| |
| """Build preview.html: embedded sample videos per regime + their questions + stats.""" |
| import base64 |
| import csv |
| import json |
| from collections import Counter |
| from pathlib import Path |
|
|
| ROOT = Path(__file__).parent / "dataset" |
| REGIME_TITLES = { |
| "train": "TRAIN (in-distribution, matches pendulum-cjepa-160f recipe)", |
| "val_high_damp": "VAL OOD · high damping γ∈(0.55,0.90)", |
| "val_low_damp": "VAL OOD · near-zero damping γ∈(0,0.08)", |
| "val_large_angle": "VAL OOD · large release angle ±(45–80°)", |
| "val_gravity": "VAL OOD · Moon / Mars / Jupiter gravity", |
| "val_quad_damping": "VAL OOD · quadratic drag β·ω|ω| (new law)", |
| "val_driven": "VAL OOD · periodically driven pendulum (new forcing)", |
| } |
|
|
|
|
| def b64(p): |
| return base64.b64encode(open(p, "rb").read()).decode() |
|
|
|
|
| def esc(s): |
| return str(s).replace("&", "&").replace("<", "<").replace(">", ">") |
|
|
|
|
| def main(): |
| idx = list(csv.DictReader(open(ROOT / "index.csv"))) |
| by_regime = {} |
| for r in idx: |
| by_regime.setdefault(r["regime"], []).append(r) |
|
|
| qj = {} |
| for split in ("train", "val"): |
| for e in json.load(open(ROOT / "questions" / f"questions_{split}.json"))["scene_annotation"]: |
| qj[e["video_id"]] = e["questions"] |
|
|
| stats_type = Counter() |
| stats_concept = Counter() |
| for qs in qj.values(): |
| for q in qs: |
| stats_type[q["question_type"]] += 1 |
| stats_concept[q.get("concept", "?")] += 1 |
|
|
| parts = ["""<!doctype html><meta charset="utf-8"> |
| <style> |
| body{font:15px/1.5 system-ui,Arial;max-width:1120px;margin:24px auto;padding:0 16px;color:#111} |
| h1{font-size:26px} h2{font-size:19px;margin:28px 0 6px;border-top:2px solid #ddd;padding-top:14px} |
| video{width:260px;border:1px solid #ccc;border-radius:6px;display:block} |
| .row{display:flex;gap:28px;align-items:flex-start;margin:10px 0 4px;flex-wrap:wrap} |
| .q{font-size:13.5px;max-width:720px} |
| .q li{margin:5px 0} |
| .t{display:inline-block;background:#eef;border-radius:4px;padding:0 6px;font-size:11px;margin-right:6px} |
| .c{background:#efe} |
| table{border-collapse:collapse;font-size:13.5px;margin:8px 0} |
| td,th{border:1px solid #ccc;padding:4px 10px} th{background:#f4f4f4} |
| code{background:#f5f5f5;padding:1px 5px;border-radius:4px} |
| </style> |
| <h1>Pendulum 3K · CLEVRER-style QA dataset — preview</h1> |
| <p>3,000 videos (160 frames @12 fps, 196×196, H.264) · frame-aligned CSV labels · |
| ~24k questions across the four CLEVRER types. Validation is <b>out-of-distribution |
| physics</b> on purpose (causal generalization), not just a held-out seed. |
| All question answers are derived from the ground-truth RK4 simulation |
| (videos show 13.33 s; a hidden 28 s continuation grounds the predictive questions).</p>"""] |
|
|
| n_q = sum(len(v) for v in qj.values()) |
| parts.append(f"<h2>Dataset stats</h2><table><tr><th></th><th>videos</th><th>questions</th></tr>" |
| f"<tr><td>train (in-distribution)</td><td>2400</td><td>—</td></tr>" |
| f"<tr><td>val (6 OOD regimes × 100)</td><td>600</td><td>—</td></tr>" |
| f"<tr><td><b>total</b></td><td><b>3000</b></td><td><b>{n_q}</b></td></tr></table>") |
| parts.append("<table><tr><th>question type</th><th>count</th></tr>" |
| + "".join(f"<tr><td>{k}</td><td>{v}</td></tr>" for k, v in stats_type.most_common()) |
| + "</table>") |
| parts.append("<details><summary><b>causal-concept histogram</b></summary><table>" |
| "<tr><th>concept</th><th>count</th></tr>" |
| + "".join(f"<tr><td>{esc(k)}</td><td>{v}</td></tr>" for k, v in stats_concept.most_common()) |
| + "</table></details>") |
|
|
| for regime in ["train"] + [k for k in REGIME_TITLES if k != "train"]: |
| rows = by_regime.get(regime) |
| if not rows: |
| continue |
| r = rows[len(rows) // 3] |
| vid = r["video_id"] |
| mp4 = ROOT / r["video_path"] |
| parts.append(f"<h2>{esc(REGIME_TITLES[regime])}</h2>") |
| params = (f"θ₀={float(r['theta0_deg']):+.1f}° ω₀={float(r['omega0_rad_s']):+.3f} " |
| f"γ={float(r['damping_s_inv']):.3f} β={float(r['quad_drag_beta']):.3f} " |
| f"g={float(r['gravity_m_s2']):.2f} drive_A={float(r['drive_amp_rad_s2']):.2f} " |
| f"f_d={float(r['drive_freq_hz']):.3f}Hz") |
| parts.append(f"<p><code>{vid}.mp4</code> · {esc(params)}</p>") |
| parts.append('<div class="row">') |
| parts.append(f'<video controls loop muted playsinline ' |
| f'src="data:video/mp4;base64,{b64(mp4)}"></video>') |
| parts.append('<div class="q"><ul>') |
| for q in qj[vid]: |
| parts.append(f'<li><span class="t">{q["question_type"]}</span>{esc(q["question"])}<br>') |
| if "choices" in q: |
| for i, c in enumerate(q["choices"]): |
| cls = ' class="c"' if i == q["answer"] else "" |
| parts.append(f'<span{cls}>{"abcd"[i]}) {esc(c)}</span> · ') |
| else: |
| parts.append(f'<span class="c">answer: {esc(q["answer"])}</span>') |
| parts.append("</li>") |
| parts.append("</ul></div></div>") |
|
|
| Path(__file__, ).parent.joinpath("preview.html").write_text("".join(parts)) |
| print("wrote preview.html") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
