Stars
Fast, accurate & comprehensive text measurement & layout
MMV-Lab / Agentic-J
Forked from LJMedPhys/Imagent_JAI agent for Microscopy Image Analysis
Image reading, metadata management, and image writing for Microscopy images in Python
tlambert03 / ome-types
Forked from imaging-formats/ome-typesnative Python dataclasses for the OME data model
Next-generation file format (NGFF) specifications for storing bioimaging data in the cloud.
A napari plugin for zarr backed OME-NGFF images
Implementation of next-generation file format (NGFF) specifications for storing bioimaging data in the cloud.
A high-level plotting API for pandas, dask, xarray, and networkx built on HoloViews
Face and iris detection for Python based on MediaPipe
Revision of the HSI_crops_clustering repo by DBP008 for my master's thesis in physics.
Comprehensive optical design, optimization, and analysis in Python, including GPU-accelerated and differentiable ray tracing via PyTorch.
🚀2.3x faster than MinIO for 4KB object payloads. RustFS is an open-source, S3-compatible high-performance object storage system supporting migration and coexistence with other S3-compatible platfor…
Browse, share, and publish OME-Zarr data
DeepInverse: a PyTorch library for solving imaging inverse problems using deep learning
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
Interactive notebook with presentation style about the abstrac and applied understandig of Persistent Homology
one summary of diffusion-based image processing, including restoration, enhancement, coding, quality assessment
The interactive graphing library for Python ✨
A deep-learning library for denoising images using Noise2Void and friends, with a focus on user-experience and documentation.)
A novel CNN called the 3-D Hyper-UNET for Hyperspectral Image Segmentation.
Open source tools for computational pathology - Nature BME
A collection of resources on applications of multi-modal learning in medical imaging.