Reverse Dependencies of tensorstore

The following projects have a declared dependency on tensorstore:

• ac-segmentation — Segmentation for Axonal Connectomics
• aind-segmentation-evaluation — Python package for evaluating neuron segmentations in terms of the number of splits and merges
• anndata-tensorstore — Anndata Tensorstore Extension: Save and Load anndata to/from Tensorstore for random access
• axlearn — AXLearn
• cellmap-flow — Realtime prediction using neuroglancer
• czpeedy — A command-line tool used to determine the tensorstore settings which yield the fastest write speed on a given machine.
• detkit — Matrix determinant toolkit
• dexp — Light-sheet Dataset EXploration and Processing
• enformer-dna-diff — This is a package for that combines DeepMind Enformer model with DNA Diffusion project
• finn-viewer — n-dimensional array viewer for cell tracking data in Python
• flashbax — Flashbax is an experience replay library oriented around JAX. Tailored to integrate seamlessly with JAX's Just-In-Time (JIT) compilation.
• flax — Flax: A neural network library for JAX designed for flexibility
• git-theta — Version control system for machine learning model checkpoints.
• levanter — Scalable Training for Foundation Models with Named Tensors and JAX
• matchviz — no summary
• megatron-core — Megatron Core - a library for efficient and scalable training of transformer based models
• microsim — Light microscopy simulation in python
• napari — n-dimensional array viewer in Python
• napari-activelearning — An active learning plugin for fine tuning of deep learning models.
• ndv — Simple, fast-loading, n-dimensional array viewer, with minimal dependencies.
• nemo-toolkit — NeMo - a toolkit for Conversational AI
• neuroflex — An advanced neural network framework with interpretability, generalization, robustness, and fairness features
• ngff-zarr — A lean and kind Open Microscopy Environment (OME) Next Generation File Format (NGFF) Zarr implementation.
• ome2024-ngff-challenge — Tools for converting OME-Zarr data within the ome2024-ngff-challenge (see https://forum.image.sc/t/ome2024-ngff-challenge/97363)
• orbax — Orbax
• orbax-checkpoint — Orbax Checkpoint
• paxml — Framework to configure and run machine learning experiments on top of Jax.
• pymmcore-plus — pymmcore superset providing improved APIs, event handling, and a pure python acquisition engine
• segmentation-skeleton-metrics — Python package for evaluating neuron segmentations in terms of the number of splits and merges
• softcopy — Copies zarr archives from an acquisition frontend to a different disk, using filesystem watching and lockfiles to allow copying during acquisition.
• stars-omics — A spatial transcriptomics analysis tool.
• syml-ultralytics — Ultralytics YOLO 🚀 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• tensorstore-stubs — Type stubs for tensorstore
• tractorun — Run distributed training in TractoAI
• tsconcat — A tool for joining multiple, homogeneous tensorstore datasets using the N5 driver into a single dataset.
• UltraDetect — Customized Ultralytics YOLO for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• ultralytics — Ultralytics YOLO 🚀 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• ultralytics-export-to-rknn — Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• ultralytics-v11 — Ultralytics YOLO for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• ultralyticsheadless — Ultralytics YOLO 🚀 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• vesuvius — no summary
• vsensebox-ultralytics — Ultralytics YOLO for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• webknossos — Python API for working with WEBKNOSSOS datasets, annotations, and for WEBKNOSSOS server interaction.
• xarray-tensorstore — no summary
• zarpaint — Paint segmentations directly to on-disk/remote zarr arrays