Skip to main content

Static and Dynamic classification tool.

Project description

Oneat

PyPI version

This project provides static and action classification networks for LSTM based networks to recoganize cell events such as division, apoptosis, cell rearrangement for various imaging modalities.

Installation & Usage

Installation

This package can be installed by

pip install --user oneat

additionally ensure that your installed tensorflow version is not over 2.3.4

If you are building this from the source, clone the repository and install via

git clone https://github.com/Kapoorlabs-CAPED/CAPED-AI-oneat/

cd CAPED-AI-oneat

pip install --user -e .

# or, to install in editable mode AND grab all of the developer tools
# (this is required if you want to contribute code back to NapaTrackMater)
pip install --user -r requirements.txt

Pipenv install

Pipenv allows you to install dependencies in a virtual environment.

# install pipenv if you don't already have it installed
pip install --user pipenv

# clone the repository and sync the dependencies
git clone https://github.com/Kapoorlabs-CAPED/CAPED-AI-oneat/
cd CAPED-AI-oneat
pipenv sync

# make the current package available
pipenv run python setup.py develop

# you can run the example notebooks by starting the jupyter notebook inside the virtual env
pipenv run jupyter notebook

Examples

oneat comes with different options to combine segmentation with classification or to just use classification independently of any segmentation during the model prediction step. We summarize this in the table below:

Example Dataset DataSet Trained Model Notebook Code Heat Map Csv output Visualization Notebook
Example timelapse Oneat model Colab Notebook Heat Map Csv File [Napari notebook] ()
Example timelapse Oneat model Colab Notebook Heat Map Csv File [Napari notebook] ()
Example timelapse Oneat model Colab Notebook Heat Map Csv File [Napari notebook] ()
Example timelapse Oneat model Colab Notebook Heat Map Csv File [Napari notebook] ()
Example timelapse Oneat model Colab Notebook Heat Map Csv File [Napari notebook] ()
Example timelapse Oneat model Colab Notebook Heat Map Csv File [Napari notebook] ()

Troubleshooting & Support

  • The image.sc forum is the best place to start getting help and support. Make sure to use the tag oneat, since we are monitoring all questions with this tag.
  • If you have technical questions or found a bug, feel free to open an issue.

Project details


Release history Release notifications | RSS feed

This version

2.0.3

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

oneat-2.0.3.tar.gz (77.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

oneat-2.0.3-py3-none-any.whl (87.2 kB view details)

Uploaded Python 3

File details

Details for the file oneat-2.0.3.tar.gz.

File metadata

  • Download URL: oneat-2.0.3.tar.gz
  • Upload date:
  • Size: 77.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.0

File hashes

Hashes for oneat-2.0.3.tar.gz
Algorithm Hash digest
SHA256 c7f0431e11c8a4b52be7a88a1656ee205c62cbf369697280597adef816648a3a
MD5 d882fc5b8eb351c0c4b0ce7eddcba917
BLAKE2b-256 a790368ec6f9cd20191e799c18c70992d38da6c99feac9a4875047302a9ff10c

See more details on using hashes here.

File details

Details for the file oneat-2.0.3-py3-none-any.whl.

File metadata

  • Download URL: oneat-2.0.3-py3-none-any.whl
  • Upload date:
  • Size: 87.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.0

File hashes

Hashes for oneat-2.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 d735a637e00d05bbe9fee6cb4e6f797b50a83a737aa99bb8212eae957a7d1b4c
MD5 581ffc3a2107879ec2037efc20c24bb5
BLAKE2b-256 522b003e72ec13200cda7014c8f8b4d6b90b0c6839f0b9b9e0932d9b262c5e25

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page