Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

Cell Maps ImmunoFluorescent Image Embedder

The Cell Maps Image Embedder is part of the Cell Mapping Toolkit

a b Documentation Status Zenodo DOI badge

Generate embeddings from ImmunoFluorescent image data from Human Protein Atlas

Dependencies

Compatibility

  • Python 3.8 - 3.11

Installation

git clone https://github.com/idekerlab/cellmaps_image_embedding
cd cellmaps_image_embedding
pip install -r requirements_dev.txt
make dist
pip install dist/cellmaps_image_embedding*whl

Run make command with no arguments to see other build/deploy options including creation of Docker image

make

Output:

clean                remove all build, test, coverage and Python artifacts
clean-build          remove build artifacts
clean-pyc            remove Python file artifacts
clean-test           remove test and coverage artifacts
lint                 check style with flake8
test                 run tests quickly with the default Python
test-all             run tests on every Python version with tox
coverage             check code coverage quickly with the default Python
docs                 generate Sphinx HTML documentation, including API docs
servedocs            compile the docs watching for changes
testrelease          package and upload a TEST release
release              package and upload a release
dist                 builds source and wheel package
install              install the package to the active Python's site-packages
dockerbuild          build docker image and store in local repository
dockerpush           push image to dockerhub

Before running tests, please install: pip install -r requirements_dev.txt.

For developers

To deploy development versions of this package

Below are steps to make changes to this code base, deploy, and then run against those changes.

  1. Make changes

    Modify code in this repo as desired

  2. Build and deploy

# From base directory of this repo cellmaps_image_embedding
pip uninstall cellmaps_image_embedding -y ; make clean dist; pip install dist/cellmaps_image_embedding*whl

Needed files

The output directory for the image downloads is required (see Cell Maps Image Downloader). Optionally, a path to the image embedding model can be provided.

Usage

For information invoke cellmaps_image_embeddingcmd.py -h

Example usage

cellmaps_image_embeddingcmd.py ./cellmaps_image_embedding_outdir --inputdir ./cellmaps_imagedownloader_outdir

Via Docker

Example usage

Coming soon...

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

History

0.3.2 (2025-05-13)

  • Updated to PEP 517 compliant build system

0.3.1 (2025-03-18)

  • Add version bounds for required packages.

  • Bug fix for change in pytorch 2.6.

0.3.0 (2024-12-02)

  • Added README generation.

  • Refactor code.

0.2.1 (2024-09-06)

  • Bug fix in --inputdir argument.

0.2.0 (2024-08-29)

  • Added --provenance flag to pass a path to json file with provenance information. This removes the necessity of input directory to be an RO-Crate.

  • Bug fixes
    • Resolved an issue in embedding generation process where images associated with multiple genes were not correctly handled (ambiguous antibodies).

0.1.0 (2024-02-01)

  • First release on PyPI.

Download files

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

Source Distribution

cellmaps_image_embedding-0.3.2a1.tar.gz (36.3 kB view details)

Uploaded Source

Built Distribution

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

cellmaps_image_embedding-0.3.2a1-py2.py3-none-any.whl (23.0 kB view details)

Uploaded Python 2Python 3

File details

Details for the file cellmaps_image_embedding-0.3.2a1.tar.gz.

File metadata

File hashes

Hashes for cellmaps_image_embedding-0.3.2a1.tar.gz
Algorithm Hash digest
SHA256 01fca7a9c8e971e506c21f4c02e52f62f7be1a950c23288afca501a5f2cd00d8
MD5 fc4e290d14656219d590698cd66e3c16
BLAKE2b-256 0e438c0a9a00eacabbc12aa76455a8e6b9de23707c8953980315843ffa868720

See more details on using hashes here.

File details

Details for the file cellmaps_image_embedding-0.3.2a1-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for cellmaps_image_embedding-0.3.2a1-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 8e64ef12f65193c060ee30694e1dfac0e5e947a957e20d734a727dc61c0d318d
MD5 9cbe60f55c04a7b1463698f15f613493
BLAKE2b-256 60c1c7b5129b3194d547295e28049946a67688deae66c106dc00773192710c20

See more details on using hashes here.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page