Saravanan666/pypi-org huggingface dataset:
Package: napari-script-editor
napari-script-editorA python script editor for napari based onhaesleinhuepf's fork of PyQode.Thisnapariplugin was generated withCookiecutterusing with@napari'scookiecutter-napari-plugintemplate.UsageStart the script editor from the menuTools > Scripts > Script Editor. Use the auto-completion while typing,
check out thenapari tutorialsand theexample scripts.
Use theRunbutton to execute a script.If you save the script to the folder ".napari-scripts" in your home directory, you will find the script in theTools > Scriptsmenu in napari. You can then also start it from there.Note: If you have scripts, that might be useful to others, please send them aspull-requestto the examples in
repository or share them in any other way that suits you.chatGPT supportIn caseopenAI APIis installed, you find another button in the script editor toAsk chatGPT.
Enter a prompt in the script editor and click the button. The script editor will send the prompt to
chatGPT and replace it with the answer. For example try entering:WritePythoncodeforsegmentinganimageusingthesesteps:*ApplyaGaussianblur*ThresholdtheimageusingOtsu's method*Applyconnectedcomponentlabelingand it will replace it with code accordingly. If it doesn't work in the first attempt, try again. ChatGPT's answers are not always the same.InstallationGet a python environment, e.g. viamini-conda.
If you never used python/conda environments before, please follow the instructionsherefirst.Installnapariusing conda.conda install -c conda-forge napariAfterwards, installnapari-script-editorusing pip:pip install napari-script-editorContributingContributions 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-script-editor" is free and open source softwareKnown issuesSometimes, the script editor thinks, the file has been changed on disk and asks to reload it.IssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-sdeconv
napari-sdeconv2D and 3D deconvolutionThisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-sdeconvviapip:pip install napari-sdeconvTo install latest development version :pip install git+https://github.com/sylvainprigent/napari-sdeconv.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-sdeconv" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-seedseg
napari-seedsegA simple plugin for 2D medical image segmentation. In this project, we are trying to use Flood method for segmentation.
Flood segmentation, also known as flood fill or region growing, is an image segmentation technique that starts from a seed point and expands to neighboring pixels with similar properties (e.g., intensity, color). In our project, you only can segment one label at the time. Below is a description of the repository's structure and the purpose of each file:.
├── setup.cfg              # package metadata
├── pyproject.toml         # use setuptools
├── src/napari_seedseg     
│   ├── napari.yaml        # Load and stress tests
│   ├── __init.py__        # Python package metadata files
│   ├── _widget.py         # Widget contributions
│   ├── _layers.py         # Layers contributions
│   └── _method.py         # Methods contributions
└── ...Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-seedsegviapip:pip install napari-seedsegTo install latest development version :pip install git+https://github.com/rezaakb/napari-seedseg.gitPackagesIn this project we have used these packages:numpy
magicgui
qtpy
opencv-python-headless
scikit-image>=0.19.3ContributingContributions 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-seedseg" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-segment
napari-segmentInteractively segment organoids/spheroids/aggregates in brightfield/fluorescence from nd2 multipositional stack.Installationpip install napari-segmentorFrom napari pluginUsage for segmentationDrag your nd2 file into napari (otherwise try the Sample data from File / Open Sample / napari-segment)Lauch Plugins -> napari-segment: Segment multiposSelect the brightfield channelThe data is lazily loaded from nd2 dataset and dynamically segmented in the viewer.Binning 1-8 allows to skip small features and focus on bigger objects, also makes processing faster.Various preprocessing modes allow segmentation of different objects:Invert: will use the dark shadow around aggregate - best for very old aggregates , out of focus (File / Open Sample / napari-segment / Old aggregate)Gradient: best for very sharp edges, early aggregates, single cells (File / Open Sample / napari-segment / Early aggregate)Gauss diff: Fluorescence images
The result of preprocessing will be shown in the "Preprocessing" layer.Smooth, Theshold and Erode parameters allow you to adjust the preliminary segmentation -> they all will appear in the "Detections" layer as outlinesMin/max diameter and eccentricity allow you to filter out unwanted regions -> the good regions will appear in the "selected labels" layer as filled areas.Once satisfied, click "Save the params!" - it will automatically create file.nd2.params.yml file, so you can recall how the segmentation was done. Next time you open the same dataset, the parameters will be loaded automatically from this file.Next section is for quantifying the sizes. Pixel size will be retrieved automatically from metadata. If not: update it manually and click Update plots to see the correct sizes. Click on any suspected value to see the corresponding frame and try to adjust the above parameters.If impossible to get good results with automatic pipeline, click Clone for manual correction: this will create an editable "Manual" layer which you can edin with built-in tools in napari. Click "Update plots" to see the updated values."Save csv!" will generate a csv file with regionprops.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-segment" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-segment-anything
