534 lines
29 KiB
Markdown
534 lines
29 KiB
Markdown
# Asset Pipeline and Tooling
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Everything the game renders is produced or gated by the scripts below. Architecture-level contracts,
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data flow and failure fallbacks are summarized in
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[`architecture.md`](architecture.md#content-and-asset-pipeline-architecture); this page is the
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operational reference. Development-only outputs (AI concept sheets, Blender sources, raw AI fabrics)
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are gitignored; the audited game assets are committed.
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## Image Asset Tools
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Install the Pillow dependency used by the existing texture generator and the asset tools:
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```bash
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python3 -m pip install -r requirements-tools.txt
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```
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Generate a role-sized image (generation requires `OPENROUTER_API_KEY`):
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```bash
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python3 tools/asset_pipeline.py generate --prompt "weathered red brick" --role tile --output assets/textures/brick_extra.png
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```
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Generated images are resized to the selected role profile. Non-square requests use
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the validated `openai/gpt-5-image-mini` source ratio and crop to the final role dimensions.
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Transparent glyphs can be recolored while preserving their alpha mask with
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`--foreground '#ffffff'`.
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Crop uses the image center by default; `--x` and `--y` select an explicit crop origin. Resize defaults to aspect-preserving `contain`; use `--fit cover` to crop or `--fit stretch` to distort to the exact dimensions.
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```bash
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python3 tools/asset_pipeline.py crop assets/textures/source.png assets/textures/crop.png --width 256 --height 128
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python3 tools/asset_pipeline.py resize assets/textures/source.png assets/images/scenes/scene.png --width 1920 --height 1080 --fit cover
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python3 tools/asset_pipeline.py seamless assets/textures/rough_tile.png assets/textures/tile.png
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```
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Audit accepts image files or directories. `--role auto` infers common roles from paths and filenames; explicit roles include `tile`, `texture`, `icon`, `card`, `banner`, `backdrop`, `background`, `overlay`, `app_icon`, and `screenshot`.
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```bash
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python3 tools/asset_pipeline.py audit assets/textures
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python3 tools/asset_pipeline.py audit assets/images/scenes --role background --json
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python3 -m unittest discover -s tools -p 'test_*.py'
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```
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The audit classifies measurable fit issues as `good` or `bad` based on role-specific dimensions, aspect ratio, alpha requirements, and tile-edge continuity. It lists perspective/projection as a visual review item because image semantics cannot be judged reliably by these deterministic checks.
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## Prop models
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Street furniture (bollards, benches, bins, planters, newspaper boxes, a hydrant)
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is real 3D geometry generated by `tools/model_pipeline.py` and written to
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`assets/models/generated/*.glb`. Godot imports each file as a `PackedScene`, and
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`WorldBuilder` instantiates it with a procedural fallback when the model or its
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import is missing, so the world still builds on a fresh checkout.
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```bash
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# Print the catalogue (parts, triangle count, whether a model/concept exists)
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python3 tools/model_pipeline.py list
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# Rebuild the models (deterministic, offline) and validate them
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python3 tools/model_pipeline.py build
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python3 tools/model_pipeline.py audit
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# Optional: an image model supplies the colour palette per prop
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# (requires OPENROUTER_API_KEY; the repo .env is read automatically)
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python3 tools/model_pipeline.py concept
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python3 tools/model_pipeline.py concept --only bench --force
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```
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Each prop is a small list of boxes and cylinders, so `build` needs no network and
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the output is byte-identical between runs. `concept` asks an image model for a
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studio-style reference; `dominant_colors` and `assign_roles` then map that image's
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colours onto material roles (darkest → metal, warm saturated → wood, light grey →
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stone, green → foliage). glTF stores colours in linear space, so the tool converts
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the sRGB palettes before writing them. Re-run `build` and `godot --headless
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--path . --import` after changing a prop. See
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[ADR-0012](adr/0012-surface-materials-and-generated-props.md).
