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metadata
license: apache-2.0
task_categories:
  - text-to-image
  - image-to-text
language:
  - th
tags:
  - handwriting-recognition
  - ocr
pretty_name: Thai Handwriting Dataset
size_categories:
  - 10K<n<100K
maintainer: Kobkrit Viriyayudhakorn (kobkrit@iapp.co.th)
dataset_info:
  features:
    - name: image
      dtype: image
    - name: text
      dtype: string
    - name: label_file
      dtype: string

Thai Handwriting Dataset

This dataset combines two major Thai handwriting datasets:

  1. BEST 2019 Thai Handwriting Recognition dataset (train-0000.parquet)
  2. Thai Handwritten Free Dataset by Wang (train-0001.parquet onwards)

Maintainer

kobkrit@iapp.co.th

Dataset Description

BEST 2019 Dataset

Contains handwritten Thai text images along with their ground truth transcriptions. The images have been processed and standardized for machine learning tasks.

Wang Dataset

  • Exclusively focuses on handwritten sentences in Thai language
  • Contains 4,920 unique sentences covering various topics and themes
  • Created from contributions by 2,026 users, ensuring diverse handwriting styles
  • Encompasses various linguistic patterns, vocabulary, and sentence structures

Dataset Structure

The dataset is provided in parquet file format with the following columns:

  • image: Image data (Image type)
  • text: Ground truth transcription of the handwritten text (String)
  • label_file: Source label file name (String)

Usage

This dataset is ideal for:

  • Handwriting recognition
  • Optical character recognition (OCR)
  • Natural language processing (NLP)
  • Language generation

Researchers, developers, and enthusiasts can utilize this dataset to:

  • Develop and benchmark algorithms
  • Train machine learning models
  • Explore innovative techniques in Thai language analysis and handwriting recognition

Original Datasets

  1. BEST 2019 Thai Handwriting Recognition competition: https://thailang.nectec.or.th/best/best2019-handwrittenrecognition-trainingset/

  2. Thai Handwritten Free Dataset by Wang: Data Market https://www.wang.in.th/dataset/64abb3e951752d79380663c2