| ---
|
| license: mit
|
| task_categories:
|
| - object-detection
|
| tags:
|
| - curb-ramp
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| - accessibility
|
| - streetscape
|
| - benchmark
|
| - evaluation
|
| configs:
|
| - config_name: native
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| data_files:
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| - split: annapolis
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| path: data/native/annapolis.parquet
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| - split: bend
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| path: data/native/bend.parquet
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| - split: budapest_district5
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| path: data/native/budapest_district5.parquet
|
| - split: clovis
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| path: data/native/clovis.parquet
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| - split: gainesville
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| path: data/native/gainesville.parquet
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| - split: morgantown
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| path: data/native/morgantown.parquet
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| - split: paterson
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| path: data/native/paterson.parquet
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| - split: richmond
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| path: data/native/richmond.parquet
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| - split: sao_paulo
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| path: data/native/sao_paulo.parquet
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| - config_name: 4096x2048
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| data_files:
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| - split: annapolis
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| path: data/4096x2048/annapolis.parquet
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| - split: bend
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| path: data/4096x2048/bend.parquet
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| - split: budapest_district5
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| path: data/4096x2048/budapest_district5.parquet
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| - split: clovis
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| path: data/4096x2048/clovis.parquet
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| - split: gainesville
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| path: data/4096x2048/gainesville.parquet
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| - split: morgantown
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| path: data/4096x2048/morgantown.parquet
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| - split: paterson
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| path: data/4096x2048/paterson.parquet
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| - split: richmond
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| path: data/4096x2048/richmond.parquet
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| - split: sao_paulo
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| path: data/4096x2048/sao_paulo.parquet
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| - config_name: galleries
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| data_files:
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| - split: annapolis
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| path: data/galleries/annapolis.parquet
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| - split: bend
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| path: data/galleries/bend.parquet
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| - split: budapest_district5
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| path: data/galleries/budapest_district5.parquet
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| - split: clovis
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| path: data/galleries/clovis.parquet
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| - split: gainesville
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| path: data/galleries/gainesville.parquet
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| - split: morgantown
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| path: data/galleries/morgantown.parquet
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| - split: paterson
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| path: data/galleries/paterson.parquet
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| - split: richmond
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| path: data/galleries/richmond.parquet
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| - split: sao_paulo
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| path: data/galleries/sao_paulo.parquet
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| - config_name: records
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| data_files:
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| - split: annapolis
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| path: data/records/annapolis.parquet
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| - split: bend
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| path: data/records/bend.parquet
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| - split: budapest_district5
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| path: data/records/budapest_district5.parquet
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| - split: clovis
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| path: data/records/clovis.parquet
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| - split: gainesville
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| path: data/records/gainesville.parquet
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| - split: morgantown
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| path: data/records/morgantown.parquet
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| - split: paterson
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| path: data/records/paterson.parquet
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| - split: richmond
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| path: data/records/richmond.parquet
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| - split: sao_paulo
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| path: data/records/sao_paulo.parquet
|
| ---
|
|
|
| # RampNet Benchmark Imagery
|
|
|
| > ### ⚠️ This benchmark is **not** part of the RampNet paper
|
| >
|
| > It did not exist when RampNet was published. The paper's tag,
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| > [`v1.0-iccv2025`](https://github.com/ProjectSidewalk/RampNet/tree/v1.0-iccv2025) (August 2025),
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| > contains **no `benchmark/` directory at all** — its evaluation was a **1,000-panorama manually
|
| > labeled gold set** (`manual_labels/`, imagery in
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| > [`rampnet-dataset`](https://huggingface.co/datasets/projectsidewalk/rampnet-dataset)), drawn from
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| > the same three training cities.
|
| >
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| > These 9 city splits were built **eleven months later**, between 2026-07-22 and
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| > 2026-07-31, as post-publication work: to test the published model on cities and imagery sources
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| > it was never trained on, and to compare it against VLM detectors.
|
| >
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| > **Use this to evaluate RampNet. Do not cite it as the paper's evaluation** — the ground truth,
|
| > the cities, and the matching protocol all differ, so numbers measured here are not comparable
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| > with the ones in the paper.
