biopb 0.5.3

Python bindings of BioPB: open protobuf/gRPC protocols for biomedical image processing

BioPB

Distributed computing for bio-imaging data.

BioPB provides a standardized way to share multi-dimensional microscopy datasets, analysis algorithms, and computational results in a network-transparent and language-agnostic manner.

Biopb-Tensor

A blazing-fast microscopy data server for sharing your lab's petabyte-scale datasets to team members and/or collaborators. Read More...

• Uniform Representation: all source data mapped to a multi-resolution and lazy-read array for client access
• Multi-language: dask array for Python and ImgLib2.CellImg for Java
• Thread-safe & Serializable: compatible with dask.distribute for distributed computing on larger-than-memory dataset
• Metadata Server: full DuckDB SQL support to query your embedded metadata
• On-the-fly Build: keep your data in original format (.zvi, ndtiff etc). No staging or on-boarding process needed
• Built-in Viewer: browse all your data with any browser (e.g., on an ipad)

Quick Start

# Ports: 8814 (browser), 8815 (data)
# Dev mode with localhost-only access (no token required)
docker run --rm \
  --name tensor-server \
  -e BIOPB_WEB_DEV_BYPASS=1 \
  -p 127.0.0.1:8814:8814 \
  -p 127.0.0.1:8815:8815 \
  -v ${DIR_YOUR_DATA}:/data \
  jiyuuchc/biopb-tensor-server:latest

Point your browser to http://localhost:8814

Biopb-Image

Deploy complex image processing algorithms (e.g., large deep-learning models) on the network as services, including pre-built containers for popular algorithms (e.g., segmentation). Read More...

Napari-Biopb

GUI app for the end-users. The power of biopb in a familiar interface. Read More...

SDK

Schema, utilities and cli for building your own workflow. Explore your data in jupyter notebook etc.

Python

pip install biopb[tensor]

Java

<dependency>
  <groupId>io.github.jiyuuchc</groupId>
  <artifactId>biopb</artifactId>
  <version>CURRENT_VERSION</version>
</dependency>