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docs(usage): add Open3D RANSAC baseline (§6) + format polish (#99)
* docs(usage): add Open3D RANSAC baseline (§6) + format polish - python/examples/evaluate_ransac_in_semantickitti.py: new eval driver built on open3d.geometry.PointCloud.segment_plane. Same metric definitions and --eval_protocol flag as evaluate_semantickitti.py, with --distance_threshold / --num_iterations knobs and an optional --sweep_thresholds / --sweep_iterations grid. Per-frame median ms is reported alongside P/R/F1. - USAGE.md §6: full 6×5 grid (thr ∈ {0.10..0.50}, iter ∈ {100..10000}) on KITTI seq 00 — F1 saturates between iter=500 and iter=1000 (the highest-iter cell only buys +0.07 F1 anywhere in the table), F1 ridge is at thr=0.15. Best config (thr=0.15, iter=1000) evaluated on full KITTI 00-10 gives macro P=94.18 / R=82.03 / F1=87.11 at 19.5 ms median per frame — +9.18 F1 behind Patchwork++ on the macro and -25.88 F1 on the worst sequence (seq 10, rolling rural). - USAGE.md top: full README-style centered header block with badges, demo gif, pip-install banner (matches README.md for consistency). - USAGE.md section headings now use ## :emoji: N. ... form per the format-readme template; existing 70-underscore dividers retained. No algorithmic change; new script + docs only. * style: apply black to evaluate_ransac_in_semantickitti.py
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USAGE.md

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# Patchwork++ — Usage Guide
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<div align="center">
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<h1>Patchwork++</h1>
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<a href="https://github.com/url-kaist/patchwork-plusplus/tree/master/patchworkpp"><img src="https://img.shields.io/badge/-C++-blue?logo=cplusplus" /></a>
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<a href="https://github.com/url-kaist/patchwork-plusplus/tree/master"><img src="https://img.shields.io/badge/Python-3670A0?logo=python&logoColor=ffdd54" /></a>
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<a href="https://github.com/url-kaist/patchwork-plusplus/tree/master/ros"><img src="https://img.shields.io/badge/ROS2-Humble-blue" /></a>
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<a href="https://github.com/url-kaist/patchwork-plusplus/tree/master"><img src="https://img.shields.io/badge/Ubuntu-E95420?logo=ubuntu&logoColor=white" /></a>
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<a href="https://github.com/url-kaist/patchwork-plusplus/tree/master"><img src="https://img.shields.io/badge/macOS-000000?logo=apple&logoColor=white" /></a>
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<a href="https://github.com/url-kaist/patchwork-plusplus/tree/master"><img src="https://img.shields.io/badge/Windows-0078D6?logo=windows&logoColor=white" /></a>
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<a href="https://arxiv.org/abs/2207.11919"><img src="https://img.shields.io/badge/arXiv-b33737?logo=arXiv" /></a>
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<a href="https://ieeexplore.ieee.org/document/9981561"><img src="https://img.shields.io/badge/DOI-10.1109/IROS47612.2022.9981561-004088.svg"/></a>
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<br />
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<a href="https://github.com/url-kaist/patchwork-plusplus/actions/workflows/cpp.yml"><img src="https://github.com/url-kaist/patchwork-plusplus/actions/workflows/cpp.yml/badge.svg?branch=master" alt="C++ API" /></a>
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<a href="https://github.com/url-kaist/patchwork-plusplus/actions/workflows/python.yml"><img src="https://github.com/url-kaist/patchwork-plusplus/actions/workflows/python.yml/badge.svg?branch=master" alt="Python API" /></a>
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<br />
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<br />
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<a href=https://www.youtube.com/watch?v=fogCM159GRk>Video</a>
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<span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
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<a href="https://github.com/url-kaist/patchwork-plusplus/tree/master/README.md###Python">Install</a>
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<span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
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<a href="https://github.com/url-kaist/patchwork-plusplus/tree/master/ros">ROS2</a>
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<span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
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<a href=https://www.youtube.com/watch?v=fogCM159GRk>Paper</a>
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<span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
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<a href=https://github.com/url-kaist/patchwork-plusplus/issues>Contact Us</a>
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<br />
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<br />
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<p align="center"><img src=pictures/patchwork++.gif alt="animated" /></p>
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<p align="center">
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<strong>(May 19, 2026)</strong> pip installation is now live:
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<br/>
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<a href="https://pypi.org/project/pypatchworkpp/"><img src="https://readme-typing-svg.demolab.com?background=0D1117&color=22C55E&font=Fira+Code&size=18&duration=2500&pause=800&center=true&vCenter=true&width=320&height=30&lines=%24+pip+install+pypatchworkpp" alt="pip install pypatchworkpp"/></a>
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</p>
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[Patchwork++][arxivlink], an extension of [Patchwork][patchworklink], is **a fast, robust, and self-adaptive ground segmentation algorithm** on 3D point cloud.
