README.md

metadata

dataset_info:
  - config_name: default
    features:
      - name: id
        dtype: string
      - name: label
        dtype: string
      - name: image
        dtype: image
    splits:
      - name: train
        num_bytes: 12241195541
        num_examples: 601152
      - name: eval
        num_bytes: 1529748306
        num_examples: 75136
      - name: test
        num_bytes: 1533972964
        num_examples: 75168
    download_size: 15095694848
    dataset_size: 15304916811
  - config_name: updated_schema
    features:
      - name: id
        dtype: string
      - name: label
        dtype: string
      - name: url
        dtype: string
    splits:
      - name: train
        num_bytes: 176527069
        num_examples: 601152
    download_size: 55583886
    dataset_size: 176527069
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: eval
        path: data/eval-*
      - split: test
        path: data/test-*
  - config_name: updated_schema
    data_files:
      - split: train
        path: updated_schema/train-*
license: odc-by
task_categories:
  - image-to-text
language:
  - bo
tags:
  - OCR
  - Tibetan
  - Line-to-text
size_categories:
  - 100K<n<1M

Dataset Card for OCR-Google_Books

A line-to-text dataset for Tibetan OCR.

Dataset Details

Dataset Description

• Curated by: Buddhist Digital Resource Center
• Language: Tibetan
• Total Samples: 751,456 line images with text transcriptions

Dataset Structure

• Features:

  • id: Image file identifier
  • label: Text transcription
  • image: Image of a line of Tibetan text

• Splits:

  • Train: 601,152 samples (37.3M characters)
  • Eval: 75,136 samples (4.7M characters)
  • Test: 75,168 samples (4.7M characters)

Uses

Direct Use

• Training and evaluation of Tibetan OCR models
• Multi-script OCR development
• Comparative analysis of modern vs. traditional printing methods
• Large-scale OCR model pretraining

Out-of-Scope Use

• Not be suitable for handwritten Tibetan texts

Dataset Creation

Curation Rationale and Process

This dataset was created to support the development of robust OCR systems for Tibetan literature, encompassing both modern typography and traditional woodblock printing methods. The inclusion of multiple scripts and printing techniques makes it valuable for training models that can handle diverse Tibetan textual sources.

The dataset is constructed from Google Books scans of Tibetan texts, with Line-level image-text pairs extracted from scanned pages

Usage

from datasets import load_dataset

# Load training split
dataset = load_dataset("openpecha/OCR-Google_Books", split="train")

# Example features
print(dataset[0])
# {'id': 'I1KG1163750042_0025',
#'label':'ཡིན་པས་ཆབ་སྲིད་དང་འབྲེལ་བ་བྱུང་བ་ཙམ་ལ་ངོ་མཚར་དགོས་དོན་གང་',
#'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=860x45>}

Dataset Contact

BDRC - help@bdrc.org