Update README.md

README.md

@@ -1,24 +1,258 @@
 ---
+
+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
+    - name: train_shard_029
+      num_bytes: 2919552229.0
+      num_examples: 5000
+    - name: train_shard_030
+      num_bytes: 3060131937.0
+      num_examples: 5000
+    - name: train_shard_031
+      num_bytes: 3090467484.0
+      num_examples: 5000
+    - name: train_shard_032
+      num_bytes: 2873511036.0
+      num_examples: 5000
+    - name: train_shard_033
+      num_bytes: 2978930908.0
+      num_examples: 5000
+    - name: train_shard_034
+      num_bytes: 2919552229.0
+      num_examples: 5000
+    - name: train_shard_035
+      num_bytes: 3055357770
+      num_examples: 5000
+    download_size: 102710794870
+    dataset_size: 102711988876.0
 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-*
+  - split: train_shard_029
+    path: data/train_shard_029-*
+  - split: train_shard_030
+    path: data/train_shard_030-*
+  - split: train_shard_031
+    path: data/train_shard_031-*
+  - split: train_shard_032
+    path: data/train_shard_032-*
+  - split: train_shard_033
+    path: data/train_shard_033-*
+  - split: train_shard_034
+    path: data/train_shard_034-*
   - split: train_shard_035
     path: data/train_shard_035-*
   - split: train_shard_036
     path: data/train_shard_036-*
-dataset_info:
-  features:
-  - name: image
-    dtype: image
-  - name: text
-    dtype: string
-  splits:
-  - name: train_shard_035
-    num_bytes: 3055357770.0
-    num_examples: 5000
-  - name: train_shard_036
-    num_bytes: 2964727872.0
-    num_examples: 5000
-  download_size: 6020012500
-  dataset_size: 6020085642.0
+  - split: train_shard_037
+    path: data/train_shard_037-*
+  - split: train_shard_038
+    path: data/train_shard_038-*
+  - split: train_shard_039
+    path: data/train_shard_039-*
+  - split: train_shard_040
+    path: data/train_shard_040-*
+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}}
+}
+```