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</div>
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______________________________________________________________________
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# :books: Usage Guide
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This guide covers three things that are easy to get wrong on first contact:
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______________________________________________________________________
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## 1. Evaluation protocols
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## :scroll: 1. Evaluation protocols
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The Patchwork and Patchwork++ papers use **different** ground-truth definitions on SemanticKITTI. The eval driver `python/examples/evaluate_semantickitti.py` supports both via `--eval_protocol {patchwork, patchworkpp}`.
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______________________________________________________________________
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## 2. Parameter tuning
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## :wrench: 2. Parameter tuning
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If results look wrong on a new sensor (Velodyne 16/32, Ouster 64/128, Livox, etc.), tune in roughly this order. Defaults are in `cpp/patchworkpp/include/patchwork/patchworkpp.h` (Patchwork++) and `cpp/patchwork/include/patchwork/patchwork.h` (classic Patchwork).
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______________________________________________________________________
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## 3. Reproducing paper Table I
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## :rocket: 3. Reproducing paper Table I
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```bash
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# 1. Install once
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______________________________________________________________________
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## 4. Official benchmarks
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## :bar_chart: 4. Official benchmarks
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KITTI 00-10 full sweep, **23,201 frames**, macro-average across the eleven sequences. All numbers are produced by `python/examples/evaluate_semantickitti.py` on current `master` (v1.3.1) with paper-matched parameters (the script already sets `uprightness_thr=0.707` and `using_global_thr=false` for `--method patchwork`; `--method patchworkpp` uses library defaults).
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## 5. Per-sequence performance
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## :chart_with_upwards_trend: 5. Per-sequence performance
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All numbers below are produced by `python/examples/evaluate_semantickitti.py` on v1.3.1 (current `master`), KITTI 00-10, paper-matched parameters. Use them to debug per-sequence regressions: if seq 05 looks fine but seq 10 is 3 F1 below the table, you have a parameter problem, not a code problem.
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## See also
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## :vs: 6. RANSAC baseline (Open3D `segment_plane`)
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A common first instinct on a new dataset is to fit a single plane with RANSAC and call the inliers "ground". `python/examples/evaluate_ransac_in_semantickitti.py` does exactly that, on top of Open3D's `segment_plane`, with the same metric definitions and `--eval_protocol` flag as `evaluate_semantickitti.py`, so the numbers drop directly into the same comparison frame as §5.
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```bash
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# Single (thr, iter) point — defaults to thr=0.15, iter=500
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python python/examples/evaluate_ransac_in_semantickitti.py \
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--distance_threshold 0.15 --num_iterations 1000 \
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--eval_protocol patchworkpp
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# Full sweep across a (thr × iter) grid
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python python/examples/evaluate_ransac_in_semantickitti.py \
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--seqs 00 \
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--sweep_thresholds 0.10,0.15,0.25,0.30,0.40,0.50 \
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--sweep_iterations 100,500,1000,5000,10000 \
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--eval_protocol patchworkpp \
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--output_csv summary_ransac_seq00_grid.csv
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```
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### Grid sweep on KITTI seq 00 (4541 frames, `--eval_protocol patchworkpp`)
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`distance_threshold` (rows) is the max point-to-plane distance counted as inlier (metres). `num_iterations` (columns) is the RANSAC hypothesis cap; Open3D's `segment_plane` early-terminates when a hypothesis crosses an internal confidence bound, so this is a **maximum** not an exact iteration count. `ransac_n=3` throughout (plane). Cell value is **F1 (%)**; second line is the **median wall-clock ms** of `segment_plane` per frame.