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Surface materials share one definition in `src/game/materials.gd`: named
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roughness/metallic profiles per surface, plus the environment tune-up (ACES
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tonemapping, glow, fog, colour grading) that the phase lighting applies.
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## NPC character model
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NPCs are moving from the procedural capsule rig to a skinned, UV-mapped base
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character authored in Blender ([ADR-0013](adr/0013-blender-authored-npc-characters.md)).
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`tools/npc_pipeline.py` builds `assets/models/generated/npc_base.glb` plus the
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per-slot material maps. `NpcAvatar` instantiates that skinned model, tints its
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five material slots from the seed-driven outfit, and drives the bones from the
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existing animation code; the procedural rig remains the offline fallback (see
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[ADR-0013](adr/0013-blender-authored-npc-characters.md) and
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[`blender-assets.md`](blender-assets.md)).
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```bash
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# Print the frozen contract (slots, bone names, triangle budget)
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python3 tools/npc_pipeline.py list
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# Rebuild the skinned base mesh + neutral maps in Blender and validate it
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flatpak run org.blender.Blender --background --python "$PWD/tools/npc_pipeline.py" -- build
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python3 tools/npc_pipeline.py audit
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# Layer the AI clothing albedos (shirt/trousers) over the procedural weave, and
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# derive per-fabric outfit colours for the avatar palette
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python3 tools/npc_pipeline.py prepare
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python3 tools/npc_pipeline.py palette
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```
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`prepare` resizes the AI fabric tiles (kept locally in `assets/textures/npc/ai/`,
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which is gitignored) onto the 256² `cloth`/`pants` albedos; `build` bakes them into
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the `.glb` and regenerates the procedural normal + packed ORM maps at the same
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256² size. Runtime fabric materials repeat the weave 4× (`NPC_FABRIC_UV_SCALE`)
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and skip the per-character baked AO, which otherwise magnified into large
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blotches; skin, hair and fixed gear keep AO. `palette` writes
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`assets/textures/npc/palette.json` using `model_pipeline.dominant_colors`.
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## Blender asset library (loaded by the game)
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`tools/blender_assets.py` models a larger library procedurally in Blender for the
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v0.6.0 integration: **8 skinned NPC characters** (casual, jacket, coat, hi-vis vest,
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dress, hoodie, firefighter, guard), each a drop-in for `npc_base.glb` (same bones,
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joint positions and tint slots); **18 gear pieces** authored at head/hand/back/chest
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attach points (caps, hood, helmet, backpack, SCBA tank, lanyard, phone, cup,
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clipboard, umbrella, camera, sign, flashlight, wand, radio, …); and **20 props**
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(octagonal bollard and bin, slatted bench, hydrant, news box, planters, street lamp,
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street and palm trees, A-frame sign, wall lantern, cone, crowd barrier, stanchion,
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handrail, podium, double door, marquee, sedan).
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`NpcAvatar` selects a character by role/seed, tints the five contract slots, and
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attaches gear at the documented points; `WorldBuilder` loads the library props
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with colliders/avoidance and drives their emissive parts from the day/night
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cycle. The single `npc_base.glb` and primitive props remain offline fallbacks.
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Contract and integration notes: [`blender-assets.md`](blender-assets.md).
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Sourcing and expansion research (no external model is shipped yet):
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[`npc-model-sourcing.md`](npc-model-sourcing.md) compares Quaternius, Kenney, Khronos and
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MakeHuman sources against the character contract and records the 2026-11-03 direction
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(procedural generator first, Quaternius reference, MakeHuman deferred).
