File size: 5,653 Bytes
9affda1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
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"
# Cells missing from phase5a (from previous diagnostic)
COADAPTGS_MISSING = [
# T&T (12)
"Auditorium", "Ballroom", "Barn", "Caterpillar", "Courtroom",
"Lighthouse", "Museum", "Palace", "Playground", "Temple", "Train", "Truck",
# Mip-360 (9)
"Bicycle", "Bonsai", "Counter", "Flowers", "Garden", "Kitchen",
"Room", "Stump", "Treehill",
# DB (2)
"DrJohnson", "Playroom",
]
LOD_GS_MISSING = [
# NS (8)
"Chair", "Drums", "Ficus", "Hotdog", "Lego", "Materials", "Mic", "Ship",
]
# Common alternate casings to try, since phase5a uses lowercase but
# directory names sometimes use the canonical mixed case.
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
# Fallback: glob anything matching
matches = list(OUTPUTS.glob(f"{method}_*"))
for m in matches:
# match scene case-insensitively
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 render dirs (typical 3DGS-family layout)
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:
# Fall back: any folder named renders / gt under run/
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)
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