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| thr \\ iter | 100 | 500 | 1000 | 5000 | 10000 |
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| ----------- | ---------------- | ---------------- | ---------------- | ---------------- | ------------------- |
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| 0.10 | 82.67 (16.5 ms) | 88.69 (34.6 ms) | 89.31 (37.5 ms) | 89.31 (56.6 ms) | 89.33 (56.7 ms) |
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| **0.15** | 89.34 (17.1 ms) | 93.12 (29.3 ms) | **93.28 (29.3 ms)** | 93.30 (40.7 ms) | **93.35 (40.8 ms)** |
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| 0.25 | 90.94 (17.4 ms) | 92.34 (24.0 ms) | 92.72 (24.2 ms) | 92.52 (30.4 ms) | 92.52 (30.5 ms) |
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| 0.30 | 89.54 (17.5 ms) | 90.16 (22.6 ms) | 90.20 (22.4 ms) | 90.35 (27.5 ms) | 90.21 (27.7 ms) |
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| 0.40 | 84.38 (15.8 ms) | 84.72 (18.6 ms) | 84.78 (20.4 ms) | 84.75 (22.8 ms) | 84.71 (23.0 ms) |
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| 0.50 | 79.43 (18.3 ms) | 80.25 (17.8 ms) | 80.16 (18.1 ms) | 80.24 (18.4 ms) | 80.02 (18.6 ms) |
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Wall-clock numbers are median per-frame ms of `segment_plane` on an i7-12700; the 24-thread parallel default of Open3D is used for iter ≤ 1000, and 8 threads (`OMP_NUM_THREADS=8`) for iter ≥ 5000 (the 24-thread iter=10000 run exhausted system memory). Compare F1 numbers across columns freely; absolute ms across iter≤1000 and iter≥5000 columns are not directly comparable.
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### Reading the grid
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- **`distance_threshold` is the dominant knob, and the F1 column has a clear inverted-U.** Tight thresholds (0.10 m) over-reject — precision saturates near 96.7 but recall caps at 83. Loose thresholds (0.40–0.50 m) over-accept — precision falls below 81. The F1 ridge sits firmly at **thr=0.15**, no matter how many iterations RANSAC is allowed.
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- **`num_iterations` saturates between 500 and 1000.** Going from 100 → 500 buys 3–6 F1; 500 → 1000 buys 0.0–0.6; 1000 → 10000 buys at most **+0.07 F1** anywhere in the table — well inside run-to-run noise. Open3D's early-termination is the cause: for thr ≥ 0.15 the wall-clock barely moves between iter=1000 and iter=10000, confirming that the inner loop stops on its own well before the cap. Only thr=0.10 keeps the loop running to the cap (37.5 → 56.7 ms going 1000 → 10000), and even there F1 changes by 0.02.
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- **The dominant-plane assumption is the ceiling.** The best cell on the entire grid is `thr=0.15, iter=10000 → F1=93.35`, indistinguishable from `thr=0.15, iter=1000 → F1=93.28`. Practically there is no high-iter config that meaningfully improves on the cheap one; the algorithmic ceiling is set by the single-plane model, not by RANSAC's iteration budget.
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### Best config on the full KITTI 00–10 sweep
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Picking `thr=0.15, iter=1000` (ties the highest-iter F1 at this threshold, runs faster) and evaluating on all 23,201 frames under the Patchwork++ paper protocol:
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| seq | frames | Precision | Recall | F1 |
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| ------- | --------- | --------- | --------- | --------- |
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| 00 | 4541 | 95.37 | 91.63 | 93.31 |
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| 01 | 1101 | 98.33 | 87.74 | 92.52 |
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| 02 | 4661 | 94.34 | 80.44 | 86.27 |
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| 03 | 801 | 97.92 | 77.49 | 85.79 |
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| 04 | 271 | 97.70 | 87.90 | 92.42 |
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| 05 | 2761 | 93.01 | 88.09 | 90.26 |
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| 06 | 1101 | 97.29 | 79.67 | 87.52 |
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| 07 | 1101 | 92.68 | 89.33 | 90.81 |
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| 08 | 4071 | 93.33 | 78.20 | 83.88 |
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| 09 | 1591 | 96.75 | 80.68 | 87.65 |
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| 10 | 1201 | 79.23 | 61.17 | 67.75 |
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| **Avg** | **23201** | **94.18** | **82.03** | **87.11** |
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Median wall-clock 19.5 ms / frame (51.2 Hz) with Open3D's default 24-thread parallelism on an i7-12700.
