021.11.2     pyhd8ed1ab_0            conda-forge      
  tk                         8.6.13        noxft_h4845f30_101      conda-forge      
  toolz                      0.12.1        pyhd8ed1ab_0            conda-forge      
  typing-extensions          4.7.1         hd8ed1ab_0              conda-forge      
  typing_extensions          4.7.1         pyha770c72_0            conda-forge      
  unicodedata2               14.0.0        py37h540881e_1          conda-forge      
  wheel                      0.42.0        pyhd8ed1ab_0            conda-forge      
  x264                       1!164.3095    h166bdaf_2              conda-forge      
  x265                       3.5           h924138e_3              conda-forge      
  xorg-fixesproto            5.0           hb9d3cd8_1003           conda-forge      
  xorg-inputproto            2.3.2         hb9d3cd8_1003           conda-forge      
  xorg-kbproto               1.0.7         hb9d3cd8_1003           conda-forge      
  xorg-libice                1.1.1         hb9d3cd8_1              conda-forge      
  xorg-libsm                 1.2.4         he73a12e_1              conda-forge      
  xorg-libx11                1.8.4         h0b41bf4_0              conda-forge      
  xorg-libxau                1.0.11        hb9d3cd8_1              conda-forge      
  xorg-libxdmcp              1.1.5         hb9d3cd8_0              conda-forge      
  xorg-libxext               1.3.4         h0b41bf4_2              conda-forge      
  xorg-libxfixes             5.0.3         h7f98852_1004           conda-forge      
  xorg-libxi                 1.7.10        h7f98852_0              conda-forge      
  xorg-libxrender            0.9.10        h7f98852_1003           conda-forge      
  xorg-renderproto           0.11.1        hb9d3cd8_1003           conda-forge      
  xorg-xextproto             7.3.0         hb9d3cd8_1004           conda-forge      
  xorg-xproto                7.0.31        hb9d3cd8_1008           conda-forge      
  xz                         5.2.6         h166bdaf_0              conda-forge      
  yaml                       0.2.5         h7f98852_2              conda-forge      
  zeromq                     4.3.5         h59595ed_1              conda-forge      
  zfp                        0.5.5         h9c3ff4c_8              conda-forge      
  zipp                       3.15.0        pyhd8ed1ab_0            conda-forge      
  zlib                       1.2.13        h4ab18f5_6              conda-forge      
  zlib-ng                    2.0.7         h0b41bf4_0              conda-forge      
  zstd                       1.5.6         ha6fb4c9_0              conda-forge





      		
    

  





        


            

            

              
            

        

      


      

            
  

    
  
    
    

  

  



    












      

  
      



  

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            roomrys
  

      

      

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Mac (manual test)


Backwards compatibility

pip freeze




mamba list






Training/Inference via GUI





Training Dialog





sleap-label





Installation

pip freeze





mamba list






      		
    

  





        


            

            

              
            

        

      


      

            
  

    
  
    
    

  

  



    












      

  
          

  

    
  


  

      

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            roomrys
  

      

      

      commented


        Oct 2, 2024


      
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Windows (manual test)


Backwards compatibility

pip freeze




mamba list






Training/Inference via GUI





Training Dialog





sleap-label

(sleap_1.4.1a3) λ sleap-label
Traceback (most recent call last):
  File "C:\Users\TalmoLab\mambaforge\envs\sleap_1.4.1a3\Scripts\sleap-label-script.py", line 33, in <module>
    sys.exit(load_entry_point('sleap==1.4.1a3', 'console_scripts', 'sleap-label')())
  File "C:\Users\TalmoLab\mambaforge\envs\sleap_1.4.1a3\Scripts\sleap-label-script.py", line 25, in importlib_load_entry_point
    return next(matches).load()
  File "C:\Users\TalmoLab\mambaforge\envs\sleap_1.4.1a3\lib\site-packages\importlib_metadata\__init__.py", line 194, in load
    module = import_module(match.group('module'))
  File "C:\Users\TalmoLab\mambaforge\envs\sleap_1.4.1a3\lib\importlib\__init__.py", line 127, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 1006, in _gcd_import
  File "<frozen importlib._bootstrap>", line 983, in _find_and_load
  File "<frozen importlib._bootstrap>", line 953, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
  File "<frozen importlib._bootstrap>", line 1006, in _gcd_import
  File "<frozen importlib._bootstrap>", line 983, in _find_and_load
  File "<frozen importlib._bootstrap>", line 953, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
  File "<frozen importlib._bootstrap>", line 1006, in _gcd_import
  File "<frozen importlib._bootstrap>", line 983, in _find_and_load
  File "<frozen importlib._bootstrap>", line 967, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 677, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 728, in exec_module
  File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
  File "C:\Users\TalmoLab\mambaforge\envs\sleap_1.4.1a3\lib\site-packages\sleap\__init__.py", line 10, in <module>
    from sleap.io.dataset import Labels, load_file
  File "C:\Users\TalmoLab\mambaforge\envs\sleap_1.4.1a3\lib\site-packages\sleap\io\dataset.py", line 61, in <module>
    import h5py as h5
  File "C:\Users\TalmoLab\mambaforge\envs\sleap_1.4.1a3\lib\site-packages\h5py\__init__.py", line 33, in <module>
    from . import version
  File "C:\Users\TalmoLab\mambaforge\envs\sleap_1.4.1a3\lib\site-packages\h5py\version.py", line 15, in <module>
    from . import h5 as _h5
  File "h5py\h5.pyx", line 1, in init h5py.h5
ImportError: DLL load failed: The specified procedure could not be found.




