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HY3D pipeline: sq_fit_v20 + mesh_mapper_v8 combined batch runner.
Input layout:
<mesh_root>/<shard>/<uid>/full.ply
Output layout:
<output_root>/<uid>/
adaptive_map_v4/<uid>_adaptive_map_v4.npz
sdf_vol/<uid>_sdf_vol.npz
sq_fit_v20/{post_sq_*.ply, final_sq_*.ply, final_sq_model.ply, ...}
curv_seg_v4/face_labels.npy # segmentation labels (prerequisite for stage B)
mesh_mapping_v8/{face_labels_v8.npy, mesh_mapped_v8.ply, report.json}
full.ply # copy of the input mesh
summary.json
Resume semantics:
Stage A sq_fit_v20 done marker: sq_fit_v20/final_sq_model.ply
Stage B mesh_mapping_v8 done marker: mesh_mapping_v8/face_labels_v8.npy
- both done -> skip the uid entirely
- only A done -> run stage B only (plus the curv_seg_v4 prerequisite if needed)
- none done -> run A, then B
- summary.json is rewritten at the end of each uid
Usage:
python scripts/run_batch_sqfit.py --mesh_root <root> --output_root <out>
python scripts/run_batch_sqfit.py --mesh_root <root> --output_root <out> --start_index 20 --end_index 50
python scripts/run_batch_sqfit.py --mesh_root <root> --output_root <out> --uids_file list.json
python scripts/run_batch_sqfit.py --mesh_root <root> --output_root <out> --no_isolate # same process (debug)
"""
from __future__ import annotations
import argparse
import glob
import json
import os
import shutil
import sys
import time
import traceback
from pathlib import Path
import numpy as np
DEFAULT_SHARD = "00"
V20_PARAMS = dict(
complex_levels=(16, 32),
max_batches=50,
max_cands=5,
target_coverage=0.9,
max_iter=200,
cost_threshold=0.05,
max_total_sqs=100,
)
V4_PARAMS = dict(
cut_percentile=90.0,
cut_abs_min_deg=6.0,
cut_abs_max_deg=12.0,
curv_weight=0.0,
min_faces=60,
smooth_iters=1,
explode_scale=0.3,
)
V8_PARAMS = dict(
vote_mode="count",
vote_tau=0.025,
orphan_face_dist=0.04,
orphan_atom_frac=0.6,
min_atom_size=3,
)
# ============================================================
# UID discovery
# ============================================================
def discover_uids(mesh_root: str, shard: str, uids_file: str | None = None) -> list[str]:
if uids_file and os.path.exists(uids_file):
if uids_file.endswith(".json"):
data = json.load(open(uids_file))
if isinstance(data, dict) and "uids" in data:
return list(data["uids"])
return list(data)
return [ln.strip() for ln in open(uids_file) if ln.strip() and not ln.startswith("#")]
shard_dir = os.path.join(mesh_root, shard)
if not os.path.isdir(shard_dir):
raise FileNotFoundError(shard_dir)
uids = []
for d in sorted(os.listdir(shard_dir)):
full = os.path.join(shard_dir, d, "full.ply")
if os.path.isfile(full):
uids.append(d)
return uids
# ============================================================
# Stage completion checks
# ============================================================
def stage_sq_done(uid_out: str) -> bool:
return os.path.isfile(os.path.join(uid_out, "sq_fit_v20", "final_sq_model.ply"))
def stage_v8_done(uid_out: str) -> bool:
return os.path.isfile(os.path.join(uid_out, "mesh_mapping_v8", "face_labels_v8.npy"))
def stage_v4_done(uid_out: str) -> bool:
return os.path.isfile(os.path.join(uid_out, "curv_seg_v4", "face_labels.npy"))
# ============================================================
# Stage A: sq_fit_v20 (adaptive_map_v4 + sdf_vol + sq_fit_v20)
# ============================================================
def _normalize_mesh_o3d(mesh, half=0.5, margin=1e-6):
import open3d as o3d
v = np.asarray(mesh.vertices, dtype=np.float64).copy()
f = np.asarray(mesh.triangles, dtype=np.int32).copy()
if v.size == 0 or f.size == 0:
raise ValueError("Empty mesh.")