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| Characters | Props |
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| --- | --- |
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```bash
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flatpak run org.blender.Blender --background --python "$PWD/tools/blender_assets.py" -- build
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flatpak run org.blender.Blender --background --python "$PWD/tools/blender_assets.py" -- render
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python3 tools/blender_assets.py sheet # docs/blender_previews/sheet_*.jpg
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python3 tools/blender_assets.py audit # no Blender needed
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python3 tools/blender_assets.py fit # gear-vs-body fit report
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python3 tools/blender_assets.py texels # per-slot texel density (px/m) of the characters
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godot --headless --path . --import
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```
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### Intake inspection (`inspect`)
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`audit` reads accessor-local bounds and ignores node transforms, so it is the right
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release gate but a poor first look at a downloaded or newly authored GLB. `inspect`
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imports the file into Blender, clears parents and applies object transforms, then
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reports what the scene actually contains:
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```bash
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# one asset, a batch, or an external download; repeat --file as needed
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flatpak run org.blender.Blender --background \
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--python "$PWD/tools/blender_assets.py" -- inspect \
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--file "$PWD/assets/models/blender/npc/npc_casual.glb" \
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--file "$PWD/tmp/downloads/SomeCharacter.glb"
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# machine-readable, for intake scripts (write to a file: Blender prints a banner first)
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... -- inspect --file "$PWD/tmp/x.glb" --json --out "$PWD/tmp/x.json"
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# force a contract family instead of inferring it from the path
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... -- inspect --file "$PWD/tmp/x.glb" --category npc
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```
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It prints triangles (with the category budget), raw and seam-split vertex counts,
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Godot-space bounds with height/feet for characters, whether transforms had to be
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applied, mesh nodes and armatures, bone names, materials, UV layers, skinning and
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animation count. Hard contract failures (`issues`) fail the command; advisory
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findings (`warnings`) do not. The category is inferred from the path:
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`blender/npc` → `npc`, `blender/npc_gear` → `npc_gear`, `blender/props` and
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`generated` → `props`, anything else → `external` (measured but with no project
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budget or rig contract).
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Caveats:
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- The glTF importer adds a bone-display mesh (`Icosphere`, used as
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`pose_bone.custom_shape`). `inspect` excludes custom-shape helpers so they never
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pollute bounds or the unskinned list.
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- Bounds and bone rests are converted from Blender Z-up to Godot Y-up (`x, z, -y`),
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matching the contract bands and the audit's coordinate space.
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- Numbers are Blender-side measurements. Triangles match `audit` on project assets; the seam-split
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vertex count can differ by ±1 because the importer rounds normals. `audit` stays the single final
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gate: it is stdlib-only, runs in CI, and matches what the engine imports.
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- `inspect` never writes or adapts the file; scale/grounding/weld/retarget work is the
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separate (not yet built) `adapt` step.
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- `--json` also captures the importer's INFO log in `stats.import_log` instead of printing it.
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Blender still prints its own version banner before the script runs, so intake scripts should use
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`--json --out <file>` rather than parsing stdout.
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### Reference-anchored concept generation
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`tools/scene_concepts.py generate --reference <photo>` anchors a concept frame on a real
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photograph: the photo is sent to the OpenRouter multimodal chat endpoint as a base64 data URL
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(`generate_textures.generate_image(reference_path=...)`) with a prompt suffix that pins the
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photographed geometry (column rhythm, band heights, signage placement, camera angle) while the
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prompt restages lighting, weather and people.
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Licence gate: the reference must be listed in its `docs/screens/refs/<venue>/SIDECAR.md` row
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(which also supplies the licence and Commons page for provenance). A photo from anywhere else
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requires `--reference-unchecked`, which records `unchecked` in the provenance. Each anchored
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generation writes a `.refgen.json` sidecar next to the frame (`model`, reference file/licence/page,
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geometry suffix) so a concept frame can always be traced back to its evidence photo. Where a
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generated frame and its reference photo disagree, the photo wins for shape.
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### Photo-anchored variant pass
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`tools/scene_concepts.py anchor --reference <photo> --context "..." --treatments day,night,weathered
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--out-dir docs/screens/concepts/<block>` generates several restaged conditions (day, night,
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weathered) of one reference photo's framing, each with its `.refgen.json` provenance sidecar, so a
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concept board stays comparable with its photo board. The reference passes the same SIDECAR licence
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gate as `--reference` on `generate`.