Installation

λ mamba create -n sleap_1.4.1a3 -c conda-forge -c nvidia -c ./sleap-build-win -c sleap -c anaconda sleap=1.4.1a3

                  __    __    __    __
                 /  \  /  \  /  \  /  \
                /    \/    \/    \/    \
███████████████/  /██/  /██/  /██/  /████████████████████████
              /  / \   / \   / \   / \  \____
             /  /   \_/   \_/   \_/   \    o \__,
            / _/                       \_____/  `
            |/
        ███╗   ███╗ █████╗ ███╗   ███╗██████╗  █████╗
        ████╗ ████║██╔══██╗████╗ ████║██╔══██╗██╔══██╗
        ██╔████╔██║███████║██╔████╔██║██████╔╝███████║
        ██║╚██╔╝██║██╔══██║██║╚██╔╝██║██╔══██╗██╔══██║
        ██║ ╚═╝ ██║██║  ██║██║ ╚═╝ ██║██████╔╝██║  ██║
        ╚═╝     ╚═╝╚═╝  ╚═╝╚═╝     ╚═╝╚═════╝ ╚═╝  ╚═╝

        mamba (1.4.1) supported by @QuantStack

        GitHub:  https://github.com/mamba-org/mamba
        Twitter: https://twitter.com/QuantStack

█████████████████████████████████████████████████████████████


Looking for: ['sleap=1.4.1a3']

conda-forge/win-64                                          Using cache
conda-forge/noarch                                          Using cache
anaconda/win-64                                             Using cache
anaconda/noarch                                             Using cache
file://C:/Users/TalmoLab/Downloads/sleap-build-w.. 977.0 B @   2.2MB/s  0.0s
file://C:/Users/TalmoLab/Downloads/sleap-build-w..  96.0 B @ 227.5kB/s  0.0s
sleap/win-64                                                  No change
sleap/noarch                                                  No change
nvidia/win-64                                                 No change
nvidia/noarch                                                 No change
warning  libmamba Extracted package cache 'C:\Users\TalmoLab\mambaforge\pkgs\sleap-1.4.1a3-py37_0' has invalid size
warning  libmamba Extracted package cache 'C:\Users\TalmoLab\mambaforge\pkgs\sleap-1.4.1a3-py37_0' has invalid SHA-256 checksum
Transaction

  Prefix: C:\Users\TalmoLab\mambaforge\envs\sleap_1.4.1a3

  Updating specs:

   - sleap=1.4.1a3


  Package                                 Version  Build                   Channel                                                  Size
------------------------------------------------------------------------------------------------------------------------------------------
  Install:
------------------------------------------------------------------------------------------------------------------------------------------

