Saravanan666/pypi-org huggingface dataset:
Package: napari-PICASSO
napari-PICASSOUnmix spectral spilloverAutomatic UsageYou can find thePICASSOplugin in the menuPlugins > napari-PICASSO: PICASSO. Select sink images that have spectral spillover from corresponding source images, then click run to optimise the mixing parameters with PICASSO.Manual UsageSelect the manual button in options pop up window. Then select sink images that have spectral spillover from corresponding source images. In the source images window, sliders for each $source$ control the mixing spillover, $m$ (top), and background, $b$ (bottom, optional).Mixing model$$ sink = \sum_{i} m_i(source - b_i) $$InstallationYou can installnapari-PICASSOviapip:pip install napari-PICASSODetailsnapari-PICASSO is a napari widget to blindly unmix fluorescence images of known members using PICASSO1.For example, if 2 fluorophores with overlapping spectra are imaged, spillover fluorescesce from a channel into an adjacent channel could be removed if you know which channel is the source of the spillover fluorescence and which channel is the sink of the spillover fluorescence.PICASSO is an algorithm to remove spillover fluorescence by minimizing the mutual information between sink and source images. The original algorithm described by Seo et al, minimized the mutual information between pairs of sink and source images using a Nelson-Mead simplex algorithm and computing the mutual information outright with custom written MATLAB code1. The napari plugin uses a neural net to estimate and minimize the mutual information (MINE2) between pairs of sink and source images using stochastic gradient descent with GPU acceleration.ReferencesSeo, J. et al. PICASSO allows ultra-multiplexed fluorescence imaging of spatially overlapping proteins without reference spectra measurements. Nat Commun 13, 2475 (2022).Belghazi, M. I. et al. MINE: Mutual Information Neural Estimation. arXiv:1801.04062 [cs, stat] (2018).
Package: napari-pims-bioformats
napari-pimsPIMS plugin for napariThisnapariplugin was generated withCookiecutterusing with@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-pimsviapip:pip install napari-pimsContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theBSD-3license,
"napari-pims" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-pixel-correction
napari-pixel-correctionPlugin to correct manually pixel wrongly predicted on image by annotationThisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.This plugin allows you to manually correct the images of the apple tree flowers by annotation. Below, a piece of an image shows the predicted pixels (in brown). A pixel in brown is assigned to the flower class. We can see that the brown colour does not necessarily cover a flower in this image.InstallationYou can installnapari-pixel-correctionviapip:pip install napari-pixel-correctionTo install latest development version :pip install git+https://github.com/hereariim/napari-pixel-correction.gitHow does it workFirst, you need a compressed file (in .zip format) were you have all your images. For a compressed file named asinput.zip, the compressed file should be built like :.
└── input.zip
    └── repository
        ├── image
        │   ├── im_1.JPG
        │   ├── im_2.JPG  
        │   ├── im_3.JPG
        │   ...
        │   └── im_n.JPG
        │
        └── mask
            ├── im_1_mask.JPG
            ├── im_2_mask.JPG
            ├── im_3_mask.JPG
            ...
            └── im_n_mask.JPGIn repository, each image folder should have two elements : image in RGB and the segmented mask in binary image (where no-flower class is 0 and flower class is 255)ContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theBSD-3license,
"napari-pixel-correction" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-plot-profile
napari-plot-profile (npp)Plot a Line ProfilePlot intensities along a line innapari.Open some images innapari.Add a shapes layer.Activate the line drawing tool or the path tool and draw a line.After drawing a line, click on the menu Plugins > Measurements (Plot Profile)If you modify the line, you may want to click the "Refresh" button to redraw the profile.To see how these steps can be done programmatically from python, check out thedemo notebookCreate a Topographical ViewCreate a 3D view of a 2D image by warping pixel intensities to heights. It can be displayed as a 3D image layer, a points cloud layer or a surface layer.Thisnapariplugin was generated withCookiecutterusing with@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-plot-profileviapip:pip install napari-plot-profileContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theBSD-3license,
"napari-plot-profile" is free and open source softwareIssuesIf you encounter any problems, please create a thread onimage.scalong with a detailed description and tag@haesleinhuepf.
