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2 daysfeat(cnn_v3): G-buffer phase 1 + training infrastructureskal
G-buffer (Phase 1): - Add NodeTypes GBUF_ALBEDO/DEPTH32/R8/RGBA32UINT to NodeRegistry - GBufferEffect: MRT raster pass (albedo+normal_mat+depth) + pack compute - Shaders: gbuf_raster.wgsl (MRT), gbuf_pack.wgsl (feature packing, 32B/px) - Shadow/SDF passes stubbed (placeholder textures), CMake integration deferred Training infrastructure (Phase 2): - blender_export.py: headless EXR export with all G-buffer render passes - pack_blender_sample.py: EXR → per-channel PNGs (oct-normals, 1/z depth) - pack_photo_sample.py: photo → zero-filled G-buffer sample layout handoff(Gemini): G-buffer phases 3-5 remain (U-Net shaders, CNNv3Effect, parity)
2026-03-05add training photosskal
2026-02-27remove old files, add new training setskal
2026-02-15feat(cnn): add CNN v3 directory structure with training dataskal
Initialize CNN v3 subdirectory with training pipeline layout: - docs/, scripts/, shaders/, src/, tools/, weights/ for organization - training/input/ with sample images - training/target_1/, target_2/ for multi-style training - README.md documenting structure Training images tracked in repo for easy collaboration. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>