nbrightandClaude Opus 5
609d9a6972
Reproduces the SUM Parts (CVPR 2025) face-labeling benchmark on a single consumer GPU, then applies it to drone-photogrammetry road survey meshes. Verified on RTX 3060 12GB / WSL2 Ubuntu 22.04 / CUDA 11.8 / torch 2.0.1: - CUDA extensions build (pointnet2_batch, pointops, chamfer_dist, emd, subsampling) - PointNet 100 epochs reaches mIoU 17.19, matching the paper's reported 15.1 - OBJ -> PLY conversion round-trips through the model and yields per-point predictions Four upstream source patches, all idempotent, originals preserved: - numpy aliases removed in 1.24 (np.long etc.) and collections ABCs moved in python 3.10 - the blind test split ships label = -1, which crashed ConfusionMatrix - mode=val referenced `epoch` before assignment Documents the traps that cost the most time, including VRAM overflow silently falling back to host RAM on WSL2 (25-100x slowdown, no OOM) and the colour scale mismatch between r/g/b float32 and red/green/blue uint8. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
55 lines
1.3 KiB
Bash
55 lines
1.3 KiB
Bash
#!/usr/bin/env bash
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# SUM Parts - list an archive's contents without extracting it
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#
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# Used to count tiles per split, which is what turns a per-iteration benchmark
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# into a wall-clock training estimate.
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set -euo pipefail
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ARCHIVE="${1:-$HOME/sum-parts/data/_archives/mesh.zip}"
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source "$HOME/miniconda3/etc/profile.d/conda.sh"
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conda activate sumparts
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python - "$ARCHIVE" <<'PY'
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import re
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import sys
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import zipfile
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from collections import Counter
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from pathlib import Path
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path = Path(sys.argv[1])
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z = zipfile.ZipFile(path)
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names = z.namelist()
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print(f"=== {path.name} : {len(names)} entries ===\n")
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dirs = Counter()
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for n in names:
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p = "/".join(n.split("/")[:-1]) or "."
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dirs[p] += 1
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for d, c in sorted(dirs.items()):
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print(f" {c:>5} {d}/")
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print()
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splits = Counter()
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for n in names:
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m = re.search(r"(?:^|/)(train|val|test|training|validation)(?:/|_)", n, re.I)
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if m:
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splits[m.group(1).lower()] += 1
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if splits:
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print("split hints:", dict(splits))
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ply = [n for n in names if n.lower().endswith(".ply")]
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print(f"\n.ply entries: {len(ply)}")
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per_split = Counter(n.split("/")[0] for n in ply)
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for s, c in sorted(per_split.items()):
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print(f" {c:>4} ply in {s}/")
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for n in ply[:5]:
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print(f" e.g. {n}")
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total = sum(i.file_size for i in z.infolist())
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print(f"\nuncompressed total: {total / 1e9:.2f} GB")
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PY
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