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### Local-only reference collection (`refcollect`)
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`tools/refcollect.py` downloads images from DuckDuckGo image search into `tmp/research/<slug>/` for
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development reference only. It applies **no licence gate** (rows are marked `local_only` /
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`unchecked-local`); everything it fetches must never be committed or promoted into
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[`screens/refs/`](screens/refs/README.md) without the normal sidecar licence + privacy gate. This
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is the owner-authorised local-only override (TODO.md §3D model re-evaluation → A).
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```bash
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python3 tools/refcollect.py search "Comedy Store Sunset Boulevard" --slug comedy-store --limit 20
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python3 tools/refcollect.py sheet --slug comedy-store # local contact sheet (never committed)
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```
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Requires `pip install duckduckgo-search` (renamed `ddgs` upstream). DuckDuckGo rate-limits by IP
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(HTTP 202), so every request — the search itself and each image download — passes through a shared
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token bucket (`--rate`, default 0.5 req/s, and `--burst`, default 3) and a polite retry routine:
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transient statuses (408/425/429/5xx/52x) and network errors back off exponentially with full
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jitter, `Retry-After` is honoured, permanent failures fail fast, and the loop gives up after six
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attempts. Requests carry a full, coherent Firefox header set (`--user-agent` overrides the UA
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string); the UA alone is no longer enough to look like a browser.
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### Reference-board research (`refboard`)
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`tools/refboard.py` searches, fetches and documents Wikimedia Commons photos of a real location for
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the [`screens/refs/`](screens/refs/README.md) boards. It is stdlib-only and never commits anything
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itself: downloads land in `tmp/`, and moving a file into a board folder is a deliberate manual step
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that goes through the sidecar licence gate.
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```bash
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# search: keyword, geosearch (the reliable "photos of this exact place"), or category
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python3 tools/refboard.py search --source geo "34.10118|-118.34009" --limit 60 --months 12
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python3 tools/refboard.py search "El Capitan Entertainment Centre" --source search
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python3 tools/refboard.py search "Hollywood Masonic Temple" --source category --json
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# fetch the usable rows into tmp/ (review-only rows need --include-review)
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python3 tools/refboard.py search ... --json > /tmp/manifest.json
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python3 tools/refboard.py fetch --from /tmp/manifest.json --dir tmp/research/<block> --max 12
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# emit SIDECAR + README table rows from the fetched manifest
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python3 tools/refboard.py rows --from tmp/research/<block>/meta.json
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```
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Licence gate: `Public domain`, `CC0` and `CC BY` are committable with attribution; `CC BY-SA` rows
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are flagged `review` and stay research-only until the share-alike decision is written into the
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sidecar (`--allow-ccbysa` marks them committable after that review); anything else is skipped.
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`--months 12` flags recent captures so a "current reality" photo can be distinguished from the
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older geometry evidence. Network gotchas baked in: a descriptive User-Agent, batched `titles=`
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metadata queries and ~3 s download spacing to avoid Commons HTTP 429s.
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### Texel density (`texels`)
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`texel_density()` and the `texels` command compute `resolution * sqrt(UV area / world area)` per
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material slot straight from the GLB, so the number does not depend on island packing. The NPC slot
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maps are 256², and cloth/pants are reported twice: authored density and effective density with the
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runtime 4× repeat from `Materials.NPC_FABRIC_UV_SCALE`. Current values and interpretation are in
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[`3d-model-review.md`](3d-model-review.md).