Package: napari-plugin-devtools
napari-plugin-devtoolsA repo with tools and services fornapari plugindevelopersInstallationThis tool can be installed via pip:pip install napari-plugin-devtools,
you can also add it to your requirements.txt to be installed with other
dependencies automatically.Validation toolThe validation tools provides automated tests for plugin developers,
these checks verify that the plugin is available for users of napari
to install, and would register entry points with napari.There are two parts to the validation tool. One part is a
command line interface and the other is a pytest fixture.Command Line Interface (CLI) UsageThe CLI can be used by continuous integration (CI) pipelines to perform a
quick verification of a plugins setup without any specific input required.
It serves as a quick "sanity check". (It is also accessible from python in validation.py)The tool can be run asnpd <cmd>. where currently we support cmdvalidate:npd validate: validate classifiers and function hooks can be recognized by napari.
The validation would run on built packages under dist folder to check if they are annotated
properly with framework classifier, and validate hooks are properly annotated that they can be found
by napari.npd validate -i|--include-plugin INCLUDE_PLUGIN [INCLUDE_PLUGIN ...]run hook checks only on listed plugins,
this is useful to filter out other plugins on a complicated python environment.npd validate -e|--exclude-plugin EXCLUDE_PLUGIN [EXCLUDE_PLUGIN ...]do not run hook checks on listed plugins,
this is useful to filter out other plugins on a complicated python environment.npd validate -v|--verboseenable verbose mode, gives slightly more information on the underlying
findings of validation process.Pytest fixture usagedevtools provides a pytest fixture: napari_plugin_tester
in plugin_tester.py, it extends a plugin manager used by napari
and have additional assertion modes ready:def test_pm(napari_plugin_tester):
    napari_plugin_tester.assert_plugin_name_registered("test-plugin")
    napari_plugin_tester.assert_module_registered(_test)
    napari_plugin_tester.assert_implementations_registered(
        "test-plugin", "napari_get_reader"
    )where you can check more specifically on a module or function
being registered under napari annotations, seehook specificationsto find what other annotations are avaiable in addition tonapari_get_reader
Package: napari-plugin-engine
napari plugin enginenapari-plugin-engineis a fork ofpluggy,
modified by thenapariteam.There are some API and feature changes, including:discovery vianaming
conventionas well asentry_pointssupport for reordering of hook calls after registration.enhanced API for retrieving plugin package metadata.modified plugin call and registration exception handlingmodifiedHookResultobject and hook call loop, with ability to retrieve theHookImplementationresponsible for the result.lazy plugin discoverysome changes to variable and attribute namingremoved all deprecated codetype annotations on everythingpytest fixtures for testinga couple napari-specific convenience importsFor usage overview and a reference for thenapari-plugin-engineAPI, see ourDocumentation(see also: thepluggy documentation)installpipinstallnapari-plugin-engineUsageseedocumentation
Package: napari-plugin-manager
napari-plugin-managerWIP, under active developmentA plugin that adds a plugin manager tonapari.InstallationYou can installnapari-plugin-managerviapip:pip install napari-plugin-managerLicenseDistributed under the terms of theBSD-3license,
"napari-plugin-manager" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-plugin-search
napari-plugin-searchFind napari pluginsUsageEnter the name of the plugin you are searching for and use theupanddownarrow keys to navigate between them.
HitEnterto start a plugin.Thisnapariplugin was generated withCookiecutterusing with@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-plugin-searchviapip:pip install napari-plugin-searchContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theBSD-3license,
"napari-plugin-search" is free and open source softwareIssuesIf you encounter any problems, please create a thread onimage.scalong with a detailed description and tag@haesleinhuepf.
