Saravanan666/pypi-org huggingface dataset:
Package: napari-indices
napari-indicesCalculer les indices de végétationThisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.Emmanuella OKAFOR (L3 PA CMI-PSI_Université d'Angers) developed this plugin during her internship with a french team called ImHorPHen (lead by David ROUSSEAU). This plugin realises vegetation indexes computation with hyperspectral images. For the momment, there are five vegetation indexes : NDVI, TCARI, NPCI, SGI, NDGI.InstallationYou can installnapari-indicesviapip:pip install napari-indicesTo install latest development version :pip install git+https://github.com/Emmanulla0/napari-indices.gitPlugin descriptionUsing this plugin requires importing the bands of a hyperspectral image into atif file, in our case, 160 bands. You must launch it by accessing thePlugins > napari-indices> Vegetation indicesmenu.Then select the vegetation index to be calculated and the different bands to be used, then click theRunbutton to start the calculation. This results in the images corresponding to the calculated indices.The areas of interest to be analysed must then be defined. To do this, click theShapesbutton on the Napari interface and choose theadd rectangleshape from the menu that appears. Using the mouse, it is then possible to draw a rectangle on each of the two areas to be analyzed, for example a tree sheet and a green sheet of paper.To perform the Fisher ratio calculation and display the histogram, it is necessary to go back to thePlugins > napari-indices > ExempleQWidgetmenu and click the **Click me! **. This action opens a new window displaying the best vegetation index to use, its corresponding Fisher ratio and the histogram of the two selected regions on the image of the vegetation index concerned. A video explaining the plugin is available at:https://uabox.univ-angers.fr/index.php/s/LqB0qs11n3jxZVJ.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-indices" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-input-visualizer
napari-input-visualizerVisualize keyboard and mouse button pressesA simple tool to visualize input events like keyboard presses or mouse clicking and scrolling. Use it to create tutorial videos or to demonstrate a bug you encountered!Demo:https://user-images.githubusercontent.com/36735863/194586424-1e6288d3-2c2f-412c-a1cb-91d139f787bd.mp4Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-input-visualizerviapip:pip install napari-input-visualizerTo install latest development version :pip install git+https://github.com/bauerdavid/napari-input-visualizer.gitContributingContributions are very welcome.LicenseDistributed under the terms of theBSD-3license,
"napari-input-visualizer" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-itk-io
napari-itk-ioFile IO withitkfornapari.Image metadata, e.g. the pixel spacing, origin, and metadata tags, are preserved and passed into napari.Supported image file formats:BioRadBMPDICOMDICOM SeriesITK HDF5JPEGGE4,GE5,GEAdwGipl (Guys Image Processing Lab)LSMMetaImageMINC 2.0MGHMRCNifTiNRRDPortable Network Graphics (PNG)Tagged Image File Format (TIFF)VTK legacy file format for imagesFor DICOM Series, select the folder containing the series withFile -> Open
Folder.... The first series will be selected and sorted spatially.InstallationYou can installnapari-itk-ioviapip:pip install napari-itk-ioContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.Follow theitk contributing
guidelinesand theitk code of
conduct.LicenseDistributed under the terms of theApache Software License 2.0license,
"napari-itk-io" is free and open source software.IssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-J
napari-JA plugin to exchange data with FIJI and to use FIJI image analysis from napari.
