--- license: mit dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train_shard_000 num_bytes: 3084316377 num_examples: 5000 - name: train_shard_001 num_bytes: 3107698844 num_examples: 5000 - name: train_shard_002 num_bytes: 3105945625 num_examples: 5000 - name: train_shard_003 num_bytes: 3064000374 num_examples: 5000 - name: train_shard_004 num_bytes: 3086188608 num_examples: 5000 - name: train_shard_005 num_bytes: 3050610859 num_examples: 5000 - name: train_shard_006 num_bytes: 2913162440 num_examples: 5000 - name: train_shard_007 num_bytes: 2919830153 num_examples: 5000 - name: train_shard_008 num_bytes: 3038788195 num_examples: 5000 - name: train_shard_009 num_bytes: 3204065572 num_examples: 5000 - name: train_shard_010 num_bytes: 3068610931 num_examples: 5000 - name: train_shard_011 num_bytes: 2933208907 num_examples: 5000 - name: train_shard_012 num_bytes: 2891239225 num_examples: 5000 - name: train_shard_013 num_bytes: 3091212463 num_examples: 5000 - name: train_shard_014 num_bytes: 2921655324 num_examples: 5000 - name: train_shard_015 num_bytes: 2979943202 num_examples: 5000 - name: train_shard_016 num_bytes: 2868563209 num_examples: 5000 - name: train_shard_017 num_bytes: 3147002484 num_examples: 5000 - name: train_shard_018 num_bytes: 3104107514 num_examples: 5000 - name: train_shard_019 num_bytes: 2926535712.0 num_examples: 5000 - name: train_shard_020 num_bytes: 2990904342.0 num_examples: 5000 - name: train_shard_021 num_bytes: 3102893465.0 num_examples: 5000 - name: train_shard_022 num_bytes: 3059280331.0 num_examples: 5000 - name: train_shard_023 num_bytes: 3090584727.0 num_examples: 5000 - name: train_shard_024 num_bytes: 2926357592.0 num_examples: 5000 - name: train_shard_025 num_bytes: 2944175013.0 num_examples: 5000 - name: train_shard_026 num_bytes: 3007380998.0 num_examples: 5000 - name: train_shard_027 num_bytes: 3135483954.0 num_examples: 5000 - name: train_shard_028 num_bytes: 3025648842.0 num_examples: 5000 download_size: 87788380542 dataset_size: 87789395282.0 configs: - config_name: default data_files: - split: train_shard_000 path: data/train_shard_000-* - split: train_shard_001 path: data/train_shard_001-* - split: train_shard_002 path: data/train_shard_002-* - split: train_shard_003 path: data/train_shard_003-* - split: train_shard_004 path: data/train_shard_004-* - split: train_shard_005 path: data/train_shard_005-* - split: train_shard_006 path: data/train_shard_006-* - split: train_shard_007 path: data/train_shard_007-* - split: train_shard_008 path: data/train_shard_008-* - split: train_shard_009 path: data/train_shard_009-* - split: train_shard_010 path: data/train_shard_010-* - split: train_shard_011 path: data/train_shard_011-* - split: train_shard_012 path: data/train_shard_012-* - split: train_shard_013 path: data/train_shard_013-* - split: train_shard_014 path: data/train_shard_014-* - split: train_shard_015 path: data/train_shard_015-* - split: train_shard_016 path: data/train_shard_016-* - split: train_shard_017 path: data/train_shard_017-* - split: train_shard_018 path: data/train_shard_018-* - split: train_shard_019 path: data/train_shard_019-* - split: train_shard_020 path: data/train_shard_020-* - split: train_shard_021 path: data/train_shard_021-* - split: train_shard_022 path: data/train_shard_022-* - split: train_shard_023 path: data/train_shard_023-* - split: train_shard_024 path: data/train_shard_024-* - split: train_shard_025 path: data/train_shard_025-* - split: train_shard_026 path: data/train_shard_026-* - split: train_shard_027 path: data/train_shard_027-* - split: train_shard_028 path: data/train_shard_028-* pretty_name: tamily 1 language: - ta source_datasets: - sasicodes/solvari-1 task_categories: - image-to-text tags: - Vaṭṭeḻuttu --- # Tamily-1: Ancient Tamil OCR Synthetic Dataset ## Description - **Repository:** [sasicodes/tamily-1](https://huggingface.co/datasets/sasicodes/tamily-1) - **Point of Contact:** [@sasicodes](https://huggingface.co/sasicodes) ### Summary Tamily-1 is an ancient Tamil OCR synthetic dataset generated from the first 200,000 rows of [Solvari-1](https://huggingface.co/datasets/sasicodes/solvari-1), a large Tamil text corpus. The dataset contains rendered images of Tamil text with various augmentations and styles, making it suitable for training OCR models. ### Fields - `image`: PNG image of rendered Tamil text - `text`: Original Tamil text ### Data Splits The dataset is split into shards of 5,000 samples each, named as `train_shard_XXX`. #### Annotation process Each text is rendered with: - Random paper style (Palm Leaf, Pale Palm Leaf, Red Stone, White Stone, Paper) - Random background style (No Lines, With Lines, Blurred, With Lines and Noise) - Random augmentation (Rotation, Perspective, Stain, Ink Bleed) ### License MIT License ```bibtex @misc{tamily-1, author = {sasicodes}, title = {Tamily-1: Ancient Tamil OCR Synthetic Dataset}, year = {2025}, publisher = {Hugging Face}, journal = {Hugging Face Hub}, howpublished = {\url{https://huggingface.co/datasets/sasicodes/tamily-1}} } ```