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Enregistrement W6912489651 · doi:10.5281/zenodo.16627702

napari: a multi-dimensional image viewer for Python

2025· other· en· W6912489651 sur OpenAlexaff

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2025
Typeother
Langueen
DomaineComputer Science
ThématiqueDigital Imaging for Blood Diseases
Établissements canadiensInnovation Cluster (Canada)
Organismes subventionnairesnon disponible
Mots-clésSlicingZoomScripting languagePython (programming language)VisualizationFeature (linguistics)Focus (optics)Graphical user interface

Résumé

récupéré en direct d'OpenAlex

napari 0.6.3 Thu, Jul 31, 2025 We're happy to announce the release of napari 0.6.3! napari is a fast, interactive, multi-dimensional image viewer for Python. It's designed for exploring, annotating, and analyzing multi-dimensional images. It's built on Qt (for the GUI), VisPy (for performant GPU-based rendering), and the scientific Python stack (NumPy, SciPy, and friends). For more information, examples, and documentation, please visit our website: https://napari.org/ Highlights A Zoom with a View 🔍 Pardon the play on words, but you can now zoom directly to a region of interest in the viewer by holding Alt and dragging with the mouse (#8004). The camera will pan and zoom to fit the selected region, making it much easier to focus on specific areas of your data. This feature works in both 2D and 3D views. Fine Tuning Thick Slicing from the GUI 📏 Thick slicing controls are now available in the GUI (#6146)! This allows you to project multiple slices together using different modes (sum, mean, max, and min) for better visualization of your multidimensional data. You can access the thickness controls by right-clicking on the dimension sliders to open a popup to change the margins either symmetrically or asymmetrical and projection mode settings are now available per layer in the layer controls widget. Run Scripts by Dragging and Dropping into the Viewer 🖱️ Scripts can now be run by dragging and dropping them into the viewer (#8135)! This is particularly useful for running napari examples without having to use the command line; you can even run these scripts from the bundled install! This works by adding a .py reader to napari's builtins. Windows: Access ~~Denied~~ Fixed 🪟 A critical Windows-specific bug that caused Access Violation errors has been resolved (#8122)! This longstanding issue would cause napari to stop displaying layers due to various events and often occurred at seemingly non-reproducible times, and required a full restart of napari. The fix ensures proper cleanup and syncing of GPU resources, also reducing memory usage on all platforms. If you were an effected user, you may recall it as Access Violation, 0x000000000000001C if triggered without a plugin, or 0x000000000000034C if triggered with a plugin. Improved PySide6 Support 🛠️ Napari now has improved support for PySide6 (#7887). We encourage plugin developers to test against PySide6, as a fully supported backend going forward. Additionally, this change will enable us to drop PySide2 along side Python 3.10, in the near future. If you are a plugin developer or otherwise depend on napari and PySide2, please reach out on Zulip or Github. New Features Qt controls for thick slicing (#6146) Add automatic area and perimeter measurement for shapes + action (#7262) Add 'zoom-box' to the viewer (#8004) Add viewbox coordinates to events and Cursor (#8130) feat: Add option to execute python code by drag'n'drop script to viewer (#8135) Improvements Allow use functions from PartSegCore-compiled-backend as numba alternative for data to texture mapping (#6617) Enable testing on recent PySide6 (#7887) Implement pasting spatial information into higher dimensions (#7973) Improve performance and memory usage of editing Shapes layer (#8006) Colorblind friendly image sample of kidney and lily (#8090) Added fixed seed and tested the value. (#8097) Add alpha to split rgba into channels and remerge image. (#8112) Add keybinding (CtrlCmd-up/down) to select layer above/below (#8119) Do not calculate projection on slices of thickness 1 (#8157) Add variables from drag and drop to console (#8174) Performance Allow use functions from PartSegCore-compiled-backend as numba alternative for data to texture mapping (#6617) Bug Fixes ensure sync when taking a screenshot (#8064) Updated code to use current symbol and border width for new points. (#8102) Improve performance and memory usage of editing Shapes layer (#8006 again) (#8109) Add alpha to split rgba into channels and remerge image. (#8112) Prevent Windows Access Violation with GPU resource cleanup on layer removal (#8122) Only use scale to transform margins in thick slices (#8137) Fix scalebar behaviour at high/low zoom (#8144) Ensure contrast limits are computed on original dtype with projected thick slices (#8149) Fix multiscale clim estimation by using full visible data, not first row (#8152) Remove np.asarray(self.cursor._view_direction) that return unbound array (#8172) API Changes Add viewbox coordinates to events and Cursor (#8130) Documentation Update docs constraints and pyprojecttoml for npe2 (#8075) Typo ismhow -> imshow (#8084) Replace deprecated view_*() method from examples (#8091) Comment the HEX codes of each color theme and where