scripts/t2s_only.py

"""Make the page Text-to-Scene only (user, 2026-10-01: drop Image-to-Scene from the video, the site and the figures).

Edits index.html, cases data and the bar script in place. Each step asserts it found what it edits, so a re-run on an
already-edited page, or on a page whose structure has moved, stops instead of silently doing half the job.
    python3 scripts/t2s_only.py
"""
from __future__ import annotations
import json, re
from pathlib import Path
from bs4 import BeautifulSoup, NavigableString

ROOT = Path(__file__).resolve().parent.parent
I2S_CASES = ("comp-31-old-industrial-pallet-bay-repair-v2", "comp-61-new-york-mailbox-pair-repair-v2")


def one(found, what):
    assert found is not None, f"not found: {what}"
    return found


def index():
    p = ROOT / "index.html"
    soup = BeautifulSoup(p.read_text(), "html.parser")
    # head
    one(soup.title, "title").string = "Code4Scene: Benchmarking Coding Agents for Constructing 3D Scenes"
    one(soup.find("meta", attrs={"name": "description"}), "meta description")["content"] = (
        "A benchmark that scores the engine-native 3D scenes coding agents build in Unreal Engine from open-ended descriptions.")
    # intro
    intro = one(soup.find(id="top"), "intro")
    h1 = one(intro.find("h1"), "intro h1")
    h1.clear(); h1.append("Constructing"); h1.append(soup.new_tag("br")); em = soup.new_tag("em"); em.string = "3D Scenes with Code"; h1.append(em)
    one(intro.find(class_="intro-text"), "intro text").string = (
        "Benchmarking coding agents that turn open-ended scene descriptions into engine-native 3D scenes in Unreal Engine. "
        "Measuring spatial reasoning, task fulfillment and physical validity.")
    cap = one(intro.find(class_="featured-video-caption"), "video caption").find("span")
    one(cap, "video caption span").string = "Construction and evaluation"
    # the teaser is v31 (no editing subtitle on its end card), under a new name so cached copies of the old cut are not reused
    for src in intro.find_all("source"):
        src["src"] = "media/teaser-v31.mp4"
    for a in intro.find_all("a", href="media/teaser.mp4"):
        a["href"] = "media/teaser-v31.mp4"
    # task format: the construction example alone, without a one-tab tab bar
    tf = one(soup.find(id="task-format"), "task format")
    one(tf.find(id="task-i2s"), "task-i2s").decompose()
    one(tf.find(class_="task-tabs"), "task tabs").decompose()
    # leaderboard: Text-to-Scene only (the overall score is half Image-to-Scene)
    lb = one(soup.find(id="leaderboard"), "leaderboard")
    one(lb.find(class_="lb-tabs"), "leaderboard tabs").decompose()
    for el in lb.find_all(attrs={"data-view": True}):
        if el.get("data-view") in ("overall", "i2s"):
            el.decompose()
        else:
            st = (el.get("style") or "").replace("display:none", "").strip(" ;")
            if st: el["style"] = st
            else: del el["style"]
    desc = one(lb.find(class_="section-desc"), "leaderboard desc")
    desc.string = "14 coding-agent configurations · paper results on the original 20 public construction cases."
    sub = one(lb.find(class_="figure-subtitle"), "pareto subtitle")
    sub.string = "Quality against the cost of one case · original 20-case public evaluation"
    for t in lb.find_all(class_="figure-caption"):
        t.string = re.sub(r"\s*Cost is the mean USD per case; ov.*$", " Cost is the mean USD per case.", t.get_text())
    # cases: the four construction cases
    cs = one(soup.find(id="cases"), "cases")
    removed = 0
    for scene in cs.find_all(attrs={"data-case": True}):
        if scene["data-case"] in I2S_CASES:
            card = scene
            while card.parent is not None and card.parent.name != "body" and card.parent.get("id") != "cases" and \
                    not any(c for c in (card.parent.get("class") or []) if "grid" in c):
                card = card.parent
            card.decompose(); removed += 1
    assert removed == 2, removed
    for p_ in cs.find_all("p"):
        if "Compare repairs" in p_.get_text():
            p_.string = "Drag any scene to inspect the saved 3D output, or open a case to explore every agent."
    # takeaways: Spatial Composition only
    tk = one(soup.find(id="takeaways"), "takeaways")
    kept = 0
    for card in tk.find_all(class_="tk"):
        h = " ".join(one(card.find("h3"), "takeaway h3").get_text(" ").split())
        if h.startswith("Spatial Composition remains"):
            kept += 1
            for n in card.find_all(class_="n"):
                n.string = "Takeaway"
        else:
            card.decompose()
    assert kept == 1, kept
    for h in tk.find_all("h2"):
        if h.get_text(strip=True) == "Takeaways":
            h.string = "Takeaway"
    # the case-count strip: construction counts only
    av = one(soup.find(class_="availability"), "availability strip")
    spans = av.find_all("span", recursive=False); assert len(spans) == 2
    spans[0].b.string = "160"; spans[0].b.next_sibling.replace_with(" construction cases in the full benchmark target, including private cases")
    spans[1].b.string = "129"; spans[1].b.next_sibling.replace_with(" public construction cases")
    # nav label
    for a in soup.find_all("a"):
        if a.get_text(strip=True) == "Takeaways":
            a.string = "Takeaway"
    p.write_text(str(soup))
    left = re.findall(r"(?i)image-to-scene|\bi2s\b|repair|corrupted", p.read_text())
    print("index.html: remaining editing mentions:", len(left))


