Koshur Pixel: a large-scale synthetic ocr dataset for kashmiri
Optical Character Recognition (OCR) for low-resource languages is often constrained by the lack of annotated training data and the complexity of script-specific rendering. Kashmiri, written primarily in the Perso-Arabic Nastaliq script, presents additional challenges due to contextual glyph shaping, dense ligatures, and orthographic variability. We introduce Koshur Pixel, the first large-scale synthetic OCR dataset for Kashmiri, comprising 613,078 image-text pairs generated from the KS-PRET-5M corpus using the SynthOCR-Gen framework. The dataset spans multiple fonts and textual granularities, ranging from individual words to full-page documents, and incorporates more than 25 augmentation ...
| Authors | Haq Nawaz Malik, Faizan Iqbal, Nahfid Nissar |
|---|---|
| Primary category | cs.CV |
| Published | 22 June 2026 |
| Last updated at source | 22 June 2026 |
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