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```bash
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python3 tools/blender_assets.py texels # all eight characters
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python3 tools/blender_assets.py texels --json # machine-readable
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python3 tools/blender_assets.py texels --only npc_coat
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```
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## Local map development (planned)
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The **Local map development** track in [`TODO.md`](../TODO.md#local-map-development)
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is not implemented yet; there are no map-generation commands to run. The planned
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pipeline will evaluate:
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- offline OpenStreetMap extracts for footprints and licence-compatible 3D building
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massing (OSM Buildings, Overture, CityGML/LOD1–2);
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- downloaded reference imagery from Wikimedia Commons, own/team photography or
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other clearly licensed sources, with author/licence/attribution and privacy
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redaction recorded per set;
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- AI-assisted composition boards for palette, facade rhythm and material study,
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with model/prompt/output provenance and human acceptance;
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- Gaussian splatting as a development-only capture/reference/texture/proxy tool,
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version-pinned offline and outside CI, until an ADR proves runtime safety.
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No online map/photo/splat service is a build or play dependency. Committed map
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assets will need provenance sidecars, ODbL/photo-licence review and the same
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`WorldBuilder` venue-budget/navigation/collider gates as the current stylized
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geometry. The detailed task plan and exit criteria live in `TODO.md`.
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## Confirmed game assets
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Everything below is audited and shipped in the game; development-only outputs
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(AI concept sheets, Blender sources, raw AI fabrics) are gitignored.
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| --- | --- |
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- **Surface textures:** the v2 picks above (brick, sidewalk pavers, dry and wet asphalt, awning canvas) plus their normal maps, loaded by `src/game/materials.gd` and `WorldBuilder`; the three skyline panoramas are switched per shift phase. The first-generation tiles and `assets/textures/skyline.png` are no longer loaded.
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- **UI art:** `assets/textures/ai/game_ready/icons/` (flashlight, door lock, wand, REC) and `assets/textures/ai/game_ready/cards/` (ID, wristband, ticket, credential, guest list), loaded by `src/game/ui/hud.gd`.
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- **Generated models:** `assets/models/generated/*.glb` — bollard, bench, trash bin, planter, newspaper box, hydrant, and the NPC base — plus their colour atlases.
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- **NPC material maps:** `assets/textures/npc/*_{albedo,normal,orm}.png` and `palette.json`.
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Audit them all:
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```bash
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python3 tools/asset_pipeline.py audit assets/textures/ai/game_ready
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python3 tools/model_pipeline.py audit
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python3 tools/npc_pipeline.py audit
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```
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## Realism pass: scene concepts, skylines and textures
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The skyline, surface tiles and phase lighting were rebuilt against AI concept frames. The
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concepts live in [`docs/screens/concepts/`](../docs/screens/concepts/README.md); the validated
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picks the game loads are in `assets/textures/ai/game_ready/v2/picks/` (day/dusk/night
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panoramas, brick, sidewalk pavers, dry and wet asphalt, awning canvas, each with a normal
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map).
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`tools/scene_concepts.py` generates and processes new candidates, promotes the validated ones
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to stable names, audits them, and scores captures against the concepts. It never overwrites an
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image: new files get a `-vN` suffix, and `process` skips existing candidates unless `--new`.
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```bash
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python3 tools/scene_concepts.py generate --group scene # or backdrop / texture, --variants N
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python3 tools/scene_concepts.py process && python3 tools/scene_concepts.py audit
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python3 tools/scene_concepts.py promote # validated picks -> v2/picks/
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godot --headless --path . --import
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# A/B a candidate without touching game code: the same cameras, textures swapped at runtime.
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godot --path . --script res://src/test/capture_realism.gd -- --out=res://docs/screens/realism/<run>/after
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godot --path . --script res://src/test/capture_realism.gd -- --out=res://docs/screens/realism/<run>/try \
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--swap=res://assets/textures/ai/game_ready/v2/picks/brick_facade.png=res://assets/textures/ai/game_ready/v2/brick_facade-v2.png
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# Score before/after against the concepts (Pillow detail metrics + vision judge).