napari-segment-anythingNapari plugin ofSegment Anything Model (SAM)Download the network weightsherehttps://user-images.githubusercontent.com/21022743/230456433-2fa7bc40-a735-4d73-8d87-ecf776bbe2be.mp4Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-segment-anythingviapip:pipinstallnapari-segment-anythingWe recommend installing the latest development version because this package is being developed:pipinstallgit+https://github.com/jookuma/napari-segment-anything.gitIMPORTANT:napariwon't work if you don't havepyqt5orpyside2installed.InstructionsOpening napari-segment-anythingThis software is napari plugin, so once you have napari installed you can open it using the command line:napari<yourimagepath>-wnapari-segment-anything'Segment Anything'I noticed that sometimes napari fails to load the plugin widget from the command line, go to step 2 from below to load it.If you prefer the user interface you need to:Drag and drop your image into napari to load it;Go to the "Plugins" file menu in the upper right corner and select the "Segment Anything" plugin.Follow the instructions below for usage.IMPORTANT: If you get an error make sure you havepyqt5orpyside2installed.UsageInteractions are done on the "SAM points" and "SAM box" layers using the existing functionalities of napari. Only rectangle shapes trigger the network prediction.For points supervision, left clicks are positive cues (object) and right clicks are negative (background).Press the "Confirm Annot." button (or the "C" key) to propagate the current segmentation mask to the label image.Use the napari labels layer features to delete or edit already confirmed labels.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 theApache Software License 2.0license,
"napari-segment-anything" is a free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-sentinel-to-zarr
napari-sentinel-to-zarrWriter plugin for napari to save Sentinel tiffs into ome-zarr formatThisnapariplugin was generated withCookiecutterusing with@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-sentinel-to-zarrviapip:`pip install napari-sentinel-to-zarr`UsageThis package provides command-line utilities for:Processing raw Sentinel zips of a tile into multiscale zarrProcessing interpolated “GapFilled” tif for that tile into zarr, rechunking along time axisProcessing the zarr from step 2 into multiscale OME-zarrRaw Zipped Images to ZarrInstall the latest version of napari usingpip install -U napariInstall napari-sentinel-to-zarr usingpip install napari-sentinel-to-zarrRunsentinel-to-zarr zip-to-zarr path/to/tile/55HBU out/path/dir/55HBU.zarrwherepath/to/tile/55HBUis a directory full of Sentinel zipsInterpolated Images to ZarrRunsentinel-to-zarr interpolated-to-zarr path/to/interpolated/55HBU_GapFilled_Image.tif out/dir/Image.zarrYou can pass in optional arguments:--step-size- how many slices to convert at once. The default is 20 which will require ~5GB RAM. A larger step size means more slices can be loaded at once, and will speed up performance. A full image is typically ~175GB.--chunk-size- the chunk size of the resulting zarr. Default is 1024 which is typically considered a good option and provides good performanceInterpolated Zarr to Multiscale ZarrRunsentinel-to-zarr zarr-to-multiscale-zarr path/to/interpolated/zarr out/path/interpolated_multiscale.zarr tilenameWherepath/to/interpolated/zarris the output file from step 2You can pass in optional arguments--min-shape-the smallest pyramid level you wish to generate. Default is 1024pxNapari PluginThis package also comes with a napari writer plugin which allows you to open the raw tiles directly by dragging one into a napari viewer, and saving out while you browse usingFile>Save LayersContributingContributions 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-sentinel-to-zarr" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-sentinel-zip
napari-sentinel-zipStacks and opens Sentinel mission zip archives for one tile across different timepoints.Thisnapariplugin was generated withCookiecutterusing with@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-sentinel-zipviapip:pip install napari-sentinel-zipContributingContributions 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-sentinel-zip" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-shape-odyssey
