PySlyde Documentation
A comprehensive Python package for preprocessing pathology whole slide images (WSIs).
PySlyde is built as a wrapper around OpenSlide and provides powerful, user-friendly functionality for working with high-resolution pathology images, making it ideal for researchers and data scientists in the medical imaging domain.
Contents:
Features
WSI Handling: Supports large pathology slides and other WSI formats via OpenSlide
Efficient Preprocessing: Streamline tasks like cropping, resizing, and filtering at high performance
Annotation Support: Easily integrate and visualize annotations from multiple formats (QuPath, ImageJ, ASAP, JSON, CSV)
Tiling and Patching: Flexible tiling options for patch extraction, ideal for deep learning workflows
Image Metadata Extraction: Retrieve and manage metadata from WSIs
Multiple Output Formats: Save processed data to disk, LMDB, or RocksDB databases
Tissue Detection: Automatic tissue region detection and masking
Feature Extraction: Built-in support for extracting features from tiles using pre-trained models
Quick Installation
pip install pyslyde
Quick Example
from pyslyde import Slide, Annotations
# Load a slide with annotations
slide = Slide("path/to/slide.svs")
annotations = Annotations("path/to/annotations.json", source="json")
# Generate tissue mask
mask = slide.generate_mask()
# Extract a region
region, region_mask = slide.generate_region(
x=(1000, 2000),
y=(1500, 2500),
x_size=1000,
y_size=1000
)