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CellProfiler is open-source cellular image analysis software.
Python Java C++ C Shell Inno Setup
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BatchProfiler Fixes #1517 - BPBatch constructor's signature changed
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cellprofiler #1308: Workspace viewer doc edits
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docker Dockerfile for builing from source
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CellProfiler.iss moved ./CellProfilerIcon* into artwork directory (fixes #1444)
CellProfiler.py Revert "Retrieve prokaryote-*.*.*.jar during setup"
CellProfiler64.iss moved ./CellProfilerIcon* into artwork directory (fixes #1444)
CellProfiler_python.bat separate 1.0 and 2.0
CellProfiler_python.command Fixed crlf and file mode issues (hopefully)
Dockerfile Add nose as a dependency
LICENSE issue #1290 more copyright notices changed to 2015
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README.md ljosa -> cellprofiler as the real docker repo
cpnose.py Make nose look in different places for jars when frozen
decorator.py Fixed crlf and file mode issues (hopefully)
external_dependencies.py Revert "Retrieve prokaryote-*.*.*.jar during setup"
python-centos.sh Fixed crlf and file mode issues (hopefully)
setup.py Revert "Retrieve prokaryote-*.*.*.jar during setup"
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windows_setup.py fixes issue #1508. The icon was being loaded from the wrong place.

README.md

CellProfiler is free, open-source software designed to enable biologists without training in computer vision or programming to quantitatively measure phenotypes from thousands of images automatically.

Our website, cellprofiler.org, is aimed at non-developer users and has lots of information about CellProfiler and how to use it, as well as a forum for asking questions.

The developer wiki covers topic such as how to build CellProfiler from source, how to set up a development environment with all of CellProfiler's dependencies, and the various resources set up to support CellProfiler development.

Getting started with the Docker image of CellProfiler

The Docker image is for advanced users who want to run CellProfiler for high-throughput processing without a graphical user interface in a Linux cluster environment. This is an alternative to installing CellProfiler from source or using the Linux build that we provide. New users will typically want to download and install CellProfiler on a Mac or Windows machine instead; see the download page.

To use the Docker image, you need to Docker's -v option to mount the input directory (which contains your images, pipeline, and other input files) and the output directory (to which images, measurements, and other output files will be written). Because CellProfiler will be run as the user "cellprofiler", you must ensure that the "cellprofiler" user has permission to write to the output directory.

Example for how to use the Docker image:

mkdir input
cd input
curl -O http://cellprofiler.org/svnmirror/ExampleImages/ExampleHumanImages/ExampleHuman.cppipe
curl -O http://cellprofiler.org/svnmirror/ExampleImages/ExampleHumanImages/AS_09125_050116030001_D03f00d0.tif
curl -O http://cellprofiler.org/svnmirror/ExampleImages/ExampleHumanImages/AS_09125_050116030001_D03f00d1.tif
curl -O http://cellprofiler.org/svnmirror/ExampleImages/ExampleHumanImages/AS_09125_050116030001_D03f00d2.tif
for a in *.tif; do echo file:///input/$a; done > filelist.txt
cd ..
mkdir -m 777 output
docker run --rm -v $(pwd)/input:/input -v $(pwd)/output:/output cellprofiler/cellprofiler:master -i /input -o /output -p /input/ExampleHuman.cppipe --file-list=/input/filelist.txt

How to file new issues

If you have a bug or other issue to report, please read the wiki page on how to file new issues to learn the best way to report it. You can also search the forum which may have a report or work-around for the issue.

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