center = (v.min(0) + v.max(0)) * 0.5
ext = float((v.max(0) - v.min(0)).max())
if ext <= 0:
raise ValueError(f"Invalid extent: {ext}")
v = (v - center) * ((half - margin) * 2.0 / ext)
return o3d.geometry.TriangleMesh(
o3d.utility.Vector3dVector(v),
o3d.utility.Vector3iVector(f),
)
def run_stage_sqfit(uid: str, mesh_path: str, uid_out: str) -> dict:
import open3d as o3d
from hitops.adaptive.adaptive_block import build_block_maps_o3d
from hitops.adaptive.adaptive_res_block import (
build_adaptive_block_map, save_adaptive_map,
)
from hitops.sdf.build_adaptive_sdf import build_sdf_volume, save_sdf_volume, sdf_volume_stats
from hitops.sqfit.sq_fit import SDFAdaptiveFitter
map_dir = os.path.join(uid_out, "adaptive_map_v4")
sdf_dir = os.path.join(uid_out, "sdf_vol")
sq_dir = os.path.join(uid_out, "sq_fit_v20")
for d in [map_dir, sdf_dir, sq_dir]:
os.makedirs(d, exist_ok=True)
stats = {"status": "ok"}
t_start = time.time()
mesh = o3d.io.read_triangle_mesh(mesh_path)
if len(mesh.vertices) == 0:
raise ValueError("empty mesh")
stats["n_vertices"] = int(len(mesh.vertices))
stats["n_triangles"] = int(len(mesh.triangles))
mesh = _normalize_mesh_o3d(mesh)
# Build the adaptive block map.
t0 = time.time()
prebuilt = {}
for b in [16, 32, 64]:
for attempt in range(3):
try:
r = build_block_maps_o3d(
mesh, B=b, R_max=32,
level_scheme="quantile", clip_percentile=99.5,
)
assert r["map"].shape == (b, b, b)
prebuilt[b] = r["map"]
break
except (ValueError, AssertionError) as e:
print(f" [retry {attempt+1}/3] B={b}: {e}", flush=True)
else:
raise RuntimeError(f"build_block_maps_o3d B={b} failed")
adaptive = build_adaptive_block_map(
mesh=mesh, B_list=[16, 32, 64], R_max=32, prebuilt_maps=prebuilt,
)
stats["time_adaptive"] = round(time.time() - t0, 2)
save_adaptive_map(adaptive, os.path.join(map_dir, f"{uid}_adaptive_map_v4.npz"))
# Build the SDF volume.
t0 = time.time()
R = adaptive["level_map"].shape[0]
sdf_vol, truncation = build_sdf_volume(mesh, resolution=R)
save_sdf_volume(sdf_vol, truncation, os.path.join(sdf_dir, f"{uid}_sdf_vol.npz"))
stats["time_sdf"] = round(time.time() - t0, 2)
sdf_volume_stats(sdf_vol, truncation)
# Fit superquadrics.
t0 = time.time()
fitter = SDFAdaptiveFitter(
adaptive_map=adaptive, sdf_vol=sdf_vol, truncation=truncation,
complex_levels=tuple(V20_PARAMS["complex_levels"]),
)
fitter.run(
max_batches=V20_PARAMS["max_batches"],
max_cands=V20_PARAMS["max_cands"],
target_coverage=V20_PARAMS["target_coverage"],
max_iter=V20_PARAMS["max_iter"],
cost_threshold=V20_PARAMS["cost_threshold"],
max_total_sqs=V20_PARAMS["max_total_sqs"],
)
fitter.save_results(sq_dir)
stats["time_sqfit"] = round(time.time() - t0, 2)
stats["n_sq"] = len(glob.glob(os.path.join(sq_dir, "post_sq_*.ply")))
stats["time_total"] = round(time.time() - t_start, 2)
return stats
# ============================================================
# Stage B prereq: curv_seg_v4 (produces face_labels.npy)
# ============================================================
def run_stage_v4(mesh_path: str, uid_out: str) -> dict:
from hitops.segment.curvature_seg import segment_pipeline
out = os.path.join(uid_out, "curv_seg_v4")
os.makedirs(out, exist_ok=True)
t0 = time.time()
segment_pipeline(
mesh_path=mesh_path,
out_dir=out,
**V4_PARAMS,
)
return {"status": "ok", "time_total": round(time.time() - t0, 2)}
# ============================================================
# Stage B: mesh_mapper_v8
# ============================================================
def run_stage_v8(mesh_path: str, uid_out: str) -> dict:
import trimesh
from hitops.mapping.mesh_mapper import _load_sq_voxel_groups, map_with_atoms, save_results
fl_path = os.path.join(uid_out, "curv_seg_v4", "face_labels.npy")
sq_dir = os.path.join(uid_out, "sq_fit_v20")
out_dir = os.path.join(uid_out, "mesh_mapping_v8")
os.makedirs(out_dir, exist_ok=True)
t0 = time.time()
mesh = trimesh.load(mesh_path, force="mesh", process=False)
face_labels_v4 = np.load(fl_path).astype(np.int32)
sq_names, sq_pts = _load_sq_voxel_groups(sq_dir)
if not sq_names:
return {"status": "skipped", "reason": "empty sq_dir"}
res = map_with_atoms(
mesh, face_labels_v4, sq_pts,
vote_mode=V8_PARAMS["vote_mode"],
vote_tau=V8_PARAMS["vote_tau"],
orphan_face_dist=V8_PARAMS["orphan_face_dist"],
orphan_atom_frac=V8_PARAMS["orphan_atom_frac"],
min_atom_size=V8_PARAMS["min_atom_size"],
)
save_results(mesh, res, sq_names, out_dir, save_per_sq=False)
s = {"status": "ok", "t_total": round(time.time() - t0, 2), **res["stats"]}
return s
# ============================================================
# Per-UID driver: runs only missing stages
# ============================================================
def process_one(uid: str, mesh_root: str, shard: str, output_root: str) -> dict:
mesh_src = os.path.join(mesh_root, shard, uid, "full.ply")
if not os.path.isfile(mesh_src):
return {"uid": uid, "status": "failed", "error": f"mesh not found: {mesh_src}"}
uid_out = os.path.join(output_root, uid)
os.makedirs(uid_out, exist_ok=True)
