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27 hoursCNN v2 Web Tool: Unify layer terminology and add binary format specskal
- Rename 'Static (L0)' → 'Static' (clearer, less confusing) - Update channel labels: 'R/G/B/D' → 'Ch0 (R)/Ch1 (G)/Ch2 (B)/Ch3 (D)' - Add 'Layer' prefix in weights table for consistency - Document layer indexing: Static + Layer 1,2,3... (UI) ↔ weights.layers[0,1,2...] - Add explanatory notes about 7D input and 4-of-8 channel display - Create doc/CNN_V2_BINARY_FORMAT.md with complete .bin specification - Cross-reference spec in CNN_V2.md and CNN_V2_WEB_TOOL.md Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
48 hourstest_demo: Add beat-synchronized CNN post-processing with version selectionskal
- Add --cnn-version <1|2> flag to select between CNN v1 and v2 - Implement beat_phase modulation for dynamic blend in both CNN effects - Fix CNN v2 per-layer uniform buffer sharing (each layer needs own buffer) - Fix CNN v2 y-axis orientation to match render pass convention - Add Scene1Effect as base visual layer to test_demo timeline - Reorganize CNN v2 shaders into cnn_v2/ subdirectory - Update asset paths and documentation for new shader organization Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2 daysUpdate docs and help messages for CNN v2 completionskal
Updated: - HOWTO.md: Complete pipeline, storage buffer, --validate mode - TODO.md: Mark CNN v2 complete, add QAT TODO - PROJECT_CONTEXT.md: Update Effects status - CNN_V2.md: Mark complete, add storage buffer notes - train_cnn_v2_full.sh: Add --help message All documentation now reflects: - Storage buffer architecture - Binary weight format - Live training progress - Validation-only mode - 8-bit quantization TODO
2 daysCNN v2: parametric static features - design docskal
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