SpatialProteomicsNet: A unified interface for spatial proteomics data access for computer vision and machine learning

`SpatialProteomicsNet` is an open-source Python package that provides a harmonized and standardized interface for accessing spatial proteomics and multiplexed imaging datasets, including imaging mass cytometry (IMC) and multiplexed ion beam imaging time-of-flight (MIBI-TOF) data. The package enables researchers to load raw spatially-resolved proteomics data from multiple studies in a unified format, apply and retrieve data structures ready for downstream machine learning analysis or model training. By focusing on open-source raw data processing and enforcing common data schemas (e.g., standardized image and single-cell data formats), `SpatialProteomicsNet` promotes reproducible and efficient research in computational and spatial biology. The library is designed to serve the broader community working on spatial proteomics by easing data access and integration into machine learning workflows.