CNN v2: parametric static features - design doc

Design document for CNN v2 with enhanced feature inputs:
- 7D static features: RGBD + UV + sin encoding + bias
- Per-layer configurable kernels (1×1, 3×3, 5×5)
- Float16 weight storage (~6.4 KB vs 3.2 KB)
- Multi-pass architecture with static feature compute

Implementation plan:
1. Static features compute shader (RGBD + UV + sin + bias)
2. C++ effect class (CNNv2Effect)
3. Training pipeline (train_cnn_v2.py, export_cnn_v2_shader.py)
4. Validation tooling (validate_cnn_v2.sh)

Files:
- doc/CNN_V2.md: Complete technical design (architecture, training, export)
- scripts/validate_cnn_v2.sh: End-to-end validation script
- TODO.md: Add CNN v2 as Priority 2 task
- doc/HOWTO.md: Add CNN v2 validation usage

Target: <10 KB for 64k demo constraint

handoff(Claude): CNN v2 design ready for implementation

0 files changed, 0 insertions, 0 deletions