Files
gig-line/Tools/gen/facade_detail_concepts.py
T
zwitschi 4d27109668 refactor(tools): group the sixty scripts by what they talk to
One directory with sixty scripts stopped being navigable, and the grouping is also the sandbox boundary:

  Tools/unreal/    commandlets and the two map builders, with ue_common.py and ue_placement.py as the
                   shared imports (they need the engine)
  Tools/blender/   builders, exporters, the FBX preset, the MPFB character pipeline, blender_screenshots
                   (they need the Blender Flatpak)
  Tools/review/    the visual loop: render_screenshots.sh, judge_screenshot.py, hero_compare.py,
                   build_comparison_md.py, e2e_asset_check.py, hero_iterate.sh, visual_loop.py,
                   visual_targets.json
  Tools/gen/       image and texture generation: the ComfyUI driver, deterministic texture writers,
                   reference fetching
  Tools/input/     OS-level input injection
  root             _common.py, check-lfs.sh, addon_compat_probe.py, sibling_asset_audit.py, tests/

Every moved script now resolves the repository root as ../.. and puts the tools root plus its siblings on
sys.path, so 'import ue_common' still works from unreal/. The test suite bootstrap does the same for the five
folders. render_screenshots.sh takes the folder as a third argument to run_cmdlet, and the e2e driver,
hero_iterate.sh and the comparison generator were repointed.

51 README rows now link to their new location, the README gains a Layout section naming each folder's
sandbox, and the architecture notes and Blender README follow the moves.

Verified: 108 tests pass, prettier is clean, judge_screenshot.py and hero_compare.py run from their new
homes, and the e2e run was aborted mid-way (it had been rebuilding an empty DemoMap for 15 minutes) and is
being rerun against the new layout.
2026-11-10 12:40:30 +01:00

