[PR #2521] Add Slideflow #1840

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GiteaMirror · 2025-11-06T13:24:15-06:00

GiteaMirror commented

2025-11-06 13:24:15 -06:00

📋 Pull Request Information

Original PR: https://github.com/vinta/awesome-python/pull/2521
Author: @prajvalmohan23
Created: 10/3/2023
Status: 🔄 Open

Base: master ← Head: master

📝 Commits (1)

5674557 Add Slideflow

📊 Changes

1 file changed (+1 additions, -0 deletions)

View changed files

📝 README.md (+1 -0)

📄 Description

What is this Python project?

Slideflow is a deep learning library for digital pathology that provides a unified API for building, training, and testing models using Tensorflow or PyTorch.

Slideflow includes tools for whole-slide image processing, customizable deep learning model training with dozens of supported architectures, multi-instance learning, self-supervised learning, cell segmentation, explainability tools (including heatmaps, mosaic maps, GANs, and saliency maps), analysis of layer activations, uncertainty quantification, and more.

What's the difference between this Python project and similar ones?

Slideflow is a one-of-a-kind library in this field and I haven't come across a similar one with this level of robustness. A variety of fast, optimized whole-slide image processing tools are included, including background filtering, blur/artifact detection, stain normalization/augmentation, and efficient storage in *.tfrecords format. Model training is easy and highly configurable, with a straightforward API for training custom architectures. Slideflow can also be used as an image processing backend for external training loops, serving optimized tf.data.Dataset or torch.utils.data.DataLoader to read and process slide images and perform real-time stain normalization.

--

Anyone who agrees with this pull request could submit an Approve review to it.

_{🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.}

## 📋 Pull Request Information **Original PR:** https://github.com/vinta/awesome-python/pull/2521 **Author:** [@prajvalmohan23](https://github.com/prajvalmohan23) **Created:** 10/3/2023 **Status:** 🔄 Open **Base:** `master` ← **Head:** `master` --- ### 📝 Commits (1) - [`5674557`](https://github.com/vinta/awesome-python/commit/567455725eb5bba90a863676e37045d1ae341cd2) Add Slideflow ### 📊 Changes **1 file changed** (+1 additions, -0 deletions) <details> <summary>View changed files</summary> 📝 `README.md` (+1 -0) </details> ### 📄 Description ## What is this Python project? **[Slideflow](https://github.com/jamesdolezal/slideflow)** is a deep learning library for digital pathology that provides a unified API for building, training, and testing models using Tensorflow or PyTorch. Slideflow includes tools for [whole-slide image processing](https://slideflow.dev/slide_processing), customizable deep learning [model training](https://slideflow.dev/training) with dozens of supported architectures, [multi-instance learning](https://slideflow.dev/mil), [self-supervised learning](https://slideflow.dev/ssl), [cell segmentation](https://slideflow.dev/cellseg), explainability tools (including [heatmaps](https://slideflow.dev/evaluation/#heatmaps), [mosaic maps](https://slideflow.dev/posthoc/#mosaic-maps), [GANs](https://slideflow.dev/stylegan/), and [saliency maps](https://slideflow.dev/saliency/)), analysis of [layer activations](https://slideflow.dev/posthoc/), [uncertainty quantification](https://slideflow.dev/uq/), and more. ## What's the difference between this Python project and similar ones? Slideflow is a one-of-a-kind library in this field and I haven't come across a similar one with this level of robustness. A variety of fast, optimized whole-slide image processing tools are included, including background filtering, blur/artifact detection, [stain normalization/augmentation](https://slideflow.dev/norm), and efficient storage in *.tfrecords format. Model training is easy and highly configurable, with a straightforward API for training custom architectures. Slideflow can also be used as an image processing backend for external training loops, serving optimized tf.data.Dataset or torch.utils.data.DataLoader to read and process slide images and perform real-time stain normalization. -- Anyone who agrees with this pull request could submit an *Approve* review to it. --- <sub>🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.</sub>

GiteaMirror added the pull-request label 2025-11-06 13:24:15 -06:00

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Reference: github-starred/awesome-python#1840