Reverse Dependencies of imagecodecs

The following projects have a declared dependency on imagecodecs:

• aicsimageio — Image Reading, Metadata Conversion, and Image Writing for Microscopy Images in Pure Python
• aideml — Autonomous AI for Data Science and Machine Learning
• aind-large-scale-prediction — Generated from aind-library-template
• aiocogeo — Asynchronous cogeotiff reader
• apeer-ometiff-library — Library to read and write ometiff images
• arraylake — Python client for ArrayLake
• aydin — Aydin - Denoising but chill
• batoolset — An aggregate of functions I find useful
• bellavista — Python package for interactive visualization of imaging-based spatial transcriptomics.
• bfio — Simple reading and writing classes for tiled tiffs using Bio-Formats.
• biapy — BiaPy: Bioimage analysis pipelines in Python
• bioimageloader — load bioimages for machine learning
• bioio-ome-tiff — A BioIO reader plugin for reading tiff files in the OME format.
• bioio-tifffile — A BioIO reader plugin for reading TIFFs using Tifffile
• bipl — Openslide/libtiff/GDAL ndarray-like interface and lazy parallel tile-based processing
• cdb-cellmaps — no summary
• cell-bin — A framework for generating single-cell gene expression data
• Cellan — Analyze cell images.
• celldega — no summary
• cellpose — anatomical segmentation algorithm
• cellpose-napari — a generalist algorithm for anatomical segmentation
• cellpose-omni — cellpose fork developed for omnipose
• cellpose-omni-acdc — cellpose fork developed for omnipose
• cellpose-plus — cell segmentation framework based on cellpose
• cellpose-vollseg — modification of cellpose algorithm
• cgohlke — Install all packages by cgohlke
• clickpoints — Scientific toolbox for manual and automatic image evaluation.
• cloud-volume — A serverless client for reading and writing Neuroglancer Precomputed volumes both locally and on cloud services.
• CloudReg — Automatic terabyte-scale cross-modal brain volume registration
• cmapfile — Write Chimera Map (CMAP) files
• competitionassay — Software for the analysis of competition assay data.
• confluentfucci — no summary
• COPEX-high-rate-compression-quality-metrics — COPEX high rate compression quality metrics
• crl-datacube — Utilities for scaling geospatial analyses
• cryohub — IO hub for Cryo-EM, Cryo-ET and subtomogram averaging data.
• CytoDataFrame — An in-memory data analysis format for single-cell profiles alongside their corresponding images and segmentation masks.
• czifile — Read Carl Zeiss Image (CZI) files
• dcclab — A Python library to read, transform, manipulate images and manage databases
• deepflash2 — A Deep learning pipeline for segmentation of fluorescent labels in microscopy images
• depalma-napari-omero — Napari interface for the De Palma lab.
• descarteslabs — Descartes Labs Python Client
• descarteslabs-dynamic-compute — no summary
• detectda — detectda - detecting features in videos using TDA
• dosertools — dosertools is a Python package for analyzing dripping-onto-substrate extensional rheology (DoSER) videos.
• easyidp — A handy tool for dealing with region of interest (ROI) on the image reconstruction (Metashape & Pix4D) outputs, mainly in agriculture applications
• educelab-imgproc — EduceLab image processing module
• eerfile — Read electron event representation (EER) files in Python
• ellipsis — Package to interact with the Ellipsis API
• empanada-dl — Algorithms for Panoptic Segmentation of organelles in EM
• empanada-napari — Napari plugin of algorithms for Panoptic Segmentation of organelles in EM
• enact-SO — ENACT is a self-contained pipeline designed to streamline Visium HD analysis from cell segmentation to annotation, enabling integration with advanced spatial analysis tools.
• epicure — Napari plugin to manually correct epithelia segmentation in movies
• eQuimage — eQuimage is a tool to postprocess astronomical images from Unistellar telescopes.
• eQuimageLab — eQuimageLab is a tool to postprocess astronomical images with JupyterLab notebooks
• eyepie — A python package to read, analyse and visualize OCT and fundus data form various sources.
• eyepy — A python package to read, analyse and visualize OCT and fundus data form various sources.
• farmlayers — Helper scripts for fetching and managing basic input layers Farm Mapping
• fibresem — A small package to automate the SEM analysis of fibrous meshes
• fibsem-tools — Tools for processing FIBSEM datasets
• FiReTiTiPyLib — Python libraries used as support/tools.
• Foscat — Generate synthetic Healpix or 2D data using Cross Scattering Transform
• frmodel — The base package to support frmodel data processing
• generate-dense-patches — A simple plugin to create a lot of training data from a 3D volume and mask
• graphite-datasets — tensorflow/datasets is a library of datasets ready to use with TensorFlow.
• harmony-to-organoid — Utility for extracting individual organoid max projections from the export of Opera Phenix Harmony software.
• HealpixML — Package adapted for Machine Learning on the Healpix grid.
• herbs — A Python-based GUI for Histological E-data Registration in Brain Space
• hestcore — no summary
• histo-patch — histopatch: image patch extraction from Whole Slide Images
• histo-tools — General histology tools.
• histomics_stream — Whole-slide image streamer for machine learning frameworks.
• hmsm — Tools for image based digitization of historical music storage media
• imagecodecs-lite — The imagecodecs-lite package is deprecated. Use the imagecodecs package instead.
• imagecodecs-numcodecs — Numcodecs entry points for the imagecodecs package
• imagery24 — A short description of your package
• imaxt-image — IMAXT Image Utilities
• imctools — Tools to handle Fluidigm IMC data
• imppy3d — IMPPY3D: A library for processing 3D image stacks
• instanseg-torch — Package for instanseg-torch PyPi
• ipp-toolkit — A general framework for informative path planning experiments, with a focus on wrapping datasets, sensors, planners, and visualization in a modular manner
• jcell — Software package for training and testing deep learning based method applied to image segmentation
• jcell-ISBI — Software package for training and testing deep learning based method applied to image segmentation
• jinxif — A python3-based image analysis package to achieve fully-documented and reproducible visualization and analysis of bio-medical microscopy images. This is a fork from Jennifer Eng`s mplex_image software library.
• jpeg-xl-float-with-nans — JpegXlFloatWithNaNs is a codec for numcodecs for compressing image data in Zarr/Xarray
• lacss — Tools for cell segmentation
• lfdfiles — Laboratory for Fluorescence Dynamics (LFD) file formats
• liffile — Read Leica image files (LIF, LOF, XLIF, XLCF, XLEF, and LIFEXT)
• magellanmapper — 3D atlas analysis and annotation
• maphis — Hierarchical segmentation and extraction of various measurements from photos of (not only) arthropods.
• mapmanagercore — MapManagerCore is a Python library that provides the core functionality for MapManager.
• medvae — MedVAE is a family of six medical image autoencoders that can encode high-dimensional medical images into latent representations.
• MFWS — Multiple Fast Fourier Transform weighted stitching algorithm.
• microscope-napari — Nanobiosensorics microscopic napari plugin.
• MILWRM — Multiplex Image Labeling With Regional Morphology
• minerva-lib — Minerva Python library
• miso — Python scripts for training CNNs for particle classification
• miso2 — Python scripts for training CNNs for particle classification
• monai — AI Toolkit for Healthcare Imaging
• monai-weekly — AI Toolkit for Healthcare Imaging
• morphapi — A lightweight python package to download neuronal morphologies