Pathml

If you're building ML pipelines for digital pathology, this gives you the full stack: load 160+ slide formats (Aperio SVS, NDPI, DICOM), run stain normalization and tissue detection, train models like HoVer-Net for nucleus segmentation, and analyze multiplex imaging data from CODEX or Vectra. It's genuinely comprehensive, with modular preprocessing pipelines, spatial graph construction for cellular relationships, and proper HDF5 storage for large datasets. The documentation is thorough across six capability areas. Main appeal is avoiding the usual format hell and preprocessing boilerplate when working with whole-slide images, though you'll need to invest time learning the API if you're just doing simple tasks.

skills.sh installs: 207
GitHub stars: 33.2K
last updated: Aug 21, 2026

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Install

$ npx -y skills add davila7/claude-code-templates --skill pathml --agent claude-code

Installs into .claude/skills of the current project.

Files

PathML

Overview

PathML is a comprehensive Python toolkit for computational pathology workflows, designed to facilitate machine learning and image analysis for whole-slide pathology images. The framework provides modular, composable tools for loading diverse slide formats, preprocessing images, constructing spatial graphs, training deep learning models, and analyzing multiparametric imaging data from technologies like CODEX and multiplex immunofluorescence.

When to Use This Skill

Apply this skill for:

Loading and processing whole-slide images (WSI) in various proprietary formats
Preprocessing H&E stained tissue images with stain normalization
Nucleus detection, segmentation, and classification workflows
Building cell and tissue graphs for spatial analysis
Training or deploying machine learning models (HoVer-Net, HACTNet) on pathology data
Analyzing multiparametric imaging (CODEX, Vectra, MERFISH) for spatial proteomics
Quantifying marker expression from multiplex immunofluorescence
Managing large-scale pathology datasets with HDF5 storage
Tile-based analysis and stitching operations