scivision
Project description
A Toolkit for Scientific Image Analysis
scivision
aims to be a well-documented and generalisable Python framework for applying computer vision methods to a wide range of scientific imagery.
This tool aims to foster collaboration between data owners and developers by:
- Empowering scientific domain experts to easily access and integrate the latest CV tools
- Enabling algorithm developers to distribute their tools to users across scientific fields
- Evolving with a focus on the needs and priorities of both developers and users
- Creating and maintaining a community of interdisciplinary contributors
- Providing a bridge between different data scales and formats
📗 Table of contents
🐨 Installation
-
Install scivision via PyPi: which tends to be the most user-friendly option:
pip install scivision
-
Install scivision from the source code:
- Clone scivision source code:
git clone https://github.com/alan-turing-institute/scivision.git
- Install scivision and its dependencies:
cd /path/to/my/scivision pip install -v -e .
🤔 Contributing
See the Contributing Guide on readthedocs, which contains information on how to set up and contribute computer vision models and scientific image datasets to the scivision catalog, and make them available via the scivision python API, as well as modify the source code.
You may consider starting or joining in with a discussion, or opening an issue in this GitHub repo.
📚 Documentation
In in addition to the Contributing Guide, the readthedocs website contains information about using the scivision python package API and updating the scivision catalog.
It also includes our maintainer documentation, which explains how to update the scivision package on PyPI and update the documentation.
📒 Demo notebook
To understand how scivision works, we recommend reading the documentation linked above, but you can also view an interactive demonstration here:
Note: if you have this repo cloned you can also look directly at the examples folder, which includes this Jupyter notebook.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for scivision-0.1.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3497a4e0024d652f6fe89868a7d1b9ea0959777f1baddbfcf08413907ac7a826 |
|
MD5 | fa3d1b9ae1142e4db509b4f4ab95687e |
|
BLAKE2b-256 | 6f5f1df3dff6fbefdcc652204b284ce4de80b70cc61e7aec36dcbbe320e78e58 |