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cellcast_python

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This crate contains the Python bindings (via PyO3) for the cellcast core Rust library. Cellcast is a recast of cell segmentation models built on the Burn tensor and deep learning framework. The goal of this project is to modernize (i.e. recast) established cell segmentation models with a WebGPU backend. Cellcast aims to make access to cell segmentation models easy and reproducible.

Installation

Requirements

The cellcast Python package currently supports the following architectures:

Operating System Architecture
Linux x86-64, arm64
macOS intel, arm64
Windows x86-64

Cellcast is compatible with Python >=3.8 and requires only NumPy.

cellcast from PyPI

You can install the cellcast Python package from PyPI with:

$ pip install cellcast

Build cellcast_python from source

To build the cellcat_python package from source, use the maturin build tool (this requires the Rust toolchain). If you're using uv to manage your Python virtual environments (venv) add numpy and maturin to your environment and run the maturin develop command in the cellcast_python directory of the cellcast repository with your venv activated:

$ source ~/path/to/myenv/.venv/bin/activate
$ (myenv) cd cellcast_python
$ maturin develop

Alernatively if you're using conda or mamba you can do the following:

$ cd cellcat_python
$ mamba activate myenv
(myenv) $ mamba install numpy maturin
...
(myenv) $ maturin develop

This will compile a non-optimized cellcast binaries. Pass the --release flag to compile optimized binaries (note that compilation time may take upwards of 10 minutes).

Usage

Using cellcast

The following example demonstrates how to use cellcast's StarDist2D model in Python with fetched versatile fluo pretrained weights (note: here we assume you have your data in a 2D NumPy array):

import cellcast.models.StarDist2D as StarDist2D

# assuming "data" is a 2D NumPy array
sd = StarDist2D.init_fluo(gpu=True)
labels = sd.predict_fluo(data)

Run help() on the predict_fluo() function to see the full function signature and default values. To initialize a model with custom weights, provide the path to the weights in burnpack format (.bpk) when creating a model instance.

sd = StarDist2D.init_fluo("path/to/custom_weights.bpk", True)

License

Cellcast itself is a dual-licensed project with your choice of:

These licenses only apply to the cellcast project and do not apply to the individual models supported by cellcast. You can find each model's associated license listed in the MODEL-LICENSES file.

Metadata

Release files for cellcast 0.3.0

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Source distribution for cellcast 0.3.0
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Table of built distributions (wheels) for cellcast 0.3.0
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cellcast-0.3.0-cp38-abi3-win_amd64.whl CPython 3.8 abi3 Windows x86-64 Details
cellcast-0.3.0-cp38-abi3-manylinux_2_28_aarch64.whl CPython 3.8 abi3 Linux glibc 2.28+ ARM64 Details
cellcast-0.3.0-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.8 abi3 Linux glibc 2.17+ x86-64 Details
cellcast-0.3.0-cp38-abi3-macosx_11_0_arm64.whl CPython 3.8 abi3 macOS 11.0+ ARM64 Details
cellcast-0.3.0-cp38-abi3-macosx_10_12_x86_64.whl CPython 3.8 abi3 macOS 10.12+ x86-64 Details

Total release size: 58.8 MB

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