napari-shape-odysseyAnalyze shapes of meshes: This plugin provides advanced measures of shape for meshes. It is based largely on the following libraries and tools:PyFMboundary-first-flatteningShape analysisThis plugin provides Laplace spectra (Reuter, Wolter, Peinecke (2005)), heat kernel signatures (Bronstein & Kokkinos (2010)) & wave kernel signatures (Audrey, Schlickewei, Cremers et al.).Laplace spectracan be imagined to be the equivalent of resonance modes on the surface of a mesh. The resonance and the resonance modes can, for typical objects, look like this:Heat kernel signatures: Heat dissipation on a mesh depends on local geometry. You can use the heat kernel signature to easily generate a large number of local features of shapeUnwrappingThis plugin provides a number of methods to unwrap a mesh into basic shapes such as spheres or disks. The method relies onboundary-first flattening- currently it's only available on Windows.Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-shape-odysseyviapip:´´´bash
pip install napari-shape-odyssey
napari-skimage-regionprops @ git+https://github.com/jo-mueller/napari-skimage-regionprops.gitpyFM @ git+https://github.com/RobinMagnet/pyFM.git´´´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-shape-odyssey" is free and open source softwareIssuesIf you encounter any problems, please [file an issue] along with a detailed description.
Package: napari-sif-reader
napari-sif-readerThis is a simple wraper to read .sif format files from Andor Technology.Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-sif-readerviapip:pip install napari-sif-readerTo install latest development version :pip install git+https://github.com/rjlopez2/napari-sif-reader.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-sif-reader" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-simpleannotate
napari-simpleannotateA simple plugin to label imageThisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-simpleannotateviapip:pip install napari-simpleannotateTo install latest development version :pip install git+https://github.com/hiroalchem/napari-simpleannotate.gitHow to useOpening Files or Directories:Click theOpen Filebutton to open an image file.Click theOpen Directorybutton to open a directory containing images.If there's aclass.yamlin the directory of the selected file or within the selected directory, it will be automatically detected. A popup will appear, giving you the option to load it.Class Management:Enter the class name in the textbox and click theAdd classbutton to add a class. When adding a class name, a number is automatically assigned to it. This number will be used when saving annotations.Select a class from the class list and click theDelete selected classbutton to remove it.Annotating Images:Use napari's rectangle tool to annotate the images. If you have a class selected, the annotation will automatically be assigned to that class.For existing rectangles, you can change their class by selecting the rectangle and then choosing a different class from the list.Saving Annotations:Click theSave Annotationsbutton to save the annotations in YOLO format.Along with saving the annotations, theclass.yamlwill also be saved. If aclass.yamlalready exists and its content is different from the current one, a popup will appear asking for confirmation to overwrite it.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-simpleannotate" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-sim-SIMulator
napari-sim-SIMulatorA simple plugin to simulate raw image stacks for structured illumination microscopy (SIM).Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-sim-SIMulatorviapip:pip install napari-sim-SIMulatorTo install latest development version :pip install git+https://github.com/Meizhu-Liang/napari-sim-SIMulator.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-sim-SIMulator" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-sketchpose
napari-sketchposeA plugin to adapt the Omnipose implementation to frugal labeling. It aims to facilitate the training from scratch or the
use of transfer learning with little data, by not needing to draw entire cells, but a few squiggles instead (see GIF below).If you use this plugin please cite thepaper:Clément Cazorla, Nathanaël Munier, Renaud Morin, Pierre Weiss. Sketchpose: Learning to Segment
Cells with Partial Annotations. 2023. ffhal-04330824f@unpublished{cazorla:hal-04330824,TITLE={{Sketchpose: Learning to Segment Cells with Partial Annotations}},AUTHOR={Cazorla, Cl{\'e}ment and Munier, Nathana{\"e}l and Morin, Renaud and Weiss, Pierre},URL={https://hal.science/hal-04330824},NOTE={working paper or preprint},YEAR={2023},MONTH=Dec,KEYWORDS={Cellpose -Segmentation -Frugal learning -Napari -Deep learning -Distance map},PDF={https://hal.science/hal-04330824/file/sketchpose_hal.pdf},HAL_ID={hal-04330824},HAL_VERSION={v1},}Image Credit: Eduard MuzhevskyiThisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationFirst, we advise you to create a conda environment in Python 3.10, in which you will run Napari:conda create -n sketchpose_env python=3.10
conda activate sketchpose_env
conda install pip
python -m pip install "napari[all]" --upgradeYou can installnapari_sketchposeviapip:pip install napari_sketchposeWARNING:For Windows users, CUDA version of PyTorch may not be installed properly. When the plugin starts for the first time, it checks whether
CUDA version is installed. If not, it tries to install it using light-the-torch library. If this does not work, you should re-install
CUDA torch and torchvision versions manually, otherwise the plugin will not work properly.TutorialWe strongly recommend reading thedocumentationto get the most out of the plugin.
