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 ```bash uv pip install histolab ``` ## 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 ### 1. Slide Management Load, inspect, and work with whole slide images in various formats. **Common operations:** - Loading WSI files (SVS, TIFF, NDPI, etc.) - Accessing slide metadata (dimensions, magnification, properties) - Generating thumbnails for visualization - Working with pyramidal image structures - Extracting regions at specific coordinates **Key classes:** `Slide` **Reference:** `references/slide_management.md` contains comprehensive documentation on: - Slide initialization and configuration - Built-in sample datasets (prostate, ovarian, breast, heart, kidney tissues)