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python3 tools/scene_concepts.py realism --run docs/screens/realism/<run> --judge \
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--model google/gemini-2.5-flash --repeats 3
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```
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Judges default to `--model auto`: `tools/openrouter_judge.py` reads the live
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OpenRouter catalogue, keeps image-input models that support `response_format`,
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and ranks them by advertised token/image price. The run falls through the list
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on provider/model errors and aborts on an invalid key. Use
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`GIG_LINE_JUDGE_MODEL` or `--model <id>` for a pinned comparison.
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`capture_npc_review.gd` is the pre-build NPC gate: it stages all eight
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library character models at portrait, conversation and crowd distance on both
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promoted maps in day and night lighting, with the normal crowd hidden. It uses
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the review-only `NpcAvatar.character_override` to include the guard model, which
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has no spawned NPC role:
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```bash
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godot --path . --script res://src/test/capture_npc_review.gd -- \
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--out=res://tmp/npc-review
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```
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Contact sheets can be assembled from the files (the output is local QA and is
|
||
not committed). The runtime applies small attach-space offsets to the lanyard
|
||
and firefighter helmet so the badge clears the jacket and the brim does not sit
|
||
over the eyes; these are `NpcAvatar.GEAR_OFFSETS`, not changes to the gear
|
||
contract.
|
||
|
||
`tools/npc_proportions.py` checks the eight character GLBs against the shared
|
||
height/head/shoulder/hip/torso/leg/arm/foot guide; the current results are in
|
||
[`npc-proportion-audit.md`](npc-proportion-audit.md). It reads the exported GLBs
|
||
and does not require Blender.
|
||
|
||
`capture_npc_pose.gd` is the pose/deformation harness for the 3D re-evaluation: idle,
|
||
walk-contact, walk-pass and seated poses of all eight variants, full-body plus shoulder
|
||
close-ups. **It is currently blocked**: the applied pose is visible in the rig and bone values
|
||
but not in the captured frames, so do not use its sheets as pose evidence. The reproduction and
|
||
what was ruled out are in [`3d-model-review.md`](3d-model-review.md) §"Pose evidence is blocked".
|
||
|
||
The baseline sheet tool accepts a custom view list, which is also how pose sheets are tiled:
|
||
|
||
```bash
|
||
# baseline set (six views, eight variants)
|
||
python3 tools/npc_baseline.py sheet --dir tmp/npc-baseline
|
||
# pose set produced by capture_npc_pose.gd
|
||
python3 tools/npc_baseline.py sheet --dir tmp/npc-pose \
|
||
--views idle,walk_contact,walk_pass,sit --out tmp/npc-pose/sheet_pose.jpg
|
||
```
|
||
|
||
`capture_npc_baseline.gd` is the 0.9.4 neutral baseline: eight characters ×
|
||
front/three-quarter/profile/back/full-body/crowd = 48 frames with a fixed
|
||
camera, studio lighting and no venue/HUD/animation. The raw PNGs stay in
|
||
`tmp/`; `tools/npc_baseline.py sheet` builds the committed contact sheet, and
|
||
`tools/npc_baseline.py compare --before DIR --after DIR` builds the review
|
||
comparison after a model change. See
|
||
[`npc-visual-review.md`](npc-visual-review.md).
