ysbecca/py-wsi
Python package for dealing with whole slide images (.svs) for machine learning, particularly for fast prototyping. Includes patch sampling and storing using OpenSlide. Patches may be stored in LMDB, HDF5 files, or to disk. It is highly recommended to fork and download this repository so that personal customisations can be made for your work.
This tool helps scientists and researchers in digital pathology analyze very large whole slide images, often in .svs format. It takes these high-resolution images and extracts smaller, manageable sections (patches) that are suitable for machine learning analysis. The output can be stored efficiently in formats like LMDB, HDF5, or as individual PNG files, making it easier for researchers to process and build models.
164 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to efficiently extract and store specific regions from gigapixel-scale digital pathology slides for machine learning applications.
Not ideal if you primarily work with standard-sized images that can be comfortably loaded into memory or if you don't require specialized handling for whole slide image formats.
Stars
164
Forks
90
Language
Jupyter Notebook
License
GPL-3.0
Category
Last pushed
Jul 25, 2024
Commits (30d)
0
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