they're used (#8099) New example for affine transformations in 3D using meshio and stl (#8103) Added a try it out now section to README.md for using uv. (#8107) Update README wording about scikit-image example (#8125) Add example for grid mode. (#8131) Update xarray_nD_image_.py to use xarray tag (#8167) Autogenerate images of parts of the viewer (docs#621) Update instructions on how to update constraints files (docs#672) Updates to NAP-9: Multiple Views (docs#730) Update guides.md to add menu contribution guide (docs#747) Update building your first plugin guide (docs#753) Update version switcher for 0.6.2 (docs#754) Update Release Guide (docs#755) Fix information about site-packages directory (docs#756) Add empty release notes for 0.6.3 (docs#757) Add roadmap to sidebar links (docs#760) Refactor contributing guide landing page (docs#761) Reorganize homepage with grid columns (docs#767) Fix sidebar roadmap link (docs#768) Fix Image Annotation example (docs#777) Add website colors to community resources (docs#779) Update napari.org homepage to remove the imshow "button" (docs#780) Add instructions for headless docs build on Wayland (docs#781) Add module docstrings to scripts (docs#787) Update pre-commit config to add some python checkers (docs#788) Group event docs in order (docs#789) Add 0.6.3 release notes draft for release candidate (docs#792) Add docs for thick slicing (docs#794) Minor roadmap update (docs#795) Add "feature highlights" page (docs#796) Add introductory paragraph to starting an event loop api doc (docs#797) Update title of event loop api page for discoverability of napari.run (docs#799) Improve API docs for view_* pending removal in 0.7 (docs#800) Update 0.6.3 release notes (docs#803) Drag and drop python scripts (docs#805) Add Carol Willing to list of core developers in documentation (docs#806) Update announcement and version switcher (docs#807) Other Pull Requests Move export ROI and export figure implementations into QtViewer (#7950) [pre-commit.ci] pre-commit autoupdate (#8062) Block the recent pytest-qt version on python 3.10 to keep PySide2 support in testing. (#8067) Add configurable suffix for test artifacts (#8069) Update coverage, hypothesis, ipython, pillow, psygnal, pytest-qt, tensorstore, xarray (#8073) [pre-commit.ci] pre-commit autoupdate (#8074) Move non-qt file actions from qactions module (#8076) Move more view actions from qaction to actions (#8077) Report benchmark on non skipped status (#8086) Enable SIM117 ruff rule (#8088) Remove dotenv from dev dependencies (#8089) Add deprecation warning for view_<layer_type> functions (#8092) Revert #8006 Improve performance and memory usage of editing Shapes layer (#8104) Improve stability of tests by ensuring cleaning of QtViewer instances (#8113) Do not crash test with leaked graph if test failed (#8123) [pre-commit.ci] pre-commit autoupdate (#8124) Cleanup of test_qt_utils.py (#8129) Small fix to shapes measurement (#8133) Update Citation file for 0.6.1 through 0.6.3 (#8138) Slightly increase pip test workflow timeout (#8143) Use pytest-rerunfailures for flaky test_toggle_fullscreen_from_maximized test (#8151) [pre-commit.ci] pre-commit autoupdate (#8158) Move scalar field _slice machinery to proper module and update naming (#8164) Fix reporting python version in benchmark bug reports (#8169) Clean benchmark logs by using the non-deprecated layer-adding method (#8170) Update list of affiliation of Grzegorz Bokota (#8179) Update triggered_target_build.yml regex to ensure we match on hyphen (docs#764) Pin Github Actions actions to their hashes (docs#804) 15 authors added to this release (alphabetical) (+) denotes first-time contributors 🥳 Andrew - @ahuang11 + Carol Willing (docs) - @willingc Filippo Balzaretti (docs) - @FilBalza + Grzegorz Bokota (docs) - @Czaki Ian Coccimiglio - @ian-coccimiglio + jaime rodraguez-guerra - @jaimergp Juan Nunez-Iglesias - @jni Kanai Potts - @8bitbiscuit + Lorenzo Gaifas (docs) - @brisvag Lukasz Migas - @lukasz-migas Melissa Weber Mendonça - @melissawm Peter Sobolewski (docs) - @psobolewskiPhD Rahul Kumar - @rahul713rk rwkozar - @rwkozar Tim Monko (docs) - @TimMonko 18 reviewers added to this release (alphabetical) (+) denotes first-time contributors 🥳 andrew sweet - @andy-sweet Carol Willing (docs) - @willingc Constantin Aronssohn - @cnstt Daniel Althviz Moré - @dalthviz Davis Bennett - @d-v-b Draga Doncila Pop - @DragaDoncila Grzegorz Bokota (docs) - @Czaki Jacopo Abramo - @jacopoabramo jaime rodraguez-guerra - @jaimergp Juan Nunez-Iglesias - @jni Lorenzo Gaifas (docs) - @brisvag Lukasz Migas - @lukasz-migas Melissa Weber Mendonça - @melissawm Peter Sobolewski (docs) - @psobolewskiPhD Rahul Kumar - @rahul713rk rwkozar - @rwkozar Tim Monko (docs) - @TimMonko Wouter-Michiel Vierdag - @melonora

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Communication savante, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,085
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0020,000
Science ouverte0,0030,003
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0050,008

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,027
Tête enseignante GPT0,263
Écart entre enseignants0,236 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2025
Routes d'admission1
Résumé présentoui

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