|
||
|
||
```bash
|
||
godot --path . --script res://src/test/capture_npc_baseline.gd -- \
|
||
--out=res://tmp/npc-baseline
|
||
python3 tools/npc_baseline.py sheet --dir tmp/npc-baseline
|
||
```
|
||
|
||
`capture_realism.gd` runs nine stages in this order: day, Hollywood surface close-ups,
|
||
portrait, evening, late, Joke Shop day, Joke Shop surface close-ups, Joke Shop night,
|
||
studio; `--stages=day,late` limits it while tuning; `--flashlight` turns on the guard
|
||
lamp for night stages (used by the Desktop HQ A/B). The `portrait` shot freezes one
|
||
NPC on open sidewalk and frames the face, which is the only capture that can judge
|
||
avatar detail (`--portrait-type=N` picks a role). For the 0.9.5 texture audit, run
|
||
the surface stages directly; the HUD is hidden for them:
|
||
|
||
```bash
|
||
godot --path . --script res://src/test/capture_realism.gd \
|
||
-- --out=res://tmp/surfaces --stages=surfaces,surfaces_joke
|
||
```
|
||
|
||
The generated realism runs under
|
||
`docs/screens/realism/` are **local, gitignored QA artifacts**; commit only the
|
||
resulting decisions/docs, not the run folders. The 0.9.5 texture/UI audit checked actual screen sizes: all screen art is
|
||
1280×720, access cards are 256×128 and HUD icons are 64×64; no runtime texture
|
||
was oversized or unused. The 24-NPC smoke now reports 168 meshes / 131,616
|
||
triangles / 6.94 ms. Compressed payloads are 24.55 MB of surface picks, 22.67 MB
|
||
of screen art and 0.48 MB of NPC maps.
|
||
|
||
The 0.9.5 realism judge ran once per shot with `z-ai/glm-5.3-flash`
|
||
(`python3 tools/scene_concepts.py realism --run docs/screens/realism/2026-11-02-tex
|
||
--judge`). Its mean `after` scores were overall 1.8, lighting 2.3, materials 1.8,
|
||
texture detail 1.2, backdrop 2.0 and characters 1.2; the Pillow metric gap was
|
||
0.306. The judge still ranks the painted concept targets above the stylized build,
|
||
particularly lit night facades and dense backdrop detail. That is expected: the
|
||
pass validated close-range surfaces and promoted the texture repairs, not a
|
||
photoreal renderer. The 0.9.5 before/after close-up sheet is
|
||
[`blender_previews/sheet_texture_refinement_0.9.5.jpg`](blender_previews/sheet_texture_refinement_0.9.5.jpg);
|
||
the texture-adoption run itself was the earlier 0.8-style candidate comparison,
|
||
and its report remains local/gitignored.
|
||
|
||
For the 0.9.6 integration checkpoint the same judge was pinned to
|
||
`z-ai/glm-5.3-flash` and run once per shot on the 10-shot set: mean overall 2.1,
|
||
lighting 2.4, materials 2.1, texture 1.7, backdrop 2.3, characters 1.8, Pillow
|
||
gap 0.291. No `review` verdicts were produced by the screen judge, so there was
|
||
no manual layout verdict to convert into a fix; the remaining realism comments
|
||
are the accepted stylized gaps.
|
||
|
||
Build release artifacts from a clean checkout or detached worktree. A normal
|
||
working tree may contain ignored `tmp/` captures and old `build/` artifacts, and
|
||
Godot can pack enough of those into exports to inflate a 0.9.6 package from
|
||
~160 MB to 1.6–3.1 GB. The 0.9.6 clean worktree produced 161.5 MB Linux,
|
||
197.1 MB Windows, 148.0 MB macOS, 97.8 MB Web and 241.5 MB Desktop HQ.
|
||
|
||
The Forward+ A/B compared the Compatibility entrance with the optional Desktop HQ
|
||
preset. The gear-fit run checked the sunglasses, bag and helmet against measured
|
||
head/skirt bounds with `python3 tools/blender_assets.py fit`; it also fixed the
|
||
portrait yaw and hid the focus overlay so the close-up shows the avatar.
|
||
|
||
Regenerate a run locally with the capture and `realism --run ...` commands above;
|
||
the reports and sheets are intentionally not part of the release repository.
|
||
|
||
## Screen design references
|
||
|
||
Screen mockups and screenshot comparison use `tools/screen_designs.py`. It turns the
|
||
screen descriptions in `docs/` (README captions, ADRs 0007–0010, `PLAN.md`, and
|
||
`architecture.md`) into runtime reference art under `assets/images/ui/` (with a
|
||
reference-only snapshot in `docs/screens/designs/`), then uses those images as
|
||
the expected state to check the game's captures.
