Datasets:

loopdesk-ai
/

lipika-eval

license: apache-2.0
task_categories:
  - image-classification
language:
  - hi
  - mr
  - ne
  - sa
  - bn
  - as
  - pa
  - gu
  - or
  - ta
  - te
  - kn
  - ml
  - ur
  - sat
  - mni
  - en
tags:
  - font-identification
  - font-recognition
  - indic
  - typography
  - synthetic
pretty_name: Lipika eval — Indic font recognition benchmark
size_categories:
  - 1K<n<10K
dataset_info:
  features:
    - name: image
      dtype: image
    - name: family
      dtype: string
    - name: script
      dtype: string
    - name: weight
      dtype: int32
    - name: italic
      dtype: bool
    - name: font_file
      dtype: string
    - name: font_license
      dtype: string
    - name: font_source
      dtype: string
  splits:
    - name: validation
      num_bytes: 293259746
      num_examples: 6876
  download_size: 289898553
  dataset_size: 293259746
configs:
  - config_name: default
    data_files:
      - split: validation
        path: data/validation-*

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}
}