  + albumentations                          1.3.1  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + aom                                     3.7.1  h63175ca_0              conda-forge/win-64                                     Cached
  + attrs                                  21.4.0  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + brotli                                  1.1.0  h2466b09_2              conda-forge/win-64                                     Cached
  + brotli-bin                              1.1.0  h2466b09_2              conda-forge/win-64                                     Cached
  + bzip2                                   1.0.8  h2466b09_7              conda-forge/win-64                                     Cached
  + ca-certificates                     2024.8.30  h56e8100_0              conda-forge/win-64                                     Cached
  + cached-property                         1.5.2  hd8ed1ab_1              conda-forge/noarch                                     Cached
  + cached_property                         1.5.2  pyha770c72_1            conda-forge/noarch                                     Cached
  + cattrs                                  1.1.1  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + certifi                             2024.8.30  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + cloudpickle                             2.2.1  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + cuda-nvcc                             11.3.58  hb8d16a4_0              nvidia/win-64                                          Cached
  + cudatoolkit                            11.3.1  hf2f0253_13             conda-forge/win-64                                     Cached
  + cudnn                                8.2.1.32  h754d62a_0              conda-forge/win-64                                     Cached
  + cycler                                 0.11.0  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + cytoolz                                0.12.0  py37hcc03f2d_0          conda-forge/win-64                                     Cached
  + dask-core                            2022.2.0  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + dav1d                                   1.2.1  hcfcfb64_0              conda-forge/win-64                                     Cached
  + expat                                   2.6.3  he0c23c2_0              conda-forge/win-64                                     Cached
  + ffmpeg                                  6.1.0  gpl_h0859920_103        conda-forge/win-64                                     Cached
  + font-ttf-dejavu-sans-mono                2.37  hab24e00_0              conda-forge/noarch                                     Cached
  + font-ttf-inconsolata                    3.000  h77eed37_0              conda-forge/noarch                                     Cached
  + font-ttf-source-code-pro                2.038  h77eed37_0              conda-forge/noarch                                     Cached
  + font-ttf-ubuntu                          0.83  h77eed37_3              conda-forge/noarch                                     Cached
  + fontconfig                             2.14.2  hbde0cde_0              conda-forge/win-64                                     Cached
  + fonts-conda-ecosystem                       1  0                       conda-forge/noarch                                     Cached
  + fonts-conda-forge                           1  0                       conda-forge/noarch                                     Cached
  + fonttools                              4.38.0  py37h51bd9d9_0          conda-forge/win-64                                     Cached
  + freeglut                                3.2.2  he0c23c2_3              conda-forge/win-64                                     Cached
  + freetype                               2.12.1  hdaf720e_2              conda-forge/win-64                                     Cached
  + fsspec                               2023.1.0  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + h5py                                    3.7.0  nompi_py37h24adfc3_101  conda-forge/win-64                                     Cached
  + hdf5                                   1.12.2  nompi_h2a0e4a3_101      conda-forge/win-64                                     Cached
  + hdmf                                    3.6.1  pyh1a96a4e_0            conda-forge/noarch                                     Cached
  + icu                                      69.1  h0e60522_0              conda-forge/win-64                                     Cached
  + imagecodecs-lite                    2019.12.3  py37h0b711f8_5          conda-forge/win-64                                     Cached
  + imageio                                2.35.1  pyh12aca89_0            conda-forge/noarch                                     Cached
  + imageio-ffmpeg                          0.5.1  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + importlib-metadata                     4.11.4  py37h03978a9_0          conda-forge/win-64                                     Cached
  + importlib_resources                     6.0.0  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + intel-openmp                         2024.2.1  h57928b3_1083           conda-forge/win-64                                     Cached
  + jasper                                 2.0.33  hc2e4405_1              conda-forge/win-64                                     Cached
  + joblib                                  1.3.2  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + jpeg                                       9e  hcfcfb64_3              conda-forge/win-64                                     Cached
  + jsmin                                   3.0.1  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + jsonpickle                                1.2  py_0                    conda-forge/noarch                                     Cached
  + jsonschema                             4.17.3  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + kiwisolver                              1.4.4  py37h8c56517_0          conda-forge/win-64                                     Cached
  + krb5                                   1.20.1  h6609f42_0              conda-forge/win-64                                     Cached
  + lcms2                                    2.14  h90d422f_0              conda-forge/win-64                                     Cached
  + lerc                                    4.0.0  h63175ca_0              conda-forge/win-64                                     Cached
  + libaec                                  1.1.3  h63175ca_0              conda-forge/win-64                                     Cached
  + libblas                                 3.9.0  24_win64_mkl            conda-forge/win-64                                     Cached
  + libbrotlicommon                         1.1.0  h2466b09_2              conda-forge/win-64                                     Cached
  + libbrotlidec                            1.1.0  h2466b09_2              conda-forge/win-64                                     Cached
  + libbrotlienc                            1.1.0  h2466b09_2              conda-forge/win-64                                     Cached
  + libcblas                                3.9.0  24_win64_mkl            conda-forge/win-64                                     Cached
  + libclang                               13.0.1  default_h21c55ae_8      conda-forge/win-64                                     Cached
  + libcurl                                 8.1.2  h68f0423_0              conda-forge/win-64                                     Cached
  + libdeflate                               1.14  hcfcfb64_0              conda-forge/win-64                                     Cached
  + libexpat                                2.6.3  he0c23c2_0              conda-forge/win-64                                     Cached
  + libhwloc                               2.11.1  default_h8125262_1000   conda-forge/win-64                                     Cached
  + libiconv                                 1.17  hcfcfb64_2              conda-forge/win-64                                     Cached
  + liblapack                               3.9.0  24_win64_mkl            conda-forge/win-64                                     Cached
  + liblapacke                              3.9.0  24_win64_mkl            conda-forge/win-64                                     Cached
  + libopencv                               4.5.5  py37h542666b_10         conda-forge/win-64                                     Cached
  + libopus                                 1.3.1  h8ffe710_1              conda-forge/win-64                                     Cached
  + libpng                                 1.6.44  h3ca93ac_0              conda-forge/win-64                                     Cached
  + libprotobuf                            3.20.3  h12be248_0              conda-forge/win-64                                     Cached
  + libsodium                              1.0.18  h8d14728_1              conda-forge/win-64                                     Cached
  + libsqlite                              3.46.1  h2466b09_0              conda-forge/win-64                                     Cached
  + libssh2                                1.10.0  h680486a_3              conda-forge/win-64                                     Cached
  + libtiff                                 4.4.0  hc4f729c_5              conda-forge/win-64                                     Cached
  + libwebp-base                            1.4.0  hcfcfb64_0              conda-forge/win-64                                     Cached
  + libxcb                                   1.13  hcd874cb_1004           conda-forge/win-64                                     Cached
  + libxml2                                2.12.7  h0f24e4e_4              conda-forge/win-64                                     Cached
  + libxslt                                1.1.39  h3df6e99_0              conda-forge/win-64                                     Cached
  + libzlib                                 1.3.1  h2466b09_1              conda-forge/win-64                                     Cached
  + locket                                  1.0.0  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + m2w64-gcc-libgfortran                   5.3.0  6                       conda-forge/win-64                                     Cached
  + m2w64-gcc-libs                          5.3.0  7                       conda-forge/win-64                                     Cached