Current features are:get the active image from FIJIsend a screenshot to FIJIget a set of points from the FIJI results tablefilter the points in naparisend the filtered points back to FIJIKnown problems:Crashes on linux  when the file-dialog is opened. Workaround: Set the optionUse JFileChooser to open/savefrom theEdit>Options>Input/Outputmenu.03.05.2022 - Currently you need to have the range of the quality values for point between 0 and 255, in the new version they can have any range, but we are waiting for the bug in napari 0.4.15 to be fixed to release this.Thisnapariplugin was generated withCookiecutterusing with@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-Jviapip:pip install napari-JContributingContributions 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-J" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-kics
napari-kicsA plugin to estimate chromosome sizes from karyotype images.Thisnapariplugin was generated withCookiecutterusing with@napari'scookiecutter-napari-plugintemplate.Table of ContentsInstallUsageExampleCitationMaintainerContributingLicenseInstallYou can installnapari-kicsviapip:pipinstallnapari-kicsThis will install all required dependencies as well. We recommend installing it in a virtual environment, e.g. usingconda:condacreate-nkicspython
condaactivatekics
pipinstallnapari-kicsWe recommend usingmambaas a faster alternative to conda.UsageLaunch Napari via command line (napari).Activate the plugin via menuPlugins -> napari-kics: Karyotype Widget.Select file viaFile -> Open File.Follow instructions in the panel on the right.You may use the interactive analysis plots directly via command line:karyotype-analysis-plotsExampleLaunch Napari via command line (napari).Activate the plugin via menuPlugins -> napari-kics: Karyotype Widget.Select file viaFile -> Open Sample -> napari-kics: sample.Follow instructions in the panel on the right.Try out the interactive analysis plots directly via command line:karyotype-analysis-plots--exampleCitationArne Ludwig, Alexandr Dibrov, Gene Myers, Martin Pippel.
Estimating chromosome sizes from karyotype images enables validation ofde novoassemblies. To be published.LicenseDistributed under the terms of theBSD-3license,
"napari-kics" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.ContributingContributions are very welcome. Pleasefile a pull requestwith your
contribution.You can setup a local development environment fornapari-kicsviapip:gitclonehttps://github.com/mpicbg-csbd/napari-kics.gitcdnapari-kics
pipinstall-e.Overviewhttps://user-images.githubusercontent.com/17703905/139654249-685703b5-2196-4a73-a036-d40d578ebcdf.mp4
Package: napari-label-focus
napari-label-focusEasily focus the view on selected elements from aLabelslayer to inspect them.The plugin works on 2D and 3D images.The table shows the label index and volume (number of pixels) of each label.Click on the table rows to focus the view on the corresponding label.The table is updated when layers are added or removed from the viewer, selected from the dropdown, and when their data is modified.The table is sorted by volume (biggest object on top).You can save the table as a CSV file.Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-label-focusviapip:pip install napari-label-focusContributingContributions 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-label-focus" is free and open source softwareIssuesIf you encounter any problems, please file an issue along with a detailed description.
Package: napari-labelimg4classification
napari-labelimg4classificationA simple image-level annotation tool supporting multi-channel images for napari.Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.UsageStart the labeling tool from the menuUtilities > label tool for classification.First, click on the Choose directory button to open the folder selection window, and select the folder that contains the
images you want to label and annotate.It will automatically list and display the images of tif, png, jpg, and bmp formats.
