demo.git/tools, branch main

style: apply clang-format

2026-05-21T06:10:47Z

ans: order-0 rANS coder + WGSL asset compression

2026-05-14T17:11:28Z

Adds src/util/ans.{h,cc}, a per-chunk-adaptive order-0 rANS entropy coder. Decoder is always built; encoder is gated on ANS_ENABLE_ENCODER (tools only). Both sides take an optional 256-entry initial_counts table to seed the adaptive model. The per-chunk initial state is (1 << kBits). Higher initial states (e.g. with a signature packed into the upper bits) force a renorm-emit at iter 0 that the decoder never consumes, corrupting multi-chunk streams once stats become skewed. Asset pipeline: - AssetRecord gains 'compression' and 'uncompressed_size' fields. - asset_packer scans every WGSL file to build a corpus-wide byte histogram, then ANS-encodes each shader using that histogram as the seed. Histogram and accessor are emitted alongside the asset table. Round-trip verification runs at pack time for every compressed asset; failures fall back to uncompressed storage. - asset_manager decompresses on first GetAsset(), caches the heap-allocated buffer, and DropAsset / ReloadAssetsFromFile free it along with the procedural cache. - Disk-load (dev) builds are unchanged: WGSL paths stay as filenames. Tests: - src/tests/util/test_ans.cc: roundtrip variants (empty, single byte, single-symbol run, all-zeros, random uniform/skewed, repeated ASCII), seeded-vs-uniform compression, rejection of mismatched counts / corruption / truncation, PeekUncompressedSize. - 37/37 dev, 36/36 STRIP_ALL. Compression observed: WGSL shaders shrink to ~0.62-0.71x in the main workspace (81 of 105 assets qualify). Docs: - doc/ANS.md (new): algorithm, bitstream, API, asset pipeline integration, compression numbers, limitations, tests. - doc/ASSET_SYSTEM.md: new Compression section + updated technical guarantees for compressed assets. - doc/COMPLETED.md: May 2026 entry. - PROJECT_CONTEXT.md: Build status line mentions WGSL ANS compression. - CLAUDE.md, GEMINI.md: tier-3 build doc list includes ANS.md.

more 3d assets for cnn_v3

2026-03-29T14:07:09Z

new script

2026-03-29T13:18:54Z

feat(procedural): add plasma, voronoi, normalmap generators

2026-03-29T00:42:28Z

Add three new procedural texture generators: - gen_plasma: classic sine-sum color texture (RGB output) - gen_voronoi: Worley cellular noise (F1/F2/F2-F1 modes) - gen_normalmap: post-process grayscale→RGB normal map Remove gen_noise_256 (was an alias for gen_noise). Register new generators in asset_manager and asset_packer. Add unit tests for all three, and use them in test_3d_render (plasma sky, voronoi noise, fBm normal map). handoff(Gemini): plasma/voronoi/normalmap procedural generators added; gen_noise_256 removed; tests + 3d_render usage wired up.

feat(cnn_v3): add infer_cnn_v3.py + rewrite cnn_test for v3 parity

2026-03-25T07:07:53Z

- cnn_v3/training/infer_cnn_v3.py: PyTorch inference tool; simple mode (single PNG, zeroed geometry) and full mode (sample directory); supports --identity-film (γ=1 β=0) to match C++ default, --cond for FiLM MLP, --blend, --debug-hex for pixel comparison - tools/cnn_test.cc: full rewrite, v3 only; packs 20-channel features on CPU (training format: [0,1] oct normals, pyrdown mip), uploads to GPU, runs CNNv3Effect, reads back RGBA16Float, saves PNG; --sample-dir for full G-buffer input, --weights for .bin override, --debug-hex - cmake/DemoTests.cmake: add cnn_v3/src include path, drop unused offscreen_render_target.cc from cnn_test sources - cnn_v3/docs/HOWTO.md: new §10 documenting both tools, comparison workflow, and feature-format convention (training vs runtime) handoff(Gemini): cnn_test + infer_cnn_v3.py ready for parity testing. Run both with --identity-film / --debug-hex on same image to compare.

add more samples + tool html

2026-03-24T22:14:57Z

move and improve the 'adjust.html' tool

2026-03-24T10:02:36Z

feat(cnn_v3): GBufDeferredEffect — simple deferred render (albedo * shadow)

2026-03-22T18:58:04Z

New effect unpacks feat_tex0/feat_tex1 and outputs albedo * shadow. Replaces CNNv3Effect in cnn_v3_test sequence until training is complete. 37/37 tests passing. handoff(Gemini): GBufDeferredEffect wired in timeline; CNN v3 pipeline: GBufferEffect → GBufDeferredEffect → sink.

feat(cnn_v3): GBufferEffect internal scene + GBufViewEffect debug wiring

2026-03-22T18:15:55Z

GBufferEffect: - set_scene() now owns Scene/Camera internally; no external pointers needed - 20 randomly rotating cubes (xorshift32 seed, axis-angle animation) - 4 pumping spheres (radius = base_r * (1 + audio_intensity * 0.8)) - Camera at (0,2.5,6) looking at origin; aspect updated per-frame - GBufLightsUniforms: 2 directional lights (warm key + cool fill) - object_type written to ObjectData.params.x (ready for SDF shadow) - shadow/transp nodes cleared via zero-draw render passes (placeholder) - bilinear sampler cached via create_linear_sampler() / sampler_.get() - dead placeholder textures removed GBufViewEffect: - gbuf_view.wgsl: all channels now fully grayscale (removed color tint) - seq_compiler.py: GBufViewEffect added to CLASS_TO_HEADER - timeline.seq: cnn_v3_test uses GBufViewEffect -> sink for debug view Docs: HOWTO.md §1 updated with set_scene() description + §1b implementation plan for Pass 2 SDF shadow (shader spec, bind layout, C++ additions) handoff(Gemini): GBufferEffect has internal scene, 36/36 tests green. Next: implement Pass 2 shadow (gbuf_shadow.wgsl) per §1b plan in HOWTO.md.