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>
23 lines
663 B
Bash
23 lines
663 B
Bash
#!/usr/bin/env bash
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# SUM Parts - inspect the prediction PLY the POC inference run produced
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set -euo pipefail
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CONDA_ROOT="$HOME/miniconda3"
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ENV_NAME="sumparts"
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LOGROOT="$HOME/sum-parts/semantic_segmentation/PointNeXt_bundle/examples/segmentation/log"
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SCRIPTS="/mnt/d/MYCLAUDE_PROJECT/sum-parts-test/scripts"
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source "$CONDA_ROOT/etc/profile.d/conda.sh"
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conda activate "$ENV_NAME"
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PRED=$(find "$LOGROOT" -name '*_pred.ply' -printf '%T@ %p\n' | sort -rn | head -1 | cut -d' ' -f2-)
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if [ -z "$PRED" ]; then
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echo "error: no *_pred.ply found under $LOGROOT" >&2
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exit 1
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fi
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echo "prediction: $PRED"
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ls -lh "$PRED"
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echo
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python "$SCRIPTS/check_pred.py" "$PRED"
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