Datasets:

openpecha
/

OCR-Google_Books

dataset_info:
  features:
    - name: filename
      dtype: string
    - name: label
      dtype: string
    - name: url
      dtype: string
    - name: BDRC_work_id
      dtype: string
    - name: char_len
      dtype: int64
    - name: script
      dtype: string
    - name: print_method
      dtype: string
  splits:
    - name: train
      num_bytes: 210467728
      num_examples: 601152
    - name: eval
      num_bytes: 26280512
      num_examples: 75136
    - name: test
      num_bytes: 26308535
      num_examples: 75168
  download_size: 76386563
  dataset_size: 263056775
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: eval
        path: data/eval-*
      - split: test
        path: data/test-*

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
- url: Source URL of the original document
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
May not suitably represent contemporary digital Tibetan fonts

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་',
# 'url': 'https://s3.amazonaws.com/monlam.ai.ocr/OCR/training_images/I1KG1163750042_0025.jpg'}

Dataset Contact

BDRC - help@bdrc.org