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PartSeg is python GUI for bio imaging analysis

Project description

PartSeg

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PartSeg is gui and library for segmentation algorithms.

This application is designed to help biologist with segmentation based on threshold and connected components

interface

Tutorials

  • Tutorial: Chromosome 1 (as gui) link
  • Data for chromosome 1 tutorial link
  • Tutorial: Different neuron types (as library) link

Installing

  • From binaries:
    • Windows (build on Windows 10)
    • Linux (build on Ubuntu 18.04)
    • MacOS (build on MacOS Mojave)
  • With pip (on linux you need to install numpy and cython earlier)
    • From pypi: pip install PartSeg
    • From repository: pip install git+https://github.com/4DNucleome/PartSeg.git

Running

If you download binaries look for PartSeg_exec file inside the PartSeg folder

If you install from repository or from pip you cat run it with PartSeg command or python -m PartSeg. First option do not work on Windows.

PartSeg export few commandline options:

  • --no_report - disable reporting errors to authors
  • --no_dialog - disable reporting errors to authors and showing error dialog. Use only when running from terminal.
  • segmentation_analysis - skip launcher and start analysis gui
  • segmentation - skip launcher and start segmentation gui

Additional remarks:

Current version of PartSeg use tifffile package to read *.tiff files. Because newer version is easy to install only on Windows. If you install it manually with imagecodecs it should work.

Save Format

Saved project are tar files compressed with gzip or bz2

Metadata are saved in data.json file (in json format) images/mask are saved as *.npy (numpy array format)

Interface

Launcher. Chose program that you will launch:
launcher
Main window of Segmentation Analysis:
interface
Main window of Segmentation Analysis with view on measurement result:
interface
Window for creating set of measurements:
statistics
Main window of Mask Segmentation:
mask interface

Laboratory

Laboratory of functional and structural genomics http://4dnucleome.cent.uw.edu.pl/

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