329 lines
15 KiB
Python

#!/usr/bin/env python3
"""Generate frontal building plates from the local reference photography.
Each study takes one photograph we already hold (`Art/reference/`, gitignored) as
the geometric anchor and asks an image model to re-stage it as a clean **frontal
view of the building** — the whole elevation, the entrance in its facade, or the
building with its neighbours — evenly lit, no crowd, no staging, so the modelling
pass has something measurable instead of a tourist photo.
Deliberately **not** close-up detail crops: a doorway or cornice crop cannot be
measured for proportion, which is what the modelling pass actually needs.
python3 Tools/gen/facade_detail_concepts.py --list
python3 Tools/gen/facade_detail_concepts.py --only door-recess,parapet-motto
python3 Tools/gen/facade_detail_concepts.py --all
python3 Tools/gen/facade_detail_concepts.py --all --model google/gemini-2.5-flash-image
Output: `Art/reference/facade-details/<study>.png` plus a `<study>.refgen.json`
sidecar recording the model, the source photograph, the prompt and the SHA-256 of
the result. `Art/reference/` is gitignored, so **neither the images nor the
sidecars are committed** — they are local working material. The study list and
the tool are the committed part.
Design notes
------------
* Standard library only: the OpenRouter chat-completions call is `urllib`, and
the returned `data:` URL is decoded with `base64` and written straight to disk.
* An existing output is never overwritten; `-v2`, `-v3` … are used instead, so
re-running after a prompt edit keeps both studies comparable.
* Generation costs money, so it is never automatic: `--list` is free, and every
generating run prints the model and the study count first.
* The token is read from `OPENROUTER_API_KEY` or the ignored `.env` and is never
written to a sidecar or a log line.
"""
from __future__ import annotations
import argparse
import base64
import json
import os
import re
import sys
import time
import urllib.error
import urllib.request
ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", ".."))
REFERENCE_DIR = os.path.join(ROOT, "Art", "reference")
OUT_DIR = os.path.join(REFERENCE_DIR, "facade-details")
API_URL = "https://openrouter.ai/api/v1/chat/completions"
DEFAULT_MODEL = "google/gemini-2.5-flash-image"
# The instruction appended to every study. Kept identical to the sibling
# project's convention so the two sets stay comparable: the photograph fixes the
# geometry, the prompt only restages light, weather, people and surface.
ANCHOR_SUFFIX = (
"Use the attached reference photograph as the source of the architecture: keep "
"the building's proportions, storey count, column rhythm, band heights and "
"signage placement exactly as photographed. You may REFRAME — step back across "
"the street, zoom out or widen the field of view — so that the whole building "
"fits in the frame from the pavement to the parapet; the reference is often "
"cropped and the plate must not be. Keep the view exterior and frontal (or "
"three-quarter where asked). Restage only lighting, weather, people and surface "
"condition. Do not invent extra storeys, wings or ornaments, and do not change "
"the architecture to fit the frame."
)
# name -> (reference photo relative to Art/reference/, what the plate must show)
#
# Verified framing (vision pre-check, 2026-11-09): the model follows the reference
# crop closely, so a plate is only as wide as its source photo. `building-entrance`
# and `building-street-front` come back as full-elevation frontal views; the studies
# anchored on the tightly cropped 2009 facade photo stay cropped, because the model
# will not invent the parapet and sky that the photograph does not contain. A full
# building plate for 6840 needs a full-elevation photograph, which the local set
# does not have (see Docs/reference-notes-hollywood.md).
#
# Every study asks for a *frontal view of a building*, not a crop of one detail:
# the whole elevation, the entrance in its facade, or the building together with
# its neighbours. Close-up framing is deliberately absent — a detail crop cannot
# be measured for proportion, which is what the modelling pass needs.
STUDIES: dict[str, tuple[str, str]] = {
"building-front": (
"hollywood/el-capitan-facade-day-wikimedia-2009-10-27.jpg",
"A frontal view of the complete building shown in the reference "
"photograph: the whole elevation from the pavement to the parapet fits in "
"the frame with clear sky above the roofline and pavement below the ground "
"floor, shot straight on and centred. Nothing may be cut off at the top or "
"bottom. Even daylight, no crowd, no vehicles.",
),
"building-entrance": (
"el-capitan-entrance/01-hollywood-el-capitan-entrance.jpg",
"A frontal view of the building in the reference photograph, framed so its "
"street entrance is clearly visible as part of the facade — the doors and "
"the wall around them in proportion, not a close-up of the doorway. "
"Include the pavement in front. Even daylight, no crowd.",
),
"building-with-neighbours": (
"hollywood/el-capitan-theatre-blade-sign-day-wikimedia-2008-10.jpg",
"A straight-on view of the street wall in the reference photograph: the "
"building and its neighbouring buildings either side, each at full height "
"from pavement to parapet with sky above, the joins between them visible, "
"nothing cut off. Shot from across the road, parallel to the frontage. "
"Even daylight, no crowd.",
),
"building-street-front": (
"hollywood/walk-of-fame-terrazzo-ovation-day-cc0-2019-06-20.jpg",
"A frontal view along the pavement of the building in the reference "
"photograph: the building's frontage seen from street level with its "
"neighbours continuing either side and the pavement in the foreground. "
"Straight on, even daylight, no crowd.",
),
"building-front-oblique": (
"hollywood/el-capitan-facade-day-wikimedia-2009-10-27.jpg",
"A three-quarter view of the complete building in the reference "
"photograph: the frontal elevation and one side visible together so the "
"building's depth and mass read, with its neighbouring building at one "
"edge. The whole building stays in frame. Even daylight, no crowd.",
),
"theatre-front-with-neighbours": (
"el-capitan-theater-detail/01-el-capitan-marquee.jpg",
"A frontal view of the theatre in the reference photograph together with "
"the buildings either side of it, the whole frontage and its full height "
"in frame, shot from across the road. Even daylight, no crowd, marquee "
"lettering blocked out as unreadable texture.",
),
}
def load_token() -> str:
