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>
114 lines
3.9 KiB
Bash
114 lines
3.9 KiB
Bash
#!/usr/bin/env bash
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# SUM Parts - build only the CUDA extensions (rerunnable)
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#
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# Split out of setup_pointnext.sh so a failed compile can be retried without
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# reinstalling every python dependency.
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#
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# ninja note: torch 2.0's cpp_extension shells out to `ninja -v` and reads its
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# output through a pipe. ninja >= 1.12 dies with SIGPIPE there, which torch
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# surfaces only as the useless "Error compiling objects for extension".
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# Pinning ninja to 1.11.x avoids it.
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set -euo pipefail
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CONDA_ROOT="$HOME/miniconda3"
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ENV_NAME="sumparts"
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REPO="$HOME/sum-parts/semantic_segmentation/PointNeXt_bundle"
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source "$CONDA_ROOT/etc/profile.d/conda.sh"
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conda activate "$ENV_NAME"
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export TORCH_CUDA_ARCH_LIST="8.6" # RTX 3060
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export CUDA_HOME="$CONDA_PREFIX"
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export PATH="$CUDA_HOME/bin:$PATH"
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export MAX_JOBS="${MAX_JOBS:-4}"
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echo "=== pin ninja to 1.11.x ==="
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pip install --no-cache-dir "ninja==1.11.1.1"
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ninja --version
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# subsampling/setup.py imports numpy.distutils, which imports
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# distutils.msvccompiler. setuptools removed that module in 74.0, so anything
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# newer dies with "No module named 'distutils.msvccompiler'".
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echo "=== pin setuptools to 69.5.1 (numpy.distutils needs it) ==="
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pip install --no-cache-dir "setuptools==69.5.1"
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python -c "import setuptools; print('setuptools', setuptools.__version__)"
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# Skip extensions that already import cleanly, so a retry does not redo a
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# 5-minute nvcc pass that already succeeded. FORCE=1 rebuilds everything.
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have() { python -c "import $1" 2>/dev/null; }
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# NOTE: pointnet2_batch's setup.py names the extension pointnet2_batch_cuda,
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# not pointnet2_cuda as in upstream PointNet++ forks.
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if [ "${FORCE:-0}" = "1" ] || ! have pointnet2_batch_cuda; then
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echo "=== build pointnet2_batch ==="
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cd "$REPO/openpoints/cpp/pointnet2_batch"
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rm -rf build ./*.egg-info dist
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python setup.py install
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else
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echo "=== skip pointnet2_batch (already importable) ==="
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fi
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echo "=== build subsampling ==="
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cd "$REPO/openpoints/cpp/subsampling"
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rm -rf build ./*.so
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python setup.py build_ext --inplace
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if [ "${FORCE:-0}" = "1" ] || ! have pointops_cuda; then
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echo "=== build pointops ==="
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cd "$REPO/openpoints/cpp/pointops"
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rm -rf build ./*.egg-info dist
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python setup.py install
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else
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echo "=== skip pointops (already importable) ==="
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fi
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# chamfer_dist and emd only matter for reconstruction tasks, but
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# openpoints/models/__init__.py imports .reconstruction unconditionally, which
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# imports chamfer_dist -- so even a pure segmentation run fails at import time
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# without them. They are not optional in practice.
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if [ "${FORCE:-0}" = "1" ] || ! have chamfer; then
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echo "=== build chamfer_dist ==="
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cd "$REPO/openpoints/cpp/chamfer_dist"
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rm -rf build ./*.egg-info dist
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python setup.py install
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else
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echo "=== skip chamfer_dist (already importable) ==="
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fi
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# emd/setup.py names the package emd_ext and the extension emd_cuda; plain
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# `emd` is only the python-level alias in openpoints/cpp/emd/__init__.py.
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if [ "${FORCE:-0}" = "1" ] || ! have emd_cuda; then
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echo "=== build emd ==="
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cd "$REPO/openpoints/cpp/emd"
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rm -rf build ./*.egg-info dist
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python setup.py install
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else
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echo "=== skip emd (already importable) ==="
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fi
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echo "=== verify ==="
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cd "$REPO"
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python - <<'PY'
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import sys
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print("torch :", __import__("torch").__version__,
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"| cuda", __import__("torch").cuda.is_available())
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ok = True
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for m in ["pointnet2_batch_cuda", "pointops_cuda", "chamfer", "emd_cuda",
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"torch_scatter", "plyfile"]:
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try:
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__import__(m)
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print(f"{m:22s}: OK")
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except Exception as e:
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ok = False
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print(f"{m:22s}: FAIL {type(e).__name__}: {e}")
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try:
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from openpoints.cpp.subsampling import grid_subsampling # noqa: F401
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print(f"{'grid_subsampling':22s}: OK")
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except Exception as e:
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ok = False
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print(f"{'grid_subsampling':22s}: FAIL {type(e).__name__}: {e}")
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sys.exit(0 if ok else 1)
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PY
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echo "BUILD DONE"
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