If you want to view the channels of a multi-channel image separately, check the split channels checkbox.Initially, all channels will be opened in grayscale, but the pseudo-color and contrast adjustments you specified will be
carried over when you open the next image.Thanks to napari, you can freely merge channels and turn them on and off.Label classes can be added, and can be removed by typing the same name as an already added class.It will automatically save the labels.csv file with the image path and label, and the class.txt file with the class of the label.If labels.csv and class.txt are already in the folder, they will be loaded and reflected automatically.InstallationYou can installnapari-labelimg4classificationviapip:pip install napari-labelimg4classificationTo install latest development version :pip install git+https://github.com/hiroalchem/napari-labelimg4classification.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 theMITlicense,
"napari-labelimg4classification" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-labeling
napari-labelingThis is a napari-plugin based on thelabeling project.It allows the generation of overlapping labels in one layer, save and load of this layer in a json-based file format and
it contains a widget to explore the overlapping labels layer and select specific segments with a mouse click .Please note that currently, the widget part only works by adding it through code with:from napari_labeling import edit_widget
viewer = napari.Viewer()
viewer.window.add_dock_widget(edit_widget)An example on how to achieve this can be found in themain.pyon GitHub.Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-labelingviapip:pip install napari-labelingContributingContributions 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-labeling" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-label-interpolator
napari-label-interpolatorA napari plugin to interpolate any number of nd-labels across a single dimension.To use, simply label a few slices along the desired dimension, then use the widget to interpolate along the desired axis.Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-label-interpolatorviapip:pip install napari-label-interpolatorTo install latest development version :pip install git+https://github.com/brisvag/napari-label-interpolator.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 theGNU GPL v3.0license,
"napari-label-interpolator" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-labelling-assistant
napari-labelling-assistantA lightweight plugin for visualizing labelling statistics.Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-labelling-assistantviapip:pip install napari-labelling-assistantTo install latest development version :pip install git+https://github.com/pranjaldhole/napari-labelling-assistant.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 theMITlicense,
"napari-labelling-assistant" is free and open source software.IssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-labelprop
napari-labelprop3D semi-automatic segmentation using deep registration-based 2D label propagationThisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.AboutSee "Semi-automatic muscle segmentation in MR images using deep registration-based label propagation" paper :[Paper][PDF]InstallationTo install this project :pip install napari['all']
pip install git+https://github.com/nathandecaux/napari-labelprop.gitUsageDownloadpretrained weights.Open napari from terminal and start using functions from 'napari-labelprop' plugin (Under Plugins scrolling menu).Available functions are :Inference : Propagate labels from trained weights (Pytorch checkpoint required)Training : Start training from scratch or from the pretrained weights.PS : "Unsupervised pretraining" is not yet implemented. See CLI option atLabelProprepository.Every operation is done in the main thread. So, napari is not responsive during training or inference, but you can still follow the progress in the terminal.TrainingTo train a model, reach the plugin in the menu bar :Plugins > napari-labelprop > TrainingFill the fields with the following information :Image: Select a loaded napari.layers.Image layer to segmentLabels: Select a loaded napari.layers.Labels layer with the initial labelshints: Select a loaded napari.layers.Labels layer with scribbled pseudo labelsPretrained checkpoint: Select a pretrained checkpoint from the server-side checkpoint directorySlices shape: Slices are resample to this shape for training and inference, then resampled to original shape. So far, slices must be squares.Propagation axis: Set the axis to use for the propagation dimensionMax epochs: Set the maximum number of epochs to train the modelCheckpoint output directoryCheckpoint nameWeighting criteria: Defines the criteria used to weight each direction of propagationncc = normalized cross correlation (slow but smooth), distance = distance to the nearest label (fast but less accurate)Reduction: When using ncc, defines the reduction to apply to the ncc mapmean / local_mean / none. Default isnoneUse GPU: Set if whether to use the GPU or not. Default isTrue(GPU). GPU:0 is used by default. To use another GPU, set theCUDA_VISIBLE_DEVICESenvironment variable before launching napari.InferenceTo run inference on a model, reach the plugin in the menu bar :Plugins > napari-labelprop-remote > InferenceFill the fields like in the training section. Then, click on theRunbutton.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-labelprop" is free and open source softwareIssuesIf you encounter any problems, please [file an issue] along with a detailed description.
Package: napari-labels-overlap
napari-labels-overlapcreate an overlap labels layer from two labels layersDescriptionThis plugin takes two labels layers (layerA, layerB) as inputs, and generate the overlapped regions as a binary labels layer.