token = os.environ.get("OPENROUTER_API_KEY")
if token:
return token.strip()
env_path = os.path.join(ROOT, ".env")
if os.path.exists(env_path):
with open(env_path, encoding="utf-8") as handle:
for line in handle:
line = line.strip()
if line.startswith("OPENROUTER_API_KEY="):
return line.split("=", 1)[1].strip().strip('"').strip("'")
raise SystemExit("no OpenRouter key: set OPENROUTER_API_KEY or add it to .env")
def build_prompt(study: str) -> str:
"""The full prompt for a study: its request plus the fixed anchor suffix."""
if study not in STUDIES:
raise KeyError(f"unknown study {study!r}; known: {sorted(STUDIES)}")
return f"{STUDIES[study][1]}\n\n{ANCHOR_SUFFIX}"
def reference_path(study: str) -> str:
return os.path.join(REFERENCE_DIR, STUDIES[study][0])
def missing_references() -> list[str]:
"""Studies whose source photograph is not present locally."""
return [name for name in STUDIES if not os.path.isfile(reference_path(name))]
def next_free_path(study: str, directory: str = OUT_DIR) -> str:
"""`<study>.png`, or `<study>-v2.png`, `-v3` … if the name is taken."""
base = os.path.join(directory, f"{study}.png")
if not os.path.exists(base):
return base
index = 2
while True:
candidate = os.path.join(directory, f"{study}-v{index}.png")
if not os.path.exists(candidate):
return candidate
index += 1
def data_url(path: str) -> str:
suffix = os.path.splitext(path)[1].lower()
mime = {".jpg": "image/jpeg", ".jpeg": "image/jpeg", ".png": "image/png"}.get(suffix)
if not mime:
raise SystemExit(f"unsupported reference type: {path}")
with open(path, "rb") as handle:
return f"data:{mime};base64,{base64.b64encode(handle.read()).decode('ascii')}"
def decode_image(payload: dict) -> bytes:
"""Extract the returned image bytes from a chat-completions payload."""
message = (payload.get("choices") or [{}])[0].get("message", {})
urls = [item.get("image_url", {}).get("url", "")
for item in (message.get("images") or []) if isinstance(item, dict)]
if not urls:
match = re.search(r"data:image/[a-z]+;base64,[A-Za-z0-9+/=]+",
str(message.get("content") or ""))
if match:
urls.append(match.group(0))
if not urls or not urls[0]:
raise SystemExit(f"model returned no image data: {json.dumps(payload)[:400]}")
url = urls[0]
if url.startswith("data:"):
return base64.b64decode(url.split(",", 1)[1])
with urllib.request.urlopen(urllib.request.Request(url), timeout=120) as response:
return response.read()
def generate(study: str, token: str, model: str, force: bool = False) -> str:
"""Generate one study; returns the written path. Never overwrites by default."""
path = next_free_path(study)
if force and os.path.exists(os.path.join(OUT_DIR, f"{study}.png")):
path = os.path.join(OUT_DIR, f"{study}.png")
# Write to a temp name then replace, so a failed call cannot destroy the
# previous result.
target = path + ".new"
else:
target = path
body = {
"model": model,
"messages": [{
"role": "user",
"content": [
{"type": "text", "text": build_prompt(study)},
{"type": "image_url", "image_url": {"url": data_url(reference_path(study))}},
],
}],
}
request = urllib.request.Request(
API_URL,
data=json.dumps(body).encode("utf-8"),
headers={
"Authorization": f"Bearer {token}",
"Content-Type": "application/json",
"HTTP-Referer": "https://git.allucanget.biz/zwitschi/gig-line",
"X-Title": "gig-line facade details",
},
method="POST",
)
payload = None
for attempt in range(3):
try:
with urllib.request.urlopen(request, timeout=180) as response:
payload = json.load(response)
break
except urllib.error.HTTPError as exc:
if exc.code == 429 or exc.code >= 500:
wait = 5 * (attempt + 1)
sys.stderr.write(f" HTTP {exc.code}; retrying in {wait}s\n")
time.sleep(wait)
continue
detail = exc.read().decode("utf-8", "replace")[:300]
raise SystemExit(f"{study}: HTTP {exc.code} — {detail}")
except urllib.error.URLError as exc:
sys.stderr.write(f" network error ({exc.reason}); retrying\n")
time.sleep(5 * (attempt + 1))
if payload is None:
raise SystemExit(f"{study}: no response after retries")
image = decode_image(payload)
os.makedirs(OUT_DIR, exist_ok=True)
with open(target, "wb") as handle:
handle.write(image)
if target != path:
os.replace(target, path)
import hashlib
sidecar = {
"study": study,
"generated": os.path.basename(path),
"generated_utc": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
"model": model,
"prompt": build_prompt(study),
"reference": {
"file": STUDIES[study][0],
"note": "local reference photography; Art/reference is gitignored and never shipped",
},
"sha256": hashlib.sha256(image).hexdigest(),
"bytes": len(image),
"redistribution": "local development reference only; not committed, not shipped",
}
sidecar_path = os.path.splitext(path)[0] + ".refgen.json"
with open(sidecar_path, "w", encoding="utf-8") as handle:
json.dump(sidecar, handle, indent=2)
if token in json.dumps(sidecar):
raise SystemExit("refusing to write a sidecar containing the token")
return path
def main(argv=None) -> int:
ap = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
ap.add_argument("--list", action="store_true", help="list studies and exit (free)")
ap.add_argument("--all", action="store_true", help="generate every study")
ap.add_argument("--only", help="comma-separated study names")
ap.add_argument("--model", default=DEFAULT_MODEL)
ap.add_argument("--force", action="store_true",
help="replace the existing <study>.png instead of writing a -vN")
args = ap.parse_args(argv)
if args.list or not (args.all or args.only):
missing = set(missing_references())
print(f"{len(STUDIES)} studies; model {args.model}")
for name, (ref, _prompt) in STUDIES.items():
state = "MISSING reference" if name in missing else "ready"
print(f" {name:22} {state:18} <- {ref}")
if missing:
print(f"\n{len(missing)} study(ies) cannot run without their reference photograph.")
return 0
names = list(STUDIES) if args.all else [s.strip() for s in args.only.split(",") if s.strip()]
unknown = [n for n in names if n not in STUDIES]
if unknown:
raise SystemExit(f"unknown study(ies): {unknown}; known: {sorted(STUDIES)}")
blocked = [n for n in names if n in set(missing_references())]
if blocked:
raise SystemExit(f"missing reference photograph for: {blocked}")
token = load_token()
print(f"generating {len(names)} study(ies) with {args.model} -> {OUT_DIR}")
for index, name in enumerate(names, 1):
print(f"[{index}/{len(names)}] {name}")
try:
path = generate(name, token, args.model, force=args.force)
except SystemExit as exc:
sys.stderr.write(f" FAILED: {exc}\n")
continue
print(f" wrote {os.path.relpath(path, ROOT)}")
return 0
if __name__ == "__main__":
raise SystemExit(main())