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|
|
| The panoramas behind that benchmark — 9 city splits, 11.41 GB. Unlike the paper's
|
| gold set, the splits deliberately include **non-US cities and a second imagery source** (Mapillary
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| as well as Google Street View), which is the whole point: the paper's own evaluation was in-domain.
|
|
|
| It is self-contained: the `records` config carries the ground truth, so you can score a model
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| against this benchmark without cloning anything. The **rubrics** those verdicts were made under,
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| the per-split reviewer confidence, and the review notes stay in git at
|
| [`benchmark/`](https://github.com/ProjectSidewalk/RampNet/tree/main/benchmark) — read
|
| [`benchmark/RUBRICS.md`](https://github.com/ProjectSidewalk/RampNet/blob/main/benchmark/RUBRICS.md)
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| before treating a verdict as self-explanatory, and `benchmark/README.md` before quoting a
|
| precision figure, because several splits carry caveats the numbers alone do not show.
|
|
|
| ## Configs
|
|
|
| | config | what it is | when you want it |
|
| | :--- | :--- | :--- |
|
| | **`records`** | **the ground truth** — per-panorama metadata, model detections with their human verdict, and reviewer-marked missed ramps | scoring any model against this benchmark |
|
| | `native` | the panoramas exactly as fetched — 4096 to 16384 px wide, depending on city and imagery source | the resolution experiment; any re-render at higher fidelity |
|
| | `4096x2048` | the same panoramas at the model's input size | **what ground-truth reviewers actually saw** — `gt_gallery.py` renders at 4096×2048 and never native, so this is the config a second rater needs |
|
| | `galleries` | the incremental false-positive crops shown in the operating-point A/B pass | redoing that A/B |
|
|
|
| ### The `records` config
|
|
|
| One row per reviewed panorama, joinable to any imagery config on `pano_id`:
|
|
|
| | column | meaning |
|
| | :--- | :--- |
|
| | `source` | `gsv` or `mapillary` |
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| | `capture_date`, `lat`, `lng`, `camera_heading`, `width`, `height` | panorama metadata as fetched |
|
| | **`copyright`** | per-record source attribution, e.g. `© <contributor> / Mapillary (CC BY-SA 4.0)` |
|
| | `detections` | model detections: `x_normalized`, `y_normalized`, `confidence`, and **`verdict`** |
|
| | `missed` | ramps the reviewer marked that the model did not find, each with an `unsure` flag |
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| | `no_missed` | reviewer confirmed they checked the whole panorama and found nothing missed |
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| | `model_id`, `model_training_date`, `label_type` | which model produced the detections |
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|
|
| `verdict` is one of **`correct`**, **`incorrect`**, **`unsure`**, **`duplicate`**. `unsure` is an
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| abstention and `duplicate` marks a second detection of an already-matched ramp — both carry the
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| meaning the scorer gives them, so the labels mean exactly what the published precision/recall were
|
| computed against. Panoramas that were never reviewed are not included.
|
|
|
| **Labels are derived, not original.** `benchmark/<city>/records.jsonl` and `verdicts.json` in git
|
| are the source of truth; this config is regenerated from them by `scripts/export_benchmark.py`.
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| Verdicts get revised, imagery does not — keeping them in separate configs means a label correction
|
| never rewrites an image blob.
|
|
|
| Configs are named by **resolution, not by consumer**. "Model resolution" is a relative label that
|
| becomes wrong the moment the model's input size changes, and a published path cannot be corrected
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| later without replacing large blobs.
|
|
|
| Note that `4096x2048` is not uniformly smaller: for splits whose native imagery is already at or
|
| near model resolution it can be *larger*, because it carries an extra JPEG generation. It is a
|
| fidelity artifact — it reproduces what a reviewer's eyes were on — not a compression trick.