A step-by-step tutorial illustrated with GIFs will guide you through the various stages.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 theGNU GPL v3.0license,
"napari-sketchpose" is free and open source softwareIssuesIf you encounter any problems, please [file an issue] along with a detailed description.
Package: napari-solarized
napari-solarizedSolarized (-ish) themes for napari, based onsolarized.Thisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnapari-solarizedviapip:pip install napari-solarizedTo install latest development version :pip install git+https://github.com/aganders3/napari-solarized.gitContributingContributions are very welcome.LicenseDistributed under the terms of theMITlicense,
"napari-solarized" is free and open source softwareIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: napari-spacemouse
napari-spacemouse3DConnexion SpaceMouse support for napariExpected to work for any product in theSpaceMouseline, but only tested on a SpaceNavigator. Currently only tested on macOS.UsageTo install globally in napari:importnapari_spacemouse# start listening to the spacemousenapari_spacemouse.install()# stop listening to the spacemousenapari_spacemouse.uninstall()Alternatively, there isSpaceMousewidget that can be used to toggle
support for the mouse, and provide some configuration.Important note for macOSCurrently, this plugin requires that the3DconnexionHelperdrivernotbe running, otherwise you will likely get anOSErrorwhen activating the plugin.  To fix this:Open/Applications/Utilities/Activity Monitor/Search for3DconnexionHelperIf it's running, highlight it and quit it using the X button at the top right.When done, you can start it again anytime at/Applications/3Dconnexion/3DconnexionHelper.(Eventually this could be fixed, but we need to use the actual Connexion framework API instead of direct USB reads.)
Package: napari-spacetx-explorer
napari-spacetx-explorerA napari plugin for interactive visualization of decoded spots from spatial transcriptomic data stored as CSVThisnapariplugin was generated withCookiecutterusing with@napari'scookiecutter-napari-plugintemplate.The plugin code was written by Sebastian Gonzalez-Tirado.Reader hookspecnapari-spacetx-explorerallows the user to open and visualize CSV files that
have point-data stored in a given format. The main target is for users who
want to analyze decoded spot maps from spatial omics experiments but it can
used as well for any other type of coordinate data where each point has assigned
a label (e. g. a gene) as a string and the x and y-coordinates of the point's center.
The header for these data must be 'target', 'xc', and 'yc', respectively.Selecting genesAfter loading the gene/target maps it is possible to select specific groups for better visualization.
This creates a new "Points" layer in napari with the selected groups displayed in different colors.Loading data in OME.ZARR formatThe plugin napari-ome-zarr can be used to display whole-tissue images in addition to the spot maps produced with thenapari-spacetx-explorerplugin.InstallationThe easiest installation is via the "Install/Uninstall Plugins..." under the Plugins menu in napari.Another way is throughpippip install napari-spacetx-explorerContributingContributions 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-spacetx-explorer" is free and open source softwareIssuesIf you encounter any problems or would like some support, pleasefile an issuealong with a detailed description.