Package: napari-points2regions
napari-points2regionsA napari plugin for Points2RegionsThisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-points2regionsviapip:pip install napari-points2regionsTo install latest development version :pip install git+https://github.com/wahlby-lab/napari-points2regions.gitContributingContributions are very welcome.LicenseDistributed under the terms of theMITlicense,
"napari-points2regions" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-pointslayer-projection
napari-pointslayer-projectionThis plugin creates a 2d projection of all your points.Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-pointslayer-projectionviapip:pip install napari-pointslayer-projectionTo install latest development version :pip install git+https://github.com/gatoniel/napari-pointslayer-projection.gitContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theBSD-3license,
"napari-pointslayer-projection" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-potential-field-navigation
napari-potential-field-navigationA simple plugin for trajectories visualisations in napari for lung navigation in CTs scansThisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-potential-field-navigationviapip:pip install napari-potential-field-navigationTo install latest development version :pip install git+https://github.com/rcremese/napari-potential-field-navigation.gitContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theMozilla Public License 2.0license,
"napari-potential-field-navigation" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-power-spectrum
napari-power-spectrumA simple plugin to get the power spectrum of frames of a stack imageThisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-power-spectrumviapip:pip install napari-power-spectrumTo install latest development version :pip install git+https://github.com/GiorgiaTortora/napari-power-spectrum.gitContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theBSD-3license,
"napari-power-spectrum" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-power-widgets
napari-power-widgetsPowerfulmagicguiwidgets and type annotations for general-purpose napari plugin development.napari-power-widgetsmakes the full use of type-to-widget mapping strategy ofmagicguito provide napari-specific types and value-widgets, which will be very useful to improve UI/UX of your napari plugins with simple codes.Currently,napari-power-widgetsdoes not provide any reader, writer or widget. It is supposed to be used programmatically.ExamplesSome types/widgets and the possible usage are picked up here (→ check all). If you have any neat ideas, please open an issue.1.BoxSelectionAlias of a four-float tuple for 2D selection. You can set the value by drawing a interaction box in the viewer.e. g. : image cropper, rectangular labeling etc.@magicguideff(box:BoxSelection):print(box)viewer.window.add_dock_widget(f)2.OneOfRectanglesAlias ofnp.ndarrayfor one of rectangles in aShapeslayer.e. g. : image cropper, rectangular labeling etc.@magicguideff(rect:OneOfRectangles):print(rect)viewer.window.add_dock_widget(f)3.LineDataAlias ofnp.ndarrayfor a line data. You can obtain the data by manually drawing a line in the viewer.e. g. : line profiling, kymograph etc.@magicguideff(line:LineData):print(line)viewer.window.add_dock_widget(f)4.OneOfLabelsAlias of booleannp.ndarrayfor a labeled region. You can choose ones by directly clicking the viewer.e. g. : image masking, feature measurement etc.@magicguideff(label:OneOfLabels):passviewer.window.add_dock_widget(f)5.ZRangeAlias of a tuple of float that represents the limit of the third dimension. You can select the values by moving the dimension slider.e. g. : movie trimming, partial image projection etc.@magicguideff(zrange:ZRange):print(zrange)viewer.window.add_dock_widget(f)Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-power-widgetsviapip:pip install napari-power-widgetsTo install latest development version :pip install git+https://github.com/hanjinliu/napari-power-widgets.gitContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theBSD-3license,
"napari-power-widgets" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-pram
napari-pramPlugin for PRAM data annotation and processing.Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.UsageOpennapari-pramtoolbox:On the toolbar, select[Plugins] > napari-pram: Open PRAM's toolboxLoad PRAM image and annotations:PressCommand/Control+O:Select*.jsonfiles for annotations (from eitherVGG Annotatorornapari-pram)Select*.pngfiles for PRAM imageAnnotatePressAnnotateClick the plus-in-circle icon on the top-left panel and start editingRun PRAM particles detectorSelect a proper threshold between 1 (ultra sensitive) - 10 (less sensitive)PressRun DetectorEvaluatePressEvaluateHide/Unhide true positive/ false postive/false negative layersLoad new imagePressClear Allto remove all layersExport to JSONPressSave to Fileto export all annotations, predictions from the algorithm to a JSON fileInstallationFollowing thistutorialto installnapari.Alternatively, you can follow my instructions as follows:You will need a python environment. I recommendConda. Create a new environment, for example:conda create --name napari-env python=3.7 pipActivate the new environment:conda activate napari-envInstallnapariviapip:pip install napari[all]Then you can finally install our pluginnapari-pramviapip:pip install napari-pramAlternatively, the plugin can be installed using napari-GUI[Plugins] > Install/Uninstall Pluginsand search fornapari-pramContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theMITlicense,
"napari-pram" is free and open source softwareIssuesIf you encounter any problems, please [file an issue] along with a detailed description.
