1.2.0

v1.2.0 — Semantic Segmentation

This release adds support for dense prediction (semantic segmentation) tasks, extending soma beyond tile/slide/patient-level classification.

Highlights

• Semantic segmentation pipeline (#69) — frozen foundation-model encoders produce dense token grids (via slide2vec) consumed by a new swappable decoder component that maps features to per-pixel predictions.
• Spacing-aware reading + live re-encode + window-as-knob sliding (#71) — spacing-aware tile reads, on-the-fly re-encoding, and sliding-window inference where the window size is a tunable knob for dense segmentation.

Notes

This is the first segmentation release and the feature set will continue to expand in future versions.