Add SUM Parts reproduction and Seosan Myeongcheon application pipeline

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>

scripts/final_eval.sh

@@ -0,0 +1,84 @@
+#!/usr/bin/env bash
+# SUM Parts - final evaluation of the trained checkpoint
+#
+# Two passes, because the splits differ in what they can tell you:
+#
+#   val  : labeled (0..12) -> produces real numbers you can quote locally
+#   test : label = -1 everywhere (blind set) -> produces predictions only.
+#          The authors score it; see the README's "send predictions to our
+#          email for local assessment".
+#
+# Requires patch_unlabeled_test.sh and patch_val_mode.sh to have run, otherwise
+# the test pass dies in ConfusionMatrix on the -1 placeholders and mode=val dies
+# with UnboundLocalError on `epoch`.
+#
+# No voxel_max override here on purpose. The cfg already validates with
+# voxel_max: null (whole tiles), which is what we want for the final number --
+# training capped it only to keep the allocator inside VRAM. Passing
+# `dataset.val.voxel_max=null` on the command line does NOT work: it arrives as
+# the string "null" and crop_pc then compares int >= str.
+set -uo pipefail
+
+CONDA_ROOT="$HOME/miniconda3"
+SEG="$HOME/sum-parts/semantic_segmentation/PointNeXt_bundle/examples/segmentation"
+DATA="$HOME/sum-parts/data/face_labeling/texsp_pcl"
+OUT="$HOME/sum-parts/runs/final_eval"
+
+source "$CONDA_ROOT/etc/profile.d/conda.sh"
+conda activate sumparts
+export WANDB_MODE=disabled WANDB_SILENT=true CUDA_HOME="$CONDA_PREFIX"
+export PYTORCH_CUDA_ALLOC_CONF="garbage_collection_threshold:0.7,max_split_size_mb:128"
+
+mkdir -p "$OUT"
+
+CKPT=$(find "$SEG/log/sumv2_triangle" -name '*_ckpt_best.pth' -printf '%T@ %p\n' \
+       | sort -rn | head -1 | cut -d' ' -f2-)
+[ -n "$CKPT" ] || { echo "error: no checkpoint found" >&2; exit 1; }
+
+echo "checkpoint: $CKPT"
+echo "data      : $DATA"
+echo
+
+cd "$SEG"
+
+run_mode() {
+    local mode="$1" log="$OUT/${1}.log"
+    echo "=== mode=$mode ==="
+    set +e
+    python -u main.py \
+        --cfg ../../cfgs/sumv2_triangle/pointnet.yaml \
+        mode="$mode" \
+        --pretrained_path "$CKPT" \
+        dataset.common.data_root="$DATA" \
+        wandb.use_wandb=False \
+        val_batch_size=1 \
+        > "$log" 2>&1
+    local rc=$?
+    set -e
+    if [ $rc -eq 0 ]; then
+        echo "  ok"
+    else
+        echo "  FAILED rc=$rc"
+        tail -12 "$log"
+    fi
+    grep -aE 'val_oa|test_oa|iou per cls|Best ckpt' "$log" | tail -6
+    echo
+    return $rc
+}
+
+# val first: this is the number we can actually stand behind locally
+run_mode val
+val_rc=$?
+
+# test: predictions only, no score possible
+run_mode test
+test_rc=$?
+
+echo "=== prediction files ==="
+find "$SEG/log/sumv2_triangle" -name '*_pred.ply' -newermt '-30 minutes' \
+    -printf '%p  (%s bytes)\n' 2>/dev/null | tail -12
+
+echo
+echo "logs in $OUT"
+[ $val_rc -eq 0 ] && echo "FINAL EVAL: val OK" || echo "FINAL EVAL: val FAILED"
+[ $test_rc -eq 0 ] && echo "FINAL EVAL: test OK" || echo "FINAL EVAL: test FAILED"