def bars():
    p = ROOT / "assets/leaderboard-bars.js"
    s = p.read_text()
    m = re.search(r"const ALL = (\{.*?\});\n", s, re.S)
    data = json.loads(one(m, "const ALL").group(1))
    assert set(data) >= {"t2s"}, data.keys()
    s = s[:m.start(1)] + json.dumps({"t2s": data["t2s"]}) + s[m.end(1):]
    p.write_text(s)
    print("leaderboard-bars.js: views", list(json.loads(re.search(r"const ALL = (\{.*?\});\n", s, re.S).group(1))))


def site_data():
    p = ROOT / "data/site.js"
    S = json.loads(p.read_text().split("=", 1)[1].rstrip().rstrip(";"))
    before = len(S["cases"])
    S["cases"] = [c for c in S["cases"] if c["track"] == "t2s"]
    p.write_text("window.SITE = " + json.dumps(S) + ";\n")
    print("data/site.js: cases", before, "->", len(S["cases"]))
    # the cases page states the counts in its header
    n3d = sum(1 for c in S["cases"] for a in c["agents"] if a.get("glb")) + sum(1 for c in S["cases"] for k in ("gt_glb", "input_glb") if c.get(k))
    cp = ROOT / "cases.html"; cs = cp.read_text()
    cs = re.sub(r"\d+ cases, \d+ scenes in 3D", f'{len(S["cases"])} cases, {n3d} scenes in 3D', cs); cp.write_text(cs)


# the packed model files of the two Image-to-Scene cases (repairs, ground truth, corrupted input), from data/site.js before this edit
I2S_MODELS = ["38071c69a86d174dc55f.bin", "46734878f740aae816d8.bin", "486b4742affe835723a3.bin", "66da6868d20ebb100197.bin", "6afbbaec6b7a4271b21f.bin", "7daf8107bb630cffdc18.bin", "c79715b9e6967c4f6c90.bin", "db5c0c5d2b78f9e47bb7.bin", "e6a6333939ccfe57d584.bin", "e9177d0cbf727df88100.bin", "f2b2b285e27a26ee6780.bin", "f3648a5ad9887ac0937d.bin"]


def progressive():
    p = ROOT / "data/progressive-scenes.json"
    d = json.loads(p.read_text()); n0 = len(d)
    d = {k: v for k, v in d.items() if k not in I2S_MODELS}
    p.write_text(json.dumps(d, indent=2) + "\n")
    print("data/progressive-scenes.json:", n0, "->", len(d))


if __name__ == "__main__":
    index(); bars(); site_data(); progressive()