A Blender addon for parametric 3D head generation using the GNM Head model. Designed for high performance, real-time viewport mesh updates, and an optimized WETWARE integration.
- Performance-driven: Operates exclusively via native NumPy operations.
- Zero Bloatware: Completely bypasses heavy neural network frameworks (e.g., Keras/TensorFlow).
- Semantic Mapping Engine: Uses a descriptive key-based mapping system to translate complex mathematically entangled PCA vectors into user-friendly attributes.
The project is currently at 5% completion. The core engine is functional and capable of generating basic mesh variations. The ongoing task involves the empirical reverse engineering and semantic cataloging of 253 PCA components to populate the data structure without causing topology instability.
The process of isolating, evaluating, and compiling synergistic transition vectors into a stable mapping matrix is highly time-consuming. You can support the continuous development and optimization of this tool through Ko-fi.