# Copy full.ply into the output directory to mirror the expected layout,
# only when it is missing.
mesh_dst = os.path.join(uid_out, "full.ply")
if not os.path.isfile(mesh_dst):
shutil.copy2(mesh_src, mesh_dst)
result: dict = {"uid": uid, "mesh_path": mesh_src}
# Run the stages against the input mesh rather than the copy; the bytes are
# identical, and the pipeline code expects the input path convention.
mesh_for_run = mesh_src
# ---- Stage A: sq_fit_v20 ----
if stage_sq_done(uid_out):
n_sq = len(glob.glob(os.path.join(uid_out, "sq_fit_v20", "post_sq_*.ply")))
result["sq_fit_v20"] = {"status": "skipped", "n_sq": n_sq}
else:
print(f" [sq_fit_v20] running...", flush=True)
try:
result["sq_fit_v20"] = run_stage_sqfit(uid, mesh_for_run, uid_out)
except Exception as e:
result["sq_fit_v20"] = {"status": "failed", "error": str(e)}
result["status"] = "failed"
result["error"] = f"sq_fit_v20: {e}"
return result
# ---- Stage B: mesh_mapper_v8 ----
if stage_v8_done(uid_out):
result["mesh_mapping_v8"] = {"status": "skipped"}
else:
# Prerequisite: the curv_seg_v4 face labels.
if not stage_v4_done(uid_out):
print(f" [curv_seg_v4] running (prereq for v8)...", flush=True)
try:
result["curv_seg_v4"] = run_stage_v4(mesh_for_run, uid_out)
except Exception as e:
result["curv_seg_v4"] = {"status": "failed", "error": str(e)}
result["mesh_mapping_v8"] = {"status": "failed", "error": f"v4 prereq: {e}"}
result["status"] = "failed"
result["error"] = f"curv_seg_v4: {e}"
return result
else:
result["curv_seg_v4"] = {"status": "skipped"}
print(f" [mesh_mapping_v8] running...", flush=True)
try:
result["mesh_mapping_v8"] = run_stage_v8(mesh_for_run, uid_out)
except Exception as e:
result["mesh_mapping_v8"] = {"status": "failed", "error": str(e)}
result["status"] = "failed"
result["error"] = f"mesh_mapping_v8: {e}"
return result
result["status"] = "ok"
