https://bugs.kde.org/show_bug.cgi?id=518355
--- Comment #2 from Ondrej Zizka <[email protected]> --- Forgive me for thinking architecturally about a project I am still getting to know, but I suspect the current face recognition scaling issues stem from the fundamental choice of KNN/ANN over a centroid-based clustering approach. I am currently importing my family's archive, and the FLANN-based matching degrades noticeably as the number of identities and faces grows. It has reached a point where many faces are assigned to "catch-all" identities—likely nodes near the top of a KD-tree space split—even when very clear training data exists for the correct person. While implementing the request to increase the number of checked neighbors may offer temporary relief, it doesn't solve the underlying complexity. In 128-dimensional space, the KD-trees used by FLANN often lose logarithmic efficiency. Furthermore, rebalancing these structures during face confirmation is computationally expensive; on a high-end workstation with MariaDB, confirming a single face can take 20 seconds. By switching to a multi-cluster centroid model, we would shift the search complexity from being a function of "total faces" to a function of "total identities", where the latter is naturally way lower (at least for a typical personal use). I will be opening a separate feature request to suggest a transition from FLANN to HNSW (Hierarchical Navigable Small World) for the indexing backend. HNSW maintains much better logarithmic performance in high-dimensional spaces and would serve as a more robust foundation for the scaling issues discussed here. To address the storage and portability concerns, especially for SQLite users, digiKam could bundle a lightweight, dependency-free extension like *sqlite-vec*. This would allow SQLite to match the native HNSW vector capabilities of modern MariaDB (11.7+), providing a unified, high-performance indexing backend across both database types. I will be opening a separate feature request to suggest this transition from FLANN to HNSW. -- You are receiving this mail because: You are watching all bug changes.