|
|
|
| ## Usage
|
|
|
| ```python
|
| from datasets import load_dataset
|
|
|
| # the ground truth for one split
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| gt = load_dataset("projectsidewalk/rampnet-benchmark", "records", split="gainesville")
|
| print(gt[0]["source"], gt[0]["capture_date"], gt[0]["copyright"])
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| print(gt[0]["detections"]) # each with x_normalized, y_normalized, confidence, verdict
|
| print(gt[0]["missed"]) # ramps the model did not find
|
|
|
| # the matching pixels, at the resolution reviewers saw
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| px = load_dataset("projectsidewalk/rampnet-benchmark", "4096x2048", split="gainesville")
|
| by_id = {r["pano_id"]: r["image"] for r in px}
|
| image = by_id[gt[0]["pano_id"]]
|
| ```
|
|
|
| Each row of an **imagery** config carries:
|
|
|
| | column | meaning |
|
| | :--- | :--- |
|
| | `pano_id` | panorama id — the join key to `benchmark/<city>/records.jsonl` in git |
|
| | `city` | split name |
|
| | `image` | the image, stored as the **exact source bytes**, not re-encoded on write |
|
| | `width`, `height` | pixel dimensions as stored |
|
| | `sha256` | hash of those exact bytes |
|
|
|
| ## Verifying you have the pixels the reviewers judged
|
|
|
| Same pano id and filename is **not** evidence the bytes are the ones a reviewer saw — a re-fetch
|
| from Google Street View or Mapillary can return re-stitched or re-compressed imagery. Two
|
| independent checks exist:
|
|
|
| 1. **Per row.** Every row carries the `sha256` of its own embedded bytes.
|
| `scripts/export_benchmark.py verify` re-hashes every image straight out of the Parquet, so the
|
| round trip through Parquet is checked rather than assumed.
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| 2. **Against the review.** `benchmark/<city>/imagery_manifest.json` in git records a sha256 and
|
| pixel size per panorama, pinned at the time each split was reviewed — 206 KB describing the
|
| whole archive. That is what ties these bytes to the verdicts.
|
|
|
| ```bash
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| python scripts/analysis/imagery_manifest.py --verify
|
| ```
|
|
|
| ## Provenance
|
|
|
| | Field | Value |
|
| | :--- | :--- |
|
| | Benchmark code and labels | https://github.com/ProjectSidewalk/RampNet @ `94be2c3` |
|
| | Exported | 2026-08-04 by `scripts/export_benchmark.py` |
|
| | Replication ledger | [`docs/replication.md`](https://github.com/ProjectSidewalk/RampNet/blob/main/docs/replication.md) |
|
| | How a split is built and reviewed | [`docs/adding_a_benchmark_city.md`](https://github.com/ProjectSidewalk/RampNet/blob/main/docs/adding_a_benchmark_city.md) |
|
|
|
| Imagery sources differ by city (Google Street View and Mapillary); per-split provenance, ground
|
| truth precision/recall, and reviewer confidence are documented in
|
| [`benchmark/README.md`](https://github.com/ProjectSidewalk/RampNet/blob/main/benchmark/README.md).
|
|
|
| ## Citation
|
|
|
| There is no separate publication for this benchmark. Cite the paper for **the pipeline and model
|
| being evaluated**, and please make clear that the evaluation set is post-publication rather than
|
| the paper's own:
|
|
|
| ```bibtex
|
| @inproceedings{omeara2025rampnet,
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| author = {John S. O'Meara and Jared Hwang and Zeyu Wang and Michael Saugstad and Jon E. Froehlich},
|
| title = {{RampNet: A Two-Stage Pipeline for Bootstrapping Curb Ramp Detection in Streetscape Images from Open Government Metadata}},
|
| booktitle = {{ICCV'25 Workshop on Vision Foundation Models and Generative AI for Accessibility: Challenges and Opportunities (ICCV 2025 Workshop)}},
|
| year = {2025},
|
| doi = {https://doi.org/10.48550/arXiv.2508.09415},
|
| }
|
| ```
|
|
|
