LSHBOX

Implements eight LSH variants including Random Hyperplane, p-Stable, and Spectral Hashing, providing a wide range of techniques for different use cases.

Offers native C++ interfaces with Python and MATLAB bindings, enabling integration into diverse development environments without rewriting core logic.

Supports saving and loading hash indexes to disk, allowing faster subsequent queries by avoiding re-indexing, as demonstrated in the Python and MATLAB examples.

Uses a compact binary format for datasets, improving I/O performance and reducing memory footprint, though it requires specific preprocessing.

Each algorithm exposes parameters like hash table size and binary code length for fine-grained control over accuracy-speed trade-offs, as detailed in the algorithm chapters.