Datasets:
metadata
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
@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}
}
arXiv preprint
Composition
Published as two splits:
web: 358,292 rows. URL-only, no image bytes hosted. Reconstruct locally withimg2dataset. Obtained directly from Re-LAION-5B.synthetic: 856,467 rows. Actual image bytes, generated with 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.
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, 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 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):
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:
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")
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