Three modes:(1) A_OR_B: new layer = layerA OR layerB (union)(2) A_AND_B: new layer = layerA AND layerB (intersection)(3) A_OUTSIDE_B: new layer = layerA OUTSIDE layerB (complement)ApplicaionsObject colocalizationMerge separately identified objectsFuture workSupport N labels layersBasic coloc stats (% volume overlap)Output Labels with distinct IDs and links to original label IDsRelease log0.0.2-- Run on npe2-- Add output types: binary/connected component0.0.1-- Run on npe1Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-labels-overlapviapip:pip install napari-labels-overlapTo install latest development version :pip install git+https://github.com/chili-chiu/napari-labels-overlap.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-labels-overlap" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-large-image-importer
napari-large-image-importerNapari plugin for easy, memory-efficient import of large images.Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-large-image-importerviapip:pip install napari-large-image-importerTo install latest development version :pip install git+https://github.com/hiroalchem/napari-large-image-importer.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-large-image-importer" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-lattice
napari-latticeThis napari plugin allows deskewing, cropping, visualisation and designing custom analysis pipelines for lattice lightsheet data, particularly from the Zeiss Lattice Lightsheet. The plugin has also been otpimixed to run in headless mode.DocumentationCheck theWiki pagefor documentation on how to get started.FunctionsDeskewing and deconvolution of Zeiss lattice lightsheet imagesAbility to preview deskewed image at channel or timepoint of interestCrop and process only a small portion of the imageImport ImageJ ROIs for croppingCreate image processing workflows using napari-workflowsRun deskewing, deconvolution and custom image processing workflows from the terminalFiles can be saved as h5 (BigDataViewer/BigStitcher) or tiff filesRun in terminal without napari, enabling processing workflows on the HPCKey FeaturesApply custom image processing workflows usingnapari-workflows.Interactive workflow generation (no coding experience needed)Use custom python functions/modules within workflowsHow to use Cellpose for cell segmentationSupport will be added for more file formats in the future.Sample lattice lightsheet data download:https://doi.org/10.5281/zenodo.7117784Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.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 the [GPL-3.0 License] license,
"napari_lattice" is free and open source softwareAcknowledgmentThis project was supported by funding from theRogers Lab at the Centre for Dynamic Imaging at the Walter and Eliza Hall Institute of Medical Research. This project has been made possible in part byNapari plugin accelerator grantfrom the Chan Zuckerberg Initiative DAF, an advised fund of the Silicon Valley Community Foundation.Thanks to the developers and maintainers of the amazing open-source plugins such aspyclesperanto,aicsimageio,daskandpycudadecon.
Thanks in particular to the developers of open source projects:LLSpyandlls_ddas they were referred to extensively for developing napari-lattice.
Thanks to the imagesc forum!IssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-layer-details-display
napari-layer-details-displayA display for layer information and propertiesThisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-layer-details-displayviapip:pip install napari-layer-details-displayTo install latest development version :pip install git+https://github.com/haesleinhuepf/napari-layer-details-display.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-layer-details-display" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-layer-table
napari-layer-tableA plugin to display a layer as a table.This will work well with point layers. We are debugging shapes and labeled layers, come back to check on that!Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-layer-tableviapip:pip install napari-layer-tableTo install latest development version :pip install git+https://github.com/mapmanager/napari-layer-table.gitUsing the PluginYou can use the napari-layer-table plugin to display points layer as a table.Open a napari viewer with a Points layerAdd the plugin to the napari viewer from Plugins menu -> Add dock widget -> napari-layer-table: Points TableThe selected layer is displayed in the table.The table has columns for:Point symbol with face colorPoint coordinates (x,y,z)If the layer has properties, they are also shown as columnsPlugin FeaturesBi-directional selection between layer and table.Bi-directional deletion between layer and table.Points added to the layer are added to the table.Points moved in the layer are updated in the table.Multiple points selected in the layer are also selected in the tableChanges to face color and symbol in the layer are updated in the table.Ability to sort individual columns from low to high or high to lowRefreshbutton to manually refresh the table databtfbutton to manually bring the layer whose table data is being shown to frontRight-click for context menu to:Toggle table columns on/off.Toggle shift+click to add a point to the layer (no need to switch viewer mode)Copy table to clipboardContributingContributions 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 theGNU GPL v3.0license,
"napari-layer-table" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.