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### Macro comparison — RANSAC vs. Patchwork / Patchwork++ on KITTI 00–10
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Side-by-side with the §5 numbers, under `--eval_protocol patchworkpp` on the same 23,201 frames:
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| Method | Precision | Recall | F1 | Median ms |
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| ------------------------------------------------------- | --------- | --------- | --------- | --------- |
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| Open3D RANSAC (best: thr=0.15, iter=1000) | 94.18 | 82.03 | 87.11 | ~19.5 |
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| Classic Patchwork (this repo, v1.4.0) | 94.64 | 97.58 | 96.02 | ~9 |
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| **Patchwork++ (this repo, v1.4.0)** | **95.55** | **97.16** | **96.29** | ~18 |
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**Patchwork++ wins by +9.18 F1 on the macro average** and roughly **matches** RANSAC on wall-clock per frame (~18 ms vs. ~19.5 ms), even though Patchwork++ is currently single-threaded on v1.4.0 (TBB intentionally disabled; see #96) while Open3D's `segment_plane` is using all 24 cores. The recall column is where the gap concentrates: RANSAC's 82.03 vs. Patchwork++'s 97.16 — a single global plane simply cannot cover the multiple ground patches that the concentric-zone partition handles natively.
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### Per-sequence gap to Patchwork++
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The macro gap is not uniform; it is dragged down by the hard sequences:
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| seq | scene | RANSAC F1 | Patchwork++ F1 | Δ |
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| --- | --------------------------- | --------- | -------------- | --------- |
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| 00 | residential, mild slope | 93.31 | 96.62 | -3.31 |
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| 01 | highway | 92.52 | 97.34 | -4.82 |
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| 02 | residential, parked cars | 86.27 | 96.35 | -10.08 |
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| 03 | short urban | 85.79 | 97.21 | -11.42 |
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| 04 | short highway | 92.42 | 97.25 | -4.83 |
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| 05 | undulating road | 90.26 | 94.84 | -4.58 |
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| 06 | open road | 87.52 | 97.61 | -10.09 |
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| 07 | inner-city | 90.81 | 95.56 | -4.75 |
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| 08 | dense urban | 83.88 | 96.74 | -12.86 |
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| 09 | rural | 87.65 | 96.06 | -8.41 |
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| 10 | rough rural / rolling roads | **67.75** | **93.63** | **-25.88** |
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Sequences with a gap below 5 F1 (00, 01, 04, 05, 07) are essentially flat with a single dominant ground plane — exactly where the single-plane assumption holds. Sequences with a gap above 10 F1 (02, 03, 06, 08, 10) all have rolling shoulders, multi-tier sidewalks, or rough off-road terrain — multiple ground patches that one plane cannot represent. Seq 10 is the extreme case: rolling rural terrain where one global plane is so wrong RANSAC drops below 70 F1 while Patchwork++ stays above 93 F1.
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### Takeaway
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RANSAC is the obvious sanity-check baseline for ground segmentation. On KITTI it is **9 F1 behind the macro Patchwork++ row, 26 F1 behind on the worst sequence, and no improvement at higher iteration counts can close that gap** — the bottleneck is the model, not the optimiser. The concentric-zone partition that Patchwork and Patchwork++ both use turns this from a hard problem (one plane for the whole scan) into many easy ones (one plane per patch, with per-patch flatness and elevation gates), which is what closes the gap.
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### Caveats
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- `ransac_n=3` (plane) is the only value tested. Higher `ransac_n` fits higher-order surfaces and is out of scope here.
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- The grid timing uses Open3D's default thread pool at iter ≤ 1000 and an 8-thread cap at iter ≥ 5000 (memory pressure at 24 threads × iter=10000 forced the cap). F1 numbers are insensitive to thread count; wall-clock numbers between low-iter and high-iter columns are **not** directly comparable. The full-KITTI Patchwork++ comparison row uses 24 threads on both sides.
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- The Patchwork++ wall-clock row above (~18 ms median, single-threaded) is conservative. Enabling TBB on the Patchwork++ side (currently disabled — see #96) is expected to roughly halve it and widen the Hz gap further. Classic Patchwork (v1.4.0) is already TBB-parallel and runs at ~9 ms median on this machine.
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______________________________________________________________________
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## :link: See also
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- [`python/examples/demo_visualize.py`](python/examples/demo_visualize.py) — single-frame visualisation.
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- [`python/examples/demo_sequential.py`](python/examples/demo_sequential.py) — iterate over a folder of `.bin` files.
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- Issues: [#87](https://github.com/url-kaist/patchwork-plusplus/issues/87) (reproduce paper), [#88](https://github.com/url-kaist/patchwork-plusplus/issues/88) (evaluation protocol), [#89](https://github.com/url-kaist/patchwork-plusplus/issues/89) (performance enhancement).
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[arxivlink]: https://arxiv.org/abs/2207.11919
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[patchworklink]: https://github.com/LimHyungTae/patchwork

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