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metadata
dataset_info:
  - config_name: assamese
    features:
      - name: id
        dtype: string
      - name: image
        dtype: image
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      - name: image
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      - name: image
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      - name: image
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      - name: image
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  - config_name: punjabi
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  - config_name: tamil
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      - name: id
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      - name: image
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  - config_name: telugu
    features:
      - name: id
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      - name: image
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      - name: text
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  - config_name: urdu
    features:
      - name: id
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      - name: image
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configs:
  - config_name: assamese
    data_files:
      - split: train
        path: assamese/train-*
      - split: validation
        path: assamese/validation-*
      - split: test
        path: assamese/test-*
  - config_name: bengali
    data_files:
      - split: train
        path: bengali/train-*
      - split: validation
        path: bengali/validation-*
      - split: test
        path: bengali/test-*
  - config_name: gujarati
    data_files:
      - split: train
        path: gujarati/train-*
      - split: validation
        path: gujarati/validation-*
      - split: test
        path: gujarati/test-*
  - config_name: hindi
    data_files:
      - split: train
        path: hindi/train-*
      - split: validation
        path: hindi/validation-*
      - split: test
        path: hindi/test-*
  - config_name: kannada
    data_files:
      - split: train
        path: kannada/train-*
      - split: validation
        path: kannada/validation-*
      - split: test
        path: kannada/test-*
  - config_name: malayalam
    data_files:
      - split: train
        path: malayalam/train-*
      - split: validation
        path: malayalam/validation-*
      - split: test
        path: malayalam/test-*
  - config_name: marathi
    data_files:
      - split: train
        path: marathi/train-*
      - split: validation
        path: marathi/validation-*
      - split: test
        path: marathi/test-*
  - config_name: odia
    data_files:
      - split: train
        path: odia/train-*
      - split: validation
        path: odia/validation-*
      - split: test
        path: odia/test-*
  - config_name: punjabi
    data_files:
      - split: train
        path: punjabi/train-*
      - split: validation
        path: punjabi/validation-*
      - split: test
        path: punjabi/test-*
  - config_name: tamil
    data_files:
      - split: train
        path: tamil/train-*
      - split: validation
        path: tamil/validation-*
      - split: test
        path: tamil/test-*
  - config_name: telugu
    data_files:
      - split: train
        path: telugu/train-*
      - split: validation
        path: telugu/validation-*
      - split: test
        path: telugu/test-*
  - config_name: urdu
    data_files:
      - split: train
        path: urdu/train-*
      - split: validation
        path: urdu/validation-*
      - split: test
        path: urdu/test-*
language:
  - as
  - hi
  - gu
  - ta
  - te
  - bn
  - ur
  - mr
  - kn
  - ml
  - pa
tags:
  - ocr

IndicSTR12 (Full Images)

This document describes the full-image portion of the IndicSTR12 real dataset.

Source

This dataset was downloaded from the CVIT IndicSTR12 Project.

Paper: IndicSTR12: A Dataset for Indic Scene Text Recognition
Authors: Harsh Lunia, Ajoy Mondal, C V Jawahar
Conference: ICDAR 2023

Note: This repository contains only the Real Dataset. The Synthetic Dataset is not included.

Structure

raw_data/
├── assamese/
│   ├── [image_id].jpeg
│   └── [image_id]_gt.txt
├── bengali/
├── gujarati/
├── hindi/
├── kannada/
├── malayalam/
├── marathi/
├── odia/
├── punjabi/
├── tamil/
├── telugu/
└── urdu/

Ground Truth (_gt.txt)

Each line is tab-separated:

word_id    x1  y1  x2  y2  x3  y3  x4  y4    text
  • (x1,y1)...(x4,y4) are the four polygon corners of the word box in the image.
  • text is the Unicode transcription for that word.

Bounding Boxes (Polygon)

In the converted dataset, bboxes are stored as the original polygon:

[x1, y1, x2, y2, x3, y3, x4, y4]

Citation

If you use this dataset in your research, please cite:

@inproceedings{lunia2023indicstr12,
  title={IndicSTR12: A Dataset for Indic Scene Text Recognition},
  author={Lunia, Harsh and Mondal, Ajoy and Jawahar, CV},
  booktitle={International Conference on Document Analysis and Recognition},
  pages={233--250},
  year={2023},
  organization={Springer}
}

Acknowledgements

This work is supported by MeitY, Government of India, through the NLTM-Bhashini project.

License

Please refer to the original dataset source for licensing information.