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metadata 
dataset_info:
  - config_name: cleaned
    features:
      - name: image
        dtype: image
      - name: text
        dtype: string
    splits:
      - name: train
        num_bytes: 287421496
        num_examples: 9065
    download_size: 304293885
    dataset_size: 287421496
  - config_name: uncleaned
    features:
      - name: image
        dtype: image
      - name: text
        dtype: string
    splits:
      - name: train
        num_bytes: 2465051123
        num_examples: 162863
    download_size: 2380627327
    dataset_size: 2465051123
configs:
  - config_name: cleaned
    data_files:
      - split: train
        path: cleaned/train-*
  - config_name: uncleaned
    data_files:
      - split: train
        path: uncleaned/train-*

Please visit the GitHub repository for other Myanmar Language datasets.

Burmese OCR Dataset (Hugging Face Format)

This is a reformatted version of alexbeatson/burmese_ocr_data converted into the native Hugging Face datasets format for easier loading and integration with modern OCR training pipelines.

Dataset Description

This dataset contains Burmese text images and their corresponding ground truth text extracted from real-life documents, suitable for training Optical Character Recognition (OCR) models.

Source

The original data was curated from the Burma Library archive, which collects and preserves government and NGO documents. Documents were processed using Google Document AI to extract text and bounding boxes, then cropped into single-line text images.

Dataset Structure

The dataset consists of two subsets:

Subset Samples Description
cleaned 9,065 Manually validated by two individuals. Some errors may still be present.
uncleaned 162,863 Raw images from Google Document AI output, without manual review.

Features

  • image: Single-line text image in PNG format (RGB)
  • text: Corresponding ground truth text

Usage 

from datasets import load_dataset

# Load the cleaned subset
cleaned = load_dataset("chuuhtetnaing/burmese_ocr_dataset_hf", "cleaned")

# Load the uncleaned subset
uncleaned = load_dataset("chuuhtetnaing/burmese_ocr_dataset_hf", "uncleaned")

# Load both subsets
dataset = load_dataset("chuuhtetnaing/burmese_ocr_dataset_hf")

# Access samples
sample = cleaned["train"][0]
print(sample["text"])
sample["image"].show()

Citation

If you use this dataset, please cite the original source:

@misc {alexanderbeatson,
    author       = { {Alexander Beatson} },
    title        = { Burmese OCR data },
    year         = 2024,
    url          = { https://huggingface.co/datasets/alexbeatson/burmese_ocr_data },
    doi          = { 10.57967/hf/3361 },
    publisher    = { Hugging Face },
    note     = {ORCID: 0000-0002-1829-5965} 
}

Acknowledgments