Skip to main content

Automated 3D cell detection in large microscopy images

Project description

Python Version PyPI Downloads Wheel Development Status Tests codecov Code style: black Imports: isort pre-commit Contributions Twitter

cellfinder

cellfinder is software for automated 3D cell detection in very large 3D images (e.g., serial two-photon or lightsheet volumes of whole mouse brains). There are three different ways to interact and use it, each with different user interfaces and objectives in mind. For more details, head over to the documentation website.

At a glance:

  • There is a command-line interface called brainmapper that integrates with brainreg for automated cell detection and classification. You can install it through brainglobe-workflows.
  • There is a napari plugin for interacting graphically with the cellfinder tool.
  • There is a Python API to allow users to integrate BrainGlobe tools into their custom workflows.

Installation

You can find the installation instructions on the BrainGlobe website, which will go into more detail about the installation process if you want to minimise your installation to suit your needs. However, we recommend that users install cellfinder either through installing BrainGlobe version 1, or (if you also want the command-line interface) installing brainglobe-workflows.

# If you want to install all BrainGlobe tools, including cellfinder, in a consistent manner with one command:
pip install brainglobe>=1.0.0
# If you want to install the brainmapper CLI tool as well:
pip install brainglobe-workflows>=1.0.0

If you only want the cellfinder package by itself, you can pip install it alone:

pip install cellfinder>=1.0.0

Be sure to specify a version greater than version v1.0.0 - prior to this version the cellfinder package had a very different structure that is incompatible with BrainGlobe version 1 and the other tools in the BrainGlobe suite. See our blog posts for more information on the release of BrainGlobe version 1.

Contributing

If you have encountered a bug whilst using cellfinder, please open an issue on GitHub.

If you are interested in contributing to cellfinder (thank you!) - please head over to our developer documentation.

Project details


Release history Release notifications | RSS feed

This version

1.1.2

Download files

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

Source Distribution

cellfinder-1.1.2.tar.gz (84.3 kB view details)

Uploaded Source

Built Distribution

cellfinder-1.1.2-py3-none-any.whl (93.0 kB view details)

Uploaded Python 3

File details

Details for the file cellfinder-1.1.2.tar.gz.

File metadata

  • Download URL: cellfinder-1.1.2.tar.gz
  • Upload date:
  • Size: 84.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.9

File hashes

Hashes for cellfinder-1.1.2.tar.gz
Algorithm Hash digest
SHA256 6de688d9f558ac40ce3d54f42f58fc9e7ff6081f1616a9773a9421b9d20be96c
MD5 9294dd25884594b12e6ffd316993e4ee
BLAKE2b-256 aeb23b1fc3a54dd713b9de8d012d187b10d8c032d264b6a9ca745bd9c50b23d4

See more details on using hashes here.

File details

Details for the file cellfinder-1.1.2-py3-none-any.whl.

File metadata

  • Download URL: cellfinder-1.1.2-py3-none-any.whl
  • Upload date:
  • Size: 93.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.9

File hashes

Hashes for cellfinder-1.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 d939141df79f4bbace427c64d6de4db1848ab841bb0963ef2615b1082106ea9a
MD5 90600df2127a50dbb3ae93e3fd78cc71
BLAKE2b-256 e6b9cfe025f7d548f9d1cd9196201c2c491d2daeaba64279f6fd9393b1c0c129

See more details on using hashes here.

Supported by

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