|
||
|
||
Each screen is tagged `scene` (a realistic first-person 3D world view) or `ui`
|
||
(an in-game panel overlaid on a softened scene), and the generator appends a
|
||
shared art-direction suffix so the frames read as one coherent game. Requests use
|
||
a 3:2 landscape source and crop to the 16:9 capture dimensions.
|
||
|
||
```bash
|
||
# Export the built-in scenarios to editor-authorable .tres resources
|
||
godot --headless --path . --script res://tools/export_venues.gd
|
||
|
||
# List the catalogue (name, kind, whether a reference design exists)
|
||
python3 tools/screen_designs.py list
|
||
|
||
# Deterministic wireframes (offline, no API key); existing designs are kept
|
||
# unless --force is passed, so an offline run never replaces an AI mockup
|
||
python3 tools/screen_designs.py generate --draft
|
||
python3 tools/screen_designs.py generate --draft --only wand --force
|
||
|
||
# Realistic 3D scenes and in-game screen designs via OpenRouter
|
||
# (requires OPENROUTER_API_KEY)
|
||
python3 tools/screen_designs.py generate
|
||
|
||
# UI-state gallery (menu, pause, settings, review, radio, wheel, crowd, responder)
|
||
godot --path . --script res://src/test/capture_ui_states.gd -- --out=res://docs/screenshots
|
||
|
||
# Prop gallery (studio line-up) for close-range prop checks
|
||
godot --path . --script res://src/test/capture_prop_gallery.gd
|
||
|
||
# Compare docs/screenshots/*.png against the designs
|
||
python3 tools/screen_designs.py compare
|
||
python3 tools/screen_designs.py compare --json
|
||
|
||
# Ask a vision model whether each capture realises its design's screen and layout
|
||
# (requires OPENROUTER_API_KEY; the repo .env is read automatically)
|
||
python3 tools/screen_designs.py judge
|
||
python3 tools/screen_designs.py judge --model openai/gpt-4o-mini --json
|
||
python3 tools/screen_designs.py judge --only 03- # one capture
|
||
python3 tools/screen_designs.py judge --dry-run # build requests, no network
|
||
```
|
||
|
||
The catalogue covers 21 screens: the thirteen scene captures plus the start menu,
|
||
pause overlay, settings, shift review, radial menu, emergency radio, crowd panic,
|
||
and responder arrival. All 21 have an AI reference in `assets/images/ui/`
|
||
(snapshot in `docs/screens/designs/`) and a committed capture, so every entry is
|
||
compared or judged against the running game.
|
||
|
||
`compare` flags gross drift: wrong aspect ratio, undersized frame, near-blank
|
||
frame, and large layout/palette/detail distance. It is a regression gate, not a
|
||
semantic judge — pixel and perceptual metrics cannot decide whether a frame's
|
||
composition is *right*.
|
||
|
||
`judge` covers that gap: it sends each capture together with its concept mockup to
|
||
a vision model and asks whether the capture realises the same screen and layout
|
||
intent. Art style, fidelity, fonts, and placeholder text are explicitly ignored.
|
||
Verdicts are classed as `match`, `review` (a mismatch below `--fail-confidence`,
|
||
default 0.6 — expected when a concept mockup is more stylised than the game), or
|
||
`diff` (a confident mismatch, which exits non-zero). Regenerate the designs after changing screen layout, then re-run
|
||
`compare` after regenerating the game screenshots with
|
||
`src/test/capture_screenshots.gd` and `src/test/capture_ui_states.gd`.
|
||
|
||
For a one-command drift check, run `tools/check_screenshots.sh`. It renders the
|
||
scene captures, UI-state captures and prop gallery into `docs/screenshots/` (using
|
||
`xvfb-run` when no display is available) and then runs `screen_designs.py compare`.
|