Datasets:
File size: 3,420 Bytes
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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](https://huggingface.co/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](https://github.com/Loopdesk-AI/lipika), 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`](https://github.com/Loopdesk-AI/lipika/blob/main/src/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
```python
from datasets import load_dataset
ds = load_dataset("loopdesk-ai/lipika-eval", split="validation")
```
## Citation
```bibtex
@software{lipika2026,
title = {Lipika: Indic Font Recognition},
author = {Loopdesk},
year = {2026},
url = {https://huggingface.co/loopdesk-ai/lipika}
}
```
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