.. slideflow documentation master file
.. figure:: https://i.imgur.com/YrsKN4I.jpeg
Slideflow Documentation
=======================
Slideflow is a Python package that provides a unified API for building and testing deep learning models for histopathology, supporting both Tensorflow/Keras and PyTorch.
Slideflow includes tools for efficient whole-slide image processing, easy and highly customizable model training with uncertainty quantification (UQ), and a number of functional tools to assist with analysis and interpretability, including predictive heatmaps, mosaic maps, GANs, saliency maps, and more. It is built with both `Tensorflow/Keras `_ and `PyTorch `_ backends, with fully cross-compatible TFRecord data storage.
This documentation starts with a high-level overview of the pipeline and includes examples of how to perform common tasks using the ``Project`` helper class. We also provide several tutorials with examples of how Slideflow can be used and extended for additional functionality.
.. toctree::
:maxdepth: 1
:caption: Introduction
installation
overview
quickstart
project_setup
datasets_and_val
slide_processing
training
evaluation
posthoc
uq
mil
ssl
stylegan
saliency
segmentation
cellseg
custom_loops
studio
troubleshooting
.. toctree::
:maxdepth: 1
:caption: Developer Notes
tfrecords
dataloaders
custom_extractors
tile_labels
.. toctree::
:maxdepth: 1
:caption: API
slideflow
project
dataset
dataset_features
heatmap
model_params
mosaic
slidemap
biscuit
slideflow_cellseg
io
io_tensorflow
io_torch
gan
grad
mil_module
model
model_tensorflow
model_torch
norm
simclr
slide
slide_qc
stats
util
studio_module
.. toctree::
:maxdepth: 1
:caption: Tutorials
tutorial1
tutorial2
tutorial3
tutorial4
tutorial5
tutorial6
tutorial7
tutorial8