---
license: cc-by-nc-4.0
task_categories:
- image-classification
tags:
- precision-at-scale
- birds
- arxiv:2407.03463
pretty_name: PaS-B
configs:
- config_name: web
  data_files: "PaS-B-web.parquet"
- config_name: synthetic
  data_files: "PaS-B-synthetic-*.parquet"
dataset_info:
- config_name: web
  features:
      - name: image_name
        dtype: string
      - name: url
        dtype: string
- config_name: synthetic
  features:
      - name: image
        dtype: image
      - name: image_name
        dtype: string
---

# PaS-B

Birds-domain dataset used to train the `PaS-B` checkpoint from
the *Precision at Scale* paper (1.2M images).

## Paper

- **Paper (Pattern Recognition, 2026):** https://doi.org/10.1016/j.patcog.2025.112236
- **Official code:** https://github.com/jesusmolrdv/Precision-at-Scale

```bibtex
@article{rodriguezdevera2026precision,
  title   = {Precision at scale: Domain-specific datasets on-demand},
  author  = {Rodr{\'i}guez-de-Vera, Jes{\'u}s M. and Estepa, Imanol G. and Saras{\'u}a, Ignacio and Nagarajan, Bhalaji and Radeva, Petia},
  journal = {Pattern Recognition},
  volume  = {171},
  pages   = {112236},
  year    = {2026},
  publisher = {Elsevier},
  doi     = {10.1016/j.patcog.2025.112236}
}
```

<details>
<summary>arXiv preprint</summary>

https://arxiv.org/abs/2407.03463

</details>

## Composition

Published as two splits:

- **`web`**: 358,292 rows. URL-only, no
  image bytes hosted. Reconstruct locally with
  [`img2dataset`](https://github.com/rom1504/img2dataset). Obtained directly
  from Re-LAION-5B.
- **`synthetic`**: 856,467 rows. Actual image bytes, generated
  with [stabilityai/stable-diffusion-2-1-base](https://huggingface.co/stabilityai/stable-diffusion-2-1-base).
  

## Data Owner Opt-Out

The `web` split contains only URLs pointing at third-party web images (no
image bytes), sourced from [Re-LAION-5B](https://laion.ai/blog/relaion-5b/).
If you own an image referenced by a URL in this split and want it removed:

- **From the upstream index**: submit a removal request via
  [Spawning's haveibeentrained.com](https://haveibeentrained.com), the
  official opt-out mechanism LAION uses to build each Re-LAION-5B revision.
- **From this specific redistribution**: since this split is a snapshot
  taken at a point in time, an upstream opt-out registered afterward won't
  automatically propagate here. Open an issue on the
  [official repository](https://github.com/jesusmolrdv/Precision-at-Scale/issues) with the URL(s) or
  `image_name`(s) in question, and they will be removed from future
  releases of this dataset.

## Usage

Load the `synthetic` split directly (image bytes are hosted):

```python
from datasets import load_dataset

synthetic = load_dataset("jesusmolrdv/pas-b", "synthetic", split="train")
```

The `web` split has no hosted image bytes, only URLs. Reconstruct it locally with
[`img2dataset`](https://github.com/rom1504/img2dataset):

```python
from datasets import load_dataset

web = load_dataset("jesusmolrdv/pas-b", "web", split="train").to_pandas()
web[["url", "image_name"]].to_parquet("PaS-B-web-urls.parquet")
```

```sh
img2dataset --url_list PaS-B-web-urls.parquet --input_format parquet \
    --url_col url --save_additional_columns '["image_name"]' \
    --output_folder PaS-B_web_images --output_format webdataset
```