Package: napari-proofread-brainbow
napari-proofread-brainbowproofreading with napariThisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-proofread-brainbowviapip:pip install napari-proofread-brainbowContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theMITlicense,
"napari-proofread-brainbow" is free and open source softwareIssuesIf you encounter any problems, please [file an issue] along with a detailed description.
Package: napari-properties-plotter
napari-properties-plotterA napari plugin that automatically generates interactive plots based on layer properties.Thisnapariplugin was generated withCookiecutterusing with@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-properties-plotterviapip:pip install napari-properties-plotterContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theBSD-3license,
"napari-properties-plotter" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-properties-viewer
napari-properties-viewerA viewer for napari layer propertiesThisnapariplugin was generated withCookiecutterusing with@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-properties-viewerviapip:pip install napari-properties-viewerUsing the properties viewer tableOpen a a napari viewer with a layer with properties (e.g., Points)View the properties by opening the properties viewer plugin from Plugins menu -> Add dock widget -> napari-propertiews-viewer: properties tableThe layer property values are now displayed in the table widget. You can edit the values by double clicking the cell of interest and entering a new value.ContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theBSD-3license,
"napari-properties-viewer" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-psf-analysis
napari-psf-analysisThisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.A plugin to analyse point spread funcitons (PSFs) of optical systems.UsageStarting PointTo run a PSF analysis open an image of acquired beads. Add a point-layer
and indicate the beads you want to measure by adding a point.Run AnalysisOpen the plugin (Plugins > napari-psf-analysis > PSF Analysis) and ensure
that your bead image and point layers are select in theBasictab underImageandPointsrespectively.
In theAdvancedtab further information can be provided. Only the filled
in fields of theAdvancedtab are saved in the output.After verifying all input fields clickExtract PSFs.Discard and Save MeasurementOnce the PSF extraction has finished a new layer (Analyzed Beads) appears,
holding a summary
image for every selected bead.
Individual summaries can be discarded by clicking theDelete Displayed Measurementbutton.Results are saved to the selectedSave Dirby clicking theSave Measurementsbutton.Note: Beads for which the bounding box does not fit within the image are
automatically excluded from the analysis and no output is generated.Saved DataEvery image of theAnalyzed Beadslayer is saved as{source_image_name}_X {bead-centroid-x}_Y{bead-centroid-y}_Z{bead-centroid-z}.pngfile.
Additionally aPSFMeasurement_{source_image_acquisition_date}_ {source_image_name}_{microscope_name}_{magnification}_{NA}.csvfile is
stored containing the measured values and all filled in fields.InstallationWe recommend installation into a fresh conda environment.1. Install naparicondacreate-y-npsf-analysis-cconda-forgepython=3.9

condaactivatepsf-analysis

condainstall-cconda-forgenaparipyqt2. Install napari-aicsimageio and bioformatsRequired if you want to open other files than.tife.g..stk..Note:Seenapari-aicsimageiofor more information about opening images.condainstall-cconda-forgeopenjdkbioformats_jar"aicsimageio[all]"napari-aicsimageio

condadeactivate
condaactivatepsf-analysis3. Install napari-psf-analysisYou can installnapari-psf-analysisviapip:python-mpipinstallxmlschema
python-mpipinstallnapari-psf-analysis4. OptionalSet ConfigYou can provide a config yaml file with the available microscope names and a default save directory.
This will change theMicroscopetext field to a drop down menu and change the default save directory.example_config.yamlmicroscopes:-TIRF-Zeiss Z1output_path:"D:\\psf_analysis\\measurements"To use this config navigate toPlugins > napari-psf-analysis > Set Configand select the config file.Note:The save path is OS specific.5. Desktop Icon for WindowsFollowthese instructionsby Robert Haase.ContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theBSD-3license,
"napari-psf-analysis" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-psf-extractor
napari-psf-extractorA simple plugin to extract precise models of the Point Spread Functions of imagesInstallationYou can installnapari-psf-extractorviapip:pip install git+https://github.com/hoogenboom-group/PSF-Extractor@master
pip install napari-psf-extractorContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.
To provide a better understanding of the project's class structure,
refer to thediagramlinked here.LicenseDistributed under the terms of theGNU GPL v3.0license,
"napari-psf-extractor" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.