# Write the per-uid summary.json.
_to_py = lambda o: (float(o) if isinstance(o, np.floating) else
int(o) if isinstance(o, np.integer) else
o.tolist() if isinstance(o, np.ndarray) else o)
with open(os.path.join(uid_out, "summary.json"), "w") as f:
json.dump(result, f, indent=2, default=_to_py)
return result
# ============================================================
# Subprocess isolation
# ============================================================
def _worker(uid, mesh_root, shard, output_root, q):
try:
r = process_one(uid, mesh_root, shard, output_root)
q.put(r)
except Exception as e:
q.put({"uid": uid, "status": "failed", "error": str(e),
"traceback": traceback.format_exc()})
def process_one_isolated(uid, mesh_root, shard, output_root, timeout_sec=1800):
import multiprocessing as mp
ctx = mp.get_context("spawn")
q = ctx.Queue()
p = ctx.Process(target=_worker, args=(uid, mesh_root, shard, output_root, q))
p.start()
p.join(timeout=timeout_sec)
if p.is_alive():
print(f" [isolate] TIMEOUT {timeout_sec}s -> terminate", flush=True)
p.terminate(); p.join(5)
if p.is_alive():
p.kill(); p.join()
return {"uid": uid, "status": "failed", "error": f"timeout {timeout_sec}s"}
res = None
try:
if not q.empty():
res = q.get(timeout=2)
except Exception:
res = None
if p.exitcode != 0:
sig = f"signal {-p.exitcode}" if p.exitcode < 0 else f"exit {p.exitcode}"
if res is not None:
res.setdefault("error", f"worker died ({sig})")
return res
return {"uid": uid, "status": "failed", "error": f"worker died ({sig})"}
if res is None:
return {"uid": uid, "status": "failed", "error": "no result"}
return res
# ============================================================
# Main
# ============================================================
def main():
ap = argparse.ArgumentParser(description="HY3D sq_fit_v20 + mesh_mapper_v8 batch runner")
ap.add_argument("--mesh_root", required=True,
help="mesh root; meshes at <mesh_root>/<shard>/<uid>/full.ply")
ap.add_argument("--shard", default=DEFAULT_SHARD)
ap.add_argument("--output_root", required=True)
ap.add_argument("--uids_file", default=None,
help="uid list .txt/.json; omit to scan the shard dir")
ap.add_argument("--start_index", type=int, default=0,
help="index into uid list to start from (inclusive, default 0)")
ap.add_argument("--end_index", type=int, default=200,
help="index into uid list to stop at (exclusive, default 200)")
ap.add_argument("--no_isolate", action="store_true", help="run in same process (debug)")
ap.add_argument("--timeout_sec", type=int, default=1800)
args = ap.parse_args()
uids_file = args.uids_file if args.uids_file else None
all_uids = discover_uids(args.mesh_root, args.shard, uids_file)
total = len(all_uids)
s = max(0, args.start_index)
e = min(total, args.end_index) if args.end_index > 0 else total
if s >= e:
raise SystemExit(f"[batch] empty slice: start_index={s} end_index={e} total={total}")
uids = all_uids[s:e]
print(f"[batch] {len(uids)} uid(s) to process (slice [{s}:{e}) of {total})")
print(f"[batch] uids_file = {uids_file or '(scan shard dir)'}")
print(f"[batch] mesh_root = {args.mesh_root}")
print(f"[batch] shard = {args.shard}")
print(f"[batch] output_root = {args.output_root}")
os.makedirs(args.output_root, exist_ok=True)
summary_path = os.path.join(args.output_root, "batch_summary.json")
all_stats: list[dict] = []
if os.path.exists(summary_path):
try:
all_stats = json.load(open(summary_path))
done = {s["uid"] for s in all_stats if s.get("status") in ("ok", "skipped")}
print(f"[batch] resume: {len(done)} uids already in batch_summary.json", flush=True)
except Exception:
all_stats = []
for i, uid in enumerate(uids):
print("\n" + "=" * 72, flush=True)
print(f"[{i+1:3d}/{len(uids)}] {uid}", flush=True)
print("=" * 72, flush=True)
# Fast path: both stages are already complete.
uid_out = os.path.join(args.output_root, uid)
if stage_sq_done(uid_out) and stage_v8_done(uid_out):
print(" -> both stages done, skip", flush=True)
s = {"uid": uid, "status": "skipped", "reason": "both_done"}
else:
try:
if args.no_isolate:
s = process_one(uid, args.mesh_root, args.shard, args.output_root)
else:
s = process_one_isolated(
uid, args.mesh_root, args.shard, args.output_root,
timeout_sec=args.timeout_sec,
)
except Exception as e:
traceback.print_exc()
s = {"uid": uid, "status": "failed", "error": str(e)}
all_stats = [x for x in all_stats if x.get("uid") != uid]
all_stats.append(s)
_to_py = lambda o: (float(o) if isinstance(o, np.floating) else
int(o) if isinstance(o, np.integer) else
o.tolist() if isinstance(o, np.ndarray) else o)
with open(summary_path, "w") as f:
json.dump(all_stats, f, indent=2, default=_to_py)
st = s.get("status")
if st == "ok":
sq = s.get("sq_fit_v20", {})
v8 = s.get("mesh_mapping_v8", {})
print(f" -> OK sq:{sq.get('status')} v8:{v8.get('status')}", flush=True)
elif st == "skipped":
print(f" -> SKIPPED ({s.get('reason','?')})", flush=True)
else:
print(f" -> FAILED: {s.get('error','?')}", flush=True)
ok = [s for s in all_stats if s.get("status") == "ok"]
skipped = [s for s in all_stats if s.get("status") == "skipped"]
failed = [s for s in all_stats if s.get("status") == "failed"]
print(f"\n[done] ok={len(ok)} skipped={len(skipped)} failed={len(failed)} "
f"| summary={summary_path}")
if __name__ == "__main__":
main()
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