  + m2w64-gcc-libs-core                     5.3.0  7                       conda-forge/win-64                                     Cached
  + m2w64-gmp                               6.1.0  2                       conda-forge/win-64                                     Cached
  + m2w64-libwinpthread-git    5.0.0.4634.697f757  2                       conda-forge/win-64                                     Cached
  + markdown-it-py                          2.2.0  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + matplotlib-base                         3.5.3  py37hbaab90a_2          conda-forge/win-64                                     Cached
  + mdurl                                   0.1.2  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + mkl                                  2024.1.0  h66d3029_694            conda-forge/win-64                                     Cached
  + msys2-conda-epoch                    20160418  1                       conda-forge/win-64                                     Cached
  + munkres                                 1.1.4  pyh9f0ad1d_0            conda-forge/noarch                                     Cached
  + ndx-pose                                0.1.1  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + networkx                                  2.7  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + numpy                                  1.21.6  py37h2830a78_0          conda-forge/win-64                                     Cached
  + opencv                                  4.5.5  py37h03978a9_10         conda-forge/win-64                                     Cached
  + openh264                                2.4.0  h63175ca_0              conda-forge/win-64                                     Cached
  + openjpeg                                2.5.0  hc9384bd_1              conda-forge/win-64                                     Cached
  + openssl                                1.1.1w  hcfcfb64_0              conda-forge/win-64                                     Cached
  + packaging                                23.2  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + pandas                                  1.3.5  py37h9386db6_0          conda-forge/win-64                                     Cached
  + partd                                   1.4.1  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + patsy                                   0.5.6  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + pillow                                  9.2.0  py37h42a8222_2          conda-forge/win-64                                     Cached
  + pip                                      24.0  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + pkgutil-resolve-name                   1.3.10  pyhd8ed1ab_1            conda-forge/noarch                                     Cached
  + protobuf                               3.20.3  py37hd77b12b_0          anaconda/win-64                                        Cached
  + psutil                                  5.9.3  py37h51bd9d9_0          conda-forge/win-64                                     Cached
  + pthread-stubs                             0.4  hcd874cb_1001           conda-forge/win-64                                     Cached
  + pthreads-win32                          2.9.1  hfa6e2cd_3              conda-forge/win-64                                     Cached
  + py-opencv                               4.5.5  py37h90c5f73_10         conda-forge/win-64                                     Cached
  + pygments                               2.17.2  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + pykalman                                0.9.7  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + pynwb                                   2.2.0  py37h03978a9_0          conda-forge/win-64                                     Cached
  + pyparsing                               3.1.4  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + pyrsistent                             0.18.1  py37hcc03f2d_1          conda-forge/win-64                                     Cached
  + pyside2                                5.13.2  py37h760f651_8          conda-forge/win-64                                     Cached
  + python                                 3.7.12  h7840368_100_cpython    conda-forge/win-64                                     Cached
  + python-dateutil                         2.9.0  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + python-rapidjson                          1.9  py37h7f67f24_0          conda-forge/win-64                                     Cached
  + python_abi                                3.7  4_cp37m                 conda-forge/win-64                                     Cached
  + pytz                                   2024.2  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + pywavelets                              1.3.0  py37h3a130e4_1          conda-forge/win-64                                     Cached
  + pyyaml                                    6.0  py37hcc03f2d_4          conda-forge/win-64                                     Cached
  + pyzmq                                  24.0.1  py37h7347f05_0          conda-forge/win-64                                     Cached
  + qt                                     5.12.9  h556501e_6              conda-forge/win-64                                     Cached
  + qtpy                                    2.4.1  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + qudida                                  0.0.4  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + rich                                   13.8.1  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + ruamel.yaml                           0.17.21  py37hcc03f2d_1          conda-forge/win-64                                     Cached
  + ruamel.yaml.clib                        0.2.6  py37hcc03f2d_1          conda-forge/win-64                                     Cached
  + scikit-image                           0.19.2  py37h9386db6_0          conda-forge/win-64                                     Cached
  + scikit-learn                              1.0  py37ha78be43_1          conda-forge/win-64                                     Cached
  + scikit-video                           1.1.11  pyh24bf2e0_0            conda-forge/noarch                                     Cached
  + scipy                                   1.7.3  py37hb6553fb_0          conda-forge/win-64                                     Cached
  + seaborn                                0.12.2  hd8ed1ab_0              conda-forge/noarch                                     Cached
  + seaborn-base                           0.12.2  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + setuptools                             59.8.0  py37h03978a9_1          conda-forge/win-64                                     Cached
  + six                                    1.16.0  pyh6c4a22f_0            conda-forge/noarch                                     Cached
  + sleap                                 1.4.1a3  py37_0                  C:/Users/TalmoLab/Downloads/sleap-build-win/win-64        3MB
  + sqlite                                 3.46.1  h2466b09_0              conda-forge/win-64                                     Cached
  + statsmodels                            0.13.2  py37h3a130e4_0          conda-forge/win-64                                     Cached
  + svt-av1                                 1.7.0  h63175ca_0              conda-forge/win-64                                     Cached
  + tbb                                 2021.13.0  hc790b64_0              conda-forge/win-64                                     Cached
  + tensorflow                              2.7.0  py37h5685391_3          sleap/win-64                                           Cached
  + tensorflow-hub                         0.12.0  pyhca92ed8_0            conda-forge/noarch                                     Cached
  + threadpoolctl                           3.1.0  pyh8a188c0_0            conda-forge/noarch                                     Cached
  + tifffile                             2020.6.3  py_0                    conda-forge/noarch                                     Cached
  + tk                                     8.6.13  h5226925_1              conda-forge/win-64                                     Cached
  + toolz                                  0.12.1  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + typing-extensions                       4.7.1  hd8ed1ab_0              conda-forge/noarch                                     Cached
  + typing_extensions                       4.7.1  pyha770c72_0            conda-forge/noarch                                     Cached
  + ucrt                             10.0.22621.0  h57928b3_0              conda-forge/win-64                                     Cached
  + unicodedata2                           14.0.0  py37hcc03f2d_1          conda-forge/win-64                                     Cached
  + vc                                       14.3  h8a93ad2_21             conda-forge/win-64                                     Cached
  + vc14_runtime                      14.40.33810  ha82c5b3_21             conda-forge/win-64                                     Cached
  + vs2015_runtime                    14.40.33810  h3bf8584_21             conda-forge/win-64                                     Cached
  + wheel                                  0.42.0  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + x264                               1!164.3095  h8ffe710_2              conda-forge/win-64                                     Cached
  + x265                                      3.5  h2d74725_3              conda-forge/win-64                                     Cached
  + xorg-libxau                            1.0.11  hcd874cb_0              conda-forge/win-64                                     Cached
  + xorg-libxdmcp                           1.1.3  hcd874cb_0              conda-forge/win-64                                     Cached
  + xz                                      5.2.6  h8d14728_0              conda-forge/win-64                                     Cached
  + yaml                                    0.2.5  h8ffe710_2              conda-forge/win-64                                     Cached
  + zeromq                                  4.3.4  h0e60522_1              conda-forge/win-64                                     Cached
  + zipp                                   3.15.0  pyhd8ed1ab_0            conda-forge/noarch                                     Cached
  + zstd                                    1.5.6  h0ea2cb4_0              conda-forge/win-64                                     Cached

