histolablisted

# Histolab ## Overview Histolab is a Python library for processing whole slide images (WSI) in digital pathology. It automates tissue detection, extracts informative tiles from gigapixel images, and prepares datasets for deep learning pipelines. The library handles multiple WSI formats, implements sophisticated tissue segmentation, and provides flexible tile extraction strategies. ## Installation Install OpenSlide system libraries first ([OpenSlide download](https://openslide.org/download/)), then install histolab: ```bash uv pip install histolab ``` For built-in TCGA sample slides via `histolab.data`, also install pooch: ```bash uv pip install pooch ``` Histolab 0.7.0 (latest stable) supports Python 3.8–3.11 on Linux and macOS. Windows is not supported as of 0.7.0. ## Quick Start Basic workflow for extracting tiles from a whole slide image: ```python from histolab.slide import Slide from histolab.tiler import RandomTiler # Load slide slide = Slide("slide.svs", processed_path="output/") # Configure tiler tiler = RandomTiler( tile_size=(512, 512), n_tiles=100, level=0, seed=42 ) # Preview tile locations tiler.locate_tiles(slide, n_tiles=20) # Extract tiles tiler.extract(slide) ``` ## Core Capabilities Six capability areas, each with worked code, are documented in [references/core_capabilities.md](references/core_capabilities.md): 1. **Slide management** — opening slides, properties, levels, thumbnails, and scaled images. 2. **Tissue detection