Whole-slide image streamer for TensorFlow.
Project description
histomics_stream
Overview
The goal of this project is to create a whole-slide image file reader for machine learning with TensorFlow. This reader will allow users to extract pixel data from whole-slide image formats, and will support reading paradigms that are commonly used during training and inference.
Installation for Python
histomics_stream can be easily installed with Python wheels. If you do not want the installation to be to your current Python environment, you should first create and activate a Python virtual environment (venv) to work in. Then, run the following from the command line:
pip uninstall -y large_image tensorflow histomics_stream
pip install 'large_image[all]' --find-links https://girder.github.io/large_image_wheels
pip install histomics_stream
Launch python3
, import the histomics_stream package, and use it
import histomics_stream as hs
This has been tested with tensorflow:2.6.2-gpu
.
History
Through version 1.0.6, this project was known as tensorflow_reader.
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 histomics_stream-2.1.2-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b3f584af9ab17358c95e4a21711645ac1f9fbdb0d6de52ba7672c798fa57d574 |
|
MD5 | fc51b50bd42faf3011160cc137f60f79 |
|
BLAKE2b-256 | 3a84135236b03973d517b8f9e7bf6fd15fa1e77bab298faf80854d11552b5a33 |