  Summary:

  Install: 166 packages

  Total download: 3MB


pip freeze

(sleap_1.4.1a3) λ pip freeze
absl-py==1.0.0
albumentations @ file:///home/conda/feedstock_root/build_artifacts/albumentations_1686576355052/work
astunparse==1.6.3
attrs @ file:///home/conda/feedstock_root/build_artifacts/attrs_1640799537051/work
backports.zoneinfo==0.2.1
cached-property @ file:///home/conda/feedstock_root/build_artifacts/cached_property_1615209429212/work
cachetools==4.2.4
cattrs @ file:///home/conda/feedstock_root/build_artifacts/cattrs_1604136207372/work
certifi @ file:///home/conda/feedstock_root/build_artifacts/certifi_1725278078093/work/certifi
charset-normalizer==2.0.9
cloudpickle @ file:///home/conda/feedstock_root/build_artifacts/cloudpickle_1674202310934/work
cycler @ file:///home/conda/feedstock_root/build_artifacts/cycler_1635519461629/work
cytoolz @ file:///D:/bld/cytoolz_1657553564801/work
dask @ file:///home/conda/feedstock_root/build_artifacts/dask-core_1644602974678/work
efficientnet==1.0.0
flatbuffers==2.0
fonttools @ file:///D:/bld/fonttools_1666390069478/work
fsspec @ file:///home/conda/feedstock_root/build_artifacts/fsspec_1674184942191/work
gast==0.4.0
google-auth==2.3.3
google-auth-oauthlib==0.4.6
google-pasta==0.2.0
grpcio==1.43.0
h5py==3.1.0
hdmf @ file:///home/conda/feedstock_root/build_artifacts/hdmf_1684510272253/work
idna==3.3
image-classifiers==1.0.0
imagecodecs-lite @ file:///D:/bld/imagecodecs-lite_1665171421509/work
imageio @ file:///home/conda/feedstock_root/build_artifacts/imageio_1724069053555/work
imageio-ffmpeg @ file:///home/conda/feedstock_root/build_artifacts/imageio-ffmpeg_1717461632069/work
imgstore==0.2.9
importlib-metadata==4.10.0
importlib-resources @ file:///home/conda/feedstock_root/build_artifacts/importlib_resources_1688813467203/work
joblib @ file:///home/conda/feedstock_root/build_artifacts/joblib_1691577114857/work
jsmin @ file:///home/conda/feedstock_root/build_artifacts/jsmin_1642532731678/work
jsonpickle==1.2
jsonschema @ file:///home/conda/feedstock_root/build_artifacts/jsonschema-meta_1669810440410/work
keras==2.7.0
Keras-Applications==1.0.8
Keras-Preprocessing==1.1.2
kiwisolver @ file:///D:/bld/kiwisolver_1657953189205/work
libclang==12.0.0
locket @ file:///home/conda/feedstock_root/build_artifacts/locket_1650660393415/work
Markdown==3.3.6
markdown-it-py @ file:///home/conda/feedstock_root/build_artifacts/markdown-it-py_1677100944732/work
matplotlib @ file:///D:/bld/matplotlib-suite_1661439973878/work
mdurl @ file:///home/conda/feedstock_root/build_artifacts/mdurl_1704317613764/work
munkres==1.1.4
ndx-pose @ file:///home/conda/feedstock_root/build_artifacts/ndx-pose_1706810229855/work
networkx @ file:///home/conda/feedstock_root/build_artifacts/networkx_1646092782768/work
nixio==1.5.3
numpy==1.19.5
oauthlib==3.1.1
opencv-python==4.5.5
opencv-python-headless==4.2.0.34
opt-einsum==3.3.0
packaging==21.3
pandas @ file:///D:/bld/pandas_1639398349358/work
partd @ file:///home/conda/feedstock_root/build_artifacts/partd_1695667515973/work
patsy @ file:///home/conda/feedstock_root/build_artifacts/patsy_1704469236901/work
Pillow @ file:///D:/bld/pillow_1660386017560/work
pkgutil_resolve_name @ file:///home/conda/feedstock_root/build_artifacts/pkgutil-resolve-name_1694617248815/work
protobuf==3.19.1
psutil @ file:///D:/bld/psutil_1666155596250/work
pyasn1==0.4.8
pyasn1-modules==0.2.8
Pygments @ file:///home/conda/feedstock_root/build_artifacts/pygments_1700607939962/work
pykalman @ file:///home/conda/feedstock_root/build_artifacts/pykalman_1711547707628/work
pynwb @ file:///D:/bld/pynwb_1666675233939/work
pyparsing==3.0.6
pyrsistent @ file:///D:/bld/pyrsistent_1649013563648/work
python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1709299778482/work
python-rapidjson @ file:///D:/bld/python-rapidjson_1666000124084/work
pytz @ file:///home/conda/feedstock_root/build_artifacts/pytz_1726055524169/work
PyWavelets @ file:///D:/bld/pywavelets_1649616556601/work
PyYAML @ file:///D:/bld/pyyaml_1648757357341/work
pyzmq @ file:///D:/bld/pyzmq_1663830622471/work
qimage2ndarray==1.10.0
QtPy @ file:///home/conda/feedstock_root/build_artifacts/qtpy_1698112029416/work
qudida @ file:///home/conda/feedstock_root/build_artifacts/qudida_1651101164121/work
requests==2.26.0
requests-oauthlib==1.3.0
rich @ file:///home/conda/feedstock_root/build_artifacts/rich_1726066019428/work/dist
rsa==4.8
ruamel.yaml @ file:///D:/bld/ruamel.yaml_1649033375933/work
ruamel.yaml.clib @ file:///D:/bld/ruamel.yaml.clib_1649013254928/work
scikit-image @ file:///D:/bld/scikit-image_1645196912385/work
scikit-learn @ file:///D:/bld/scikit-learn_1632611530541/work
scikit-video==1.1.11
scipy @ file:///C:/bld/scipy_1637806996411/work
seaborn @ file:///home/conda/feedstock_root/build_artifacts/seaborn-split_1672497695270/work
segmentation-models==1.0.1
setuptools-scm==6.3.2
six @ file:///home/conda/feedstock_root/build_artifacts/six_1620240208055/work
sleap==1.4.1a3
statsmodels @ file:///D:/bld/statsmodels_1654787262041/work
tensorboard==2.7.0
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.0
tensorflow==2.7.0
tensorflow-estimator==2.7.0
tensorflow-hub @ file:///home/conda/feedstock_root/build_artifacts/tensorflow-hub_1618768305670/work/wheel_dir/tensorflow_hub-0.12.0-py2.py3-none-any.whl
tensorflow-io-gcs-filesystem==0.23.1
termcolor==1.1.0
threadpoolctl @ file:///home/conda/feedstock_root/build_artifacts/threadpoolctl_1643647933166/work
tifffile @ file:///home/conda/feedstock_root/build_artifacts/tifffile_1591280222285/work
tomli==2.0.0
toolz @ file:///home/conda/feedstock_root/build_artifacts/toolz_1706112571092/work
typing_extensions==4.0.1
tzdata==2024.2
tzlocal==5.1
unicodedata2 @ file:///D:/bld/unicodedata2_1649112131705/work
urllib3==1.26.7
Werkzeug==2.0.2
wrapt==1.13.3
zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1677313463193/work




