| |
| |
| """ |
| Diagnostic: check whether CoAdaptGS / LoD-GS have PLY, test renders, and metrics |
| for the cells that are missing from outputs/phase5a/task_vapre_splatatlas_repro.csv. |
| """ |
| import json |
| from pathlib import Path |
|
|
| ROOT = Path("/root/autodl-tmp/SplatAtlas") |
| OUTPUTS = ROOT / "outputs" |
|
|
| |
| COADAPTGS_MISSING = [ |
| |
| "Auditorium", "Ballroom", "Barn", "Caterpillar", "Courtroom", |
| "Lighthouse", "Museum", "Palace", "Playground", "Temple", "Train", "Truck", |
| |
| "Bicycle", "Bonsai", "Counter", "Flowers", "Garden", "Kitchen", |
| "Room", "Stump", "Treehill", |
| |
| "DrJohnson", "Playroom", |
| ] |
|
|
| LOD_GS_MISSING = [ |
| |
| "Chair", "Drums", "Ficus", "Hotdog", "Lego", "Materials", "Mic", "Ship", |
| ] |
|
|
| |
| |
| def candidate_dirs(method: str, scene: str): |
| cands = [ |
| OUTPUTS / f"{method}_{scene}", |
| OUTPUTS / f"{method}_{scene.lower()}", |
| OUTPUTS / f"{method}_{scene.capitalize()}", |
| ] |
| seen = [] |
| for c in cands: |
| if c not in seen: |
| seen.append(c) |
| return seen |
|
|
| def find_run_dir(method: str, scene: str): |
| for d in candidate_dirs(method, scene): |
| if d.exists(): |
| return d |
| |
| matches = list(OUTPUTS.glob(f"{method}_*")) |
| for m in matches: |
| |
| suffix = m.name[len(method) + 1:] |
| if suffix.lower() == scene.lower(): |
| return m |
| return None |
|
|
| def count_images(d: Path): |
| if not d.exists(): |
| return 0 |
| n = 0 |
| for ext in ("*.png", "*.jpg", "*.jpeg"): |
| n += len(list(d.glob(ext))) |
| return n |
|
|
| def inspect_metrics_json(p: Path): |
| if not p.exists(): |
| return None |
| try: |
| obj = json.load(open(p, "r")) |
| except Exception as e: |
| return {"_error": str(e)} |
| flat = {} |
| def walk(o, prefix=""): |
| if isinstance(o, dict): |
| for k, v in o.items(): |
| walk(v, f"{prefix}{k}.") |
| elif isinstance(o, list): |
| pass |
| else: |
| flat[prefix.rstrip(".")] = o |
| walk(obj) |
| keep = {} |
| for k, v in flat.items(): |
| kl = k.lower() |
| if any(t in kl for t in ["psnr", "ssim", "lpips"]): |
| keep[k] = v |
| return keep or {"_no_metric_keys": list(flat.keys())[:10]} |
|
|
| def check(method: str, scene: str): |
| run = find_run_dir(method, scene) |
| row = { |
| "method": method, |
| "scene": scene, |
| "run_dir": str(run) if run else "MISSING", |
| } |
| if run is None: |
| row.update({"ply": "-", "cameras": "-", "renders": "-", "gt": "-", |
| "metrics_json": "-", "metrics_values": "-"}) |
| return row |
|
|
| ply = run / "point_cloud" / "iteration_30000" / "point_cloud.ply" |
| cameras = run / "cameras.json" |
|
|
| |
| test_root_candidates = [ |
| run / "test" / "ours_30000", |
| run / "test" / "ours_30000" / "30000", |
| ] |
| test_root = next((p for p in test_root_candidates if p.exists()), None) |
|
|
| if test_root: |
| renders_dir = test_root / "renders" |
| gt_dir = test_root / "gt" |
| else: |
| |
| renders_list = list(run.rglob("renders")) |
| gt_list = list(run.rglob("gt")) |
| renders_dir = renders_list[0] if renders_list else None |
| gt_dir = gt_list[0] if gt_list else None |
|
|
| n_renders = count_images(renders_dir) if renders_dir else 0 |
| n_gt = count_images(gt_dir) if gt_dir else 0 |
|
|
| metrics_path = run / "metrics_test_iter30000.json" |
| metrics_values = inspect_metrics_json(metrics_path) |
|
|
| row.update({ |
| "ply": "OK" if ply.exists() else "MISSING", |
| "cameras": "OK" if cameras.exists() else "MISSING", |
| "renders": f"{n_renders} imgs @ {renders_dir}" if renders_dir else "MISSING", |
| "gt": f"{n_gt} imgs @ {gt_dir}" if gt_dir else "MISSING", |
| "metrics_json": "OK" if metrics_path.exists() else "MISSING", |
| "metrics_values": metrics_values if metrics_values else "-", |
| }) |
| return row |
|
|
| def print_block(method: str, scenes): |
| print(f"\n{'='*100}") |
| print(f" {method} ({len(scenes)} missing scenes)") |
| print(f"{'='*100}") |
| summary = {"run_dir": 0, "ply": 0, "renders": 0, "metrics_json": 0} |
| for s in scenes: |
| r = check(method, s) |
| print(f"\n--- {method} × {s} ---") |
| print(f" run_dir : {r['run_dir']}") |
| print(f" PLY : {r['ply']}") |
| print(f" cameras.json : {r['cameras']}") |
| print(f" test renders : {r['renders']}") |
| print(f" test gt : {r['gt']}") |
| print(f" metrics_json : {r['metrics_json']}") |
| if isinstance(r['metrics_values'], dict): |
| print(f" metrics_values: {r['metrics_values']}") |
| if r['run_dir'] != "MISSING": |
| summary["run_dir"] += 1 |
| if r['ply'] == "OK": |
| summary["ply"] += 1 |
| if isinstance(r['renders'], str) and r['renders'].startswith(tuple("0123456789")): |
| n = int(r['renders'].split()[0]) |
| if n > 0: |
| summary["renders"] += 1 |
| if r['metrics_json'] == "OK": |
| summary["metrics_json"] += 1 |
| print(f"\n[Summary {method}]") |
| for k, v in summary.items(): |
| print(f" {k:<14}: {v} / {len(scenes)}") |
|
|
| print_block("coadaptgs", COADAPTGS_MISSING) |
| print_block("lod_gs", LOD_GS_MISSING) |
|
|