Python bindings of BioPB: open protobuf/gRPC protocols for biomedical image processing
Project description
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)
docker run -d --rm \
--name tensor-server \
-p 8814:8814 \
-p 8815:8815 \
-v ${DIR_YOUR_DATA}:/data \
jiyuuchc/biopb-tensor-server:latest
Biopb-Image
Deploy complex image processing algorithms (e.g., large deep-learning models) on the network as services. Pre-built containers for popular algorithms (e.g., segmentation) included. 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. Play around in jupyter notebook etc.
Python
pip install biopb[tensor]
Java
<dependency>
<groupId>io.github.jiyuuchc</groupId>
<artifactId>biopb</artifactId>
<version>CURRENT_VERSION</version>
</dependency>
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