mamba list

(sleap_1.4.1a3) λ mamba list
# packages in environment at C:\Users\TalmoLab\mambaforge\envs\sleap_1.4.1a3:
#
# Name                    Version                   Build  Channel
absl-py                   1.0.0                    pypi_0    pypi
albumentations            1.3.1              pyhd8ed1ab_0    conda-forge
aom                       3.7.1                h63175ca_0    conda-forge
astunparse                1.6.3                    pypi_0    pypi
attrs                     21.4.0             pyhd8ed1ab_0    conda-forge
backports-zoneinfo        0.2.1                    pypi_0    pypi
brotli                    1.1.0                h2466b09_2    conda-forge
brotli-bin                1.1.0                h2466b09_2    conda-forge
bzip2                     1.0.8                h2466b09_7    conda-forge
ca-certificates           2024.8.30            h56e8100_0    conda-forge
cached-property           1.5.2                hd8ed1ab_1    conda-forge
cached_property           1.5.2              pyha770c72_1    conda-forge
cachetools                4.2.4                    pypi_0    pypi
cattrs                    1.1.1              pyhd8ed1ab_0    conda-forge
certifi                   2024.8.30          pyhd8ed1ab_0    conda-forge
charset-normalizer        2.0.9                    pypi_0    pypi
cloudpickle               2.2.1              pyhd8ed1ab_0    conda-forge
cuda-nvcc                 11.3.58              hb8d16a4_0    nvidia
cudatoolkit               11.3.1              hf2f0253_13    conda-forge
cudnn                     8.2.1.32             h754d62a_0    conda-forge
cycler                    0.11.0             pyhd8ed1ab_0    conda-forge
cytoolz                   0.12.0           py37hcc03f2d_0    conda-forge
dask-core                 2022.2.0           pyhd8ed1ab_0    conda-forge
dav1d                     1.2.1                hcfcfb64_0    conda-forge
efficientnet              1.0.0                    pypi_0    pypi
expat                     2.6.3                he0c23c2_0    conda-forge
ffmpeg                    6.1.0           gpl_h0859920_103    conda-forge
flatbuffers               2.0                      pypi_0    pypi
font-ttf-dejavu-sans-mono 2.37                 hab24e00_0    conda-forge
font-ttf-inconsolata      3.000                h77eed37_0    conda-forge
font-ttf-source-code-pro  2.038                h77eed37_0    conda-forge
font-ttf-ubuntu           0.83                 h77eed37_3    conda-forge
fontconfig                2.14.2               hbde0cde_0    conda-forge
fonts-conda-ecosystem     1                             0    conda-forge
fonts-conda-forge         1                             0    conda-forge
fonttools                 4.38.0           py37h51bd9d9_0    conda-forge
freeglut                  3.2.2                he0c23c2_3    conda-forge
freetype                  2.12.1               hdaf720e_2    conda-forge
fsspec                    2023.1.0           pyhd8ed1ab_0    conda-forge
gast                      0.4.0                    pypi_0    pypi
google-auth               2.3.3                    pypi_0    pypi
google-auth-oauthlib      0.4.6                    pypi_0    pypi
google-pasta              0.2.0                    pypi_0    pypi
grpcio                    1.43.0                   pypi_0    pypi
h5py                      3.1.0                    pypi_0    pypi
hdf5                      1.12.2          nompi_h2a0e4a3_101    conda-forge
hdmf                      3.6.1                    pypi_0    pypi
icu                       69.1                 h0e60522_0    conda-forge
idna                      3.3                      pypi_0    pypi
image-classifiers         1.0.0                    pypi_0    pypi
imagecodecs-lite          2019.12.3        py37h0b711f8_5    conda-forge
imageio                   2.35.1             pyh12aca89_0    conda-forge
imageio-ffmpeg            0.5.1              pyhd8ed1ab_0    conda-forge
imgstore                  0.2.9                    pypi_0    pypi
importlib-metadata        4.2.0                    pypi_0    pypi
importlib_resources       6.0.0              pyhd8ed1ab_0    conda-forge
intel-openmp              2024.2.1          h57928b3_1083    conda-forge
jasper                    2.0.33               hc2e4405_1    conda-forge
joblib                    1.3.2              pyhd8ed1ab_0    conda-forge
jpeg                      9e                   hcfcfb64_3    conda-forge
jsmin                     3.0.1              pyhd8ed1ab_0    conda-forge
jsonpickle                1.2                        py_0    conda-forge
jsonschema                4.17.3             pyhd8ed1ab_0    conda-forge
keras                     2.7.0                    pypi_0    pypi
keras-applications        1.0.8                    pypi_0    pypi
keras-preprocessing       1.1.2                    pypi_0    pypi
kiwisolver                1.4.4            py37h8c56517_0    conda-forge
krb5                      1.20.1               h6609f42_0    conda-forge
lcms2                     2.14                 h90d422f_0    conda-forge
lerc                      4.0.0                h63175ca_0    conda-forge
libaec                    1.1.3                h63175ca_0    conda-forge
libblas                   3.9.0              24_win64_mkl    conda-forge
libbrotlicommon           1.1.0                h2466b09_2    conda-forge
