loopdesk-ai/lipika-eval

Lipika eval — Indic font recognition benchmark

The frozen validation set behind loopdesk-ai/lipika (Indic font recognizer): 6,876 synthetic text crops covering 553 freely-licensed font families across 13 scripts (Devanagari, Bengali, Gujarati, Gurmukhi, Kannada, Malayalam, Meetei Mayek, Odia, Ol Chiki, Perso-Arabic, Tamil, Telugu, Latin).

This is the set reported as "synthetic val" in the model card (Lipika v2.4 scores 0.849 family top-1 / 0.977 top-5 / 0.991 script). Use it to benchmark your own font-ID model or to reproduce ours.

How it was made

Crops are rendered with proper Indic shaping (HarfBuzz via a Pillow/raqm stack) from the open Lipika font corpus, with the frozen-eval augmentation distribution: varied sizes, colors, backgrounds, mild blur/noise/rotation, JPEG artifacts. Seed-frozen (seed 2028) — the generator lives in fontrecog/dataset/pregenerate_val.py.

Training data is not published as files — it is rendered on the fly from font files by the same pipeline; the corpus manifest + fetch scripts in the GitHub repo reproduce it.

Fields

Field	Description
image	RGB text crop
family	Font family label (one of 553)
script	Writing script of the rendered text
weight	CSS weight bucket 100–900
italic	Italic/oblique flag
font_file	Source font filename
font_license	Upstream font license (OFL, GPL+FE, freeware, …)
font_source	Corpus source (google_fonts, smc, ekushey, salrc, …)

Licensing

Dataset packaging & annotations: Apache-2.0. Images are bitmap renders of freely licensed / freely distributed fonts only (OFL, GPL with font exception, public freeware); each row carries its font's upstream license in font_license. Crops rendered from proprietary system fonts (10 families, 84 crops of the original 6,960) are excluded from this release; scores on this subset may differ from the model card's full-set numbers by <0.2pt.

Load

from datasets import load_dataset
ds = load_dataset("loopdesk-ai/lipika-eval", split="validation")

Citation

@software{lipika2026,
  title  = {Lipika: Indic Font Recognition},
  author = {Loopdesk},
  year   = {2026},
  url    = {https://huggingface.co/loopdesk-ai/lipika}
}