libbrotlidec              1.1.0                h2466b09_2    conda-forge
libbrotlienc              1.1.0                h2466b09_2    conda-forge
libcblas                  3.9.0              24_win64_mkl    conda-forge
libclang                  12.0.0                   pypi_0    pypi
libcurl                   8.1.2                h68f0423_0    conda-forge
libdeflate                1.14                 hcfcfb64_0    conda-forge
libexpat                  2.6.3                he0c23c2_0    conda-forge
libhwloc                  2.11.1          default_h8125262_1000    conda-forge
libiconv                  1.17                 hcfcfb64_2    conda-forge
liblapack                 3.9.0              24_win64_mkl    conda-forge
liblapacke                3.9.0              24_win64_mkl    conda-forge
libopencv                 4.5.5           py37h542666b_10    conda-forge
libopus                   1.3.1                h8ffe710_1    conda-forge
libpng                    1.6.44               h3ca93ac_0    conda-forge
libprotobuf               3.20.3               h12be248_0    conda-forge
libsodium                 1.0.18               h8d14728_1    conda-forge
libsqlite                 3.46.1               h2466b09_0    conda-forge
libssh2                   1.10.0               h680486a_3    conda-forge
libtiff                   4.4.0                hc4f729c_5    conda-forge
libwebp-base              1.4.0                hcfcfb64_0    conda-forge
libxcb                    1.13              hcd874cb_1004    conda-forge
libxml2                   2.12.7               h0f24e4e_4    conda-forge
libxslt                   1.1.39               h3df6e99_0    conda-forge
libzlib                   1.3.1                h2466b09_1    conda-forge
locket                    1.0.0              pyhd8ed1ab_0    conda-forge
m2w64-gcc-libgfortran     5.3.0                         6    conda-forge
m2w64-gcc-libs            5.3.0                         7    conda-forge
m2w64-gcc-libs-core       5.3.0                         7    conda-forge
m2w64-gmp                 6.1.0                         2    conda-forge
m2w64-libwinpthread-git   5.0.0.4634.697f757               2    conda-forge
markdown                  3.3.6                    pypi_0    pypi
markdown-it-py            2.2.0              pyhd8ed1ab_0    conda-forge
matplotlib-base           3.5.3            py37hbaab90a_2    conda-forge
mdurl                     0.1.2              pyhd8ed1ab_0    conda-forge
mkl                       2024.1.0           h66d3029_694    conda-forge
msys2-conda-epoch         20160418                      1    conda-forge
munkres                   1.1.4              pyh9f0ad1d_0    conda-forge
ndx-pose                  0.1.1              pyhd8ed1ab_0    conda-forge
networkx                  2.7                pyhd8ed1ab_0    conda-forge
nixio                     1.5.3                    pypi_0    pypi
numpy                     1.19.5                   pypi_0    pypi
oauthlib                  3.1.1                    pypi_0    pypi
opencv                    4.5.5           py37h03978a9_10    conda-forge
opencv-python-headless    4.2.0.34                 pypi_0    pypi
openh264                  2.4.0                h63175ca_0    conda-forge
openjpeg                  2.5.0                hc9384bd_1    conda-forge
openssl                   1.1.1w               hcfcfb64_0    conda-forge
opt-einsum                3.3.0                    pypi_0    pypi
packaging                 21.3                     pypi_0    pypi
pandas                    1.3.5            py37h9386db6_0    conda-forge
partd                     1.4.1              pyhd8ed1ab_0    conda-forge
patsy                     0.5.6              pyhd8ed1ab_0    conda-forge
pillow                    9.2.0            py37h42a8222_2    conda-forge
pip                       24.0               pyhd8ed1ab_0    conda-forge
pkgutil-resolve-name      1.3.10             pyhd8ed1ab_1    conda-forge
protobuf                  3.19.1                   pypi_0    pypi
psutil                    5.9.3            py37h51bd9d9_0    conda-forge
pthread-stubs             0.4               hcd874cb_1001    conda-forge
pthreads-win32            2.9.1                hfa6e2cd_3    conda-forge
py-opencv                 4.5.5           py37h90c5f73_10    conda-forge
pyasn1                    0.4.8                    pypi_0    pypi
pyasn1-modules            0.2.8                    pypi_0    pypi
pygments                  2.17.2             pyhd8ed1ab_0    conda-forge
pykalman                  0.9.7              pyhd8ed1ab_0    conda-forge
pynwb                     2.3.3                    pypi_0    pypi
pyparsing                 3.0.6                    pypi_0    pypi
pyrsistent                0.18.1           py37hcc03f2d_1    conda-forge
pyside2                   5.13.2           py37h760f651_8    conda-forge
python                    3.7.12          h7840368_100_cpython    conda-forge
python-dateutil           2.9.0              pyhd8ed1ab_0    conda-forge
python-rapidjson          1.9              py37h7f67f24_0    conda-forge
python_abi                3.7                     4_cp37m    conda-forge
pytz                      2024.2             pyhd8ed1ab_0    conda-forge
pywavelets                1.3.0            py37h3a130e4_1    conda-forge
pyyaml                    6.0              py37hcc03f2d_4    conda-forge
pyzmq                     24.0.1           py37h7347f05_0    conda-forge
qimage2ndarray            1.10.0                   pypi_0    pypi
qt                        5.12.9               h556501e_6    conda-forge
qtpy                      2.4.1              pyhd8ed1ab_0    conda-forge
qudida                    0.0.4              pyhd8ed1ab_0    conda-forge
requests                  2.26.0                   pypi_0    pypi
requests-oauthlib         1.3.0                    pypi_0    pypi
rich                      13.8.1             pyhd8ed1ab_0    conda-forge
ruamel.yaml               0.17.21          py37hcc03f2d_1    conda-forge
ruamel.yaml.clib          0.2.6            py37hcc03f2d_1    conda-forge
scikit-image              0.19.2           py37h9386db6_0    conda-forge
scikit-learn              1.0              py37ha78be43_1    conda-forge
scikit-video              1.1.11             pyh24bf2e0_0    conda-forge
scipy                     1.7.3            py37hb6553fb_0    conda-forge
seaborn                   0.12.2               hd8ed1ab_0    conda-forge
seaborn-base              0.12.2             pyhd8ed1ab_0    conda-forge
segmentation-models       1.0.1                    pypi_0    pypi
setuptools                59.8.0           py37h03978a9_1    conda-forge
setuptools-scm            6.3.2                    pypi_0    pypi
six                       1.16.0             pyh6c4a22f_0    conda-forge
sleap                     1.4.1a3                  pypi_0    pypi
sqlite                    3.46.1               h2466b09_0    conda-forge
statsmodels               0.13.2           py37h3a130e4_0    conda-forge
svt-av1                   1.7.0                h63175ca_0    conda-forge
tbb                       2021.13.0            hc790b64_0    conda-forge
tensorboard               2.7.0                    pypi_0    pypi
tensorboard-data-server   0.6.1                    pypi_0    pypi
tensorboard-plugin-wit    1.8.0                    pypi_0    pypi
tensorflow                2.7.0                    pypi_0    pypi
tensorflow-estimator      2.7.0                    pypi_0    pypi
tensorflow-hub            0.12.0             pyhca92ed8_0    conda-forge
tensorflow-io-gcs-filesystem 0.23.1                   pypi_0    pypi
termcolor                 1.1.0                    pypi_0    pypi
threadpoolctl             3.1.0              pyh8a188c0_0    conda-forge
tifffile                  2020.6.3                   py_0    conda-forge
tk                        8.6.13               h5226925_1    conda-forge
tomli                     2.0.0                    pypi_0    pypi
toolz                     0.12.1             pyhd8ed1ab_0    conda-forge
typing-extensions         4.0.1                    pypi_0    pypi
typing_extensions         4.7.1              pyha770c72_0    conda-forge
tzdata                    2024.2                   pypi_0    pypi
tzlocal                   5.1                      pypi_0    pypi
ucrt                      10.0.22621.0         h57928b3_0    conda-forge
unicodedata2              14.0.0           py37hcc03f2d_1    conda-forge
urllib3                   1.26.7                   pypi_0    pypi
vc                        14.3                h8a93ad2_21    conda-forge
vc14_runtime              14.40.33810         ha82c5b3_21    conda-forge
vs2015_runtime            14.40.33810         h3bf8584_21    conda-forge
werkzeug                  2.0.2                    pypi_0    pypi
wheel                     0.42.0             pyhd8ed1ab_0    conda-forge
wrapt                     1.13.3                   pypi_0    pypi
x264                      1!164.3095           h8ffe710_2    conda-forge
x265                      3.5                  h2d74725_3    conda-forge
xorg-libxau               1.0.11               hcd874cb_0    conda-forge
xorg-libxdmcp             1.1.3                hcd874cb_0    conda-forge
xz                        5.2.6                h8d14728_0    conda-forge
yaml                      0.2.5                h8ffe710_2    conda-forge
zeromq                    4.3.4                h0e60522_1    conda-forge
zipp                      3.6.0                    pypi_0    pypi
zstd                      1.5.6                h0ea2cb4_0    conda-forge





      		
    

  





        


            

            

              
            

        

      


      

            
  

    
  
    
    

  

  



    












      

  
      



  

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            roomrys
  

      

      

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Since we were running into trouble with an incorrect h5py DLL on Windows, we are jumping ahead to release the py310 update as 1.4.1a3 (which changes many dependencies). See #1989.

      		
    

  





        


            

            

              
            

        

      


      

            
  

    
  
    
    

  

  



    












      

  
            

    

      
    

    


      

          @roomrys
roomrys




            closed this


      Oct 9, 2024

    

  


    











  
  

    

      

  




    


    

      

              

  
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