README.md

metadata

license: mit
task_categories:
  - image-to-text
language:
  - en
tags:
  - ocr
  - icdar
  - icdar2013
pretty_name: ICDAR 2013
dataset_info:
  features:
    - name: image
      dtype: image
    - name: text
      dtype: string
  splits:
    - name: train
      num_bytes: 56543493
      num_examples: 848
    - name: train_numbers
      num_bytes: 2042222
      num_examples: 33
    - name: test
      num_bytes: 51675533.125
      num_examples: 1015
    - name: test_numbers
      num_bytes: 1513622
      num_examples: 71
  download_size: 111842710
  dataset_size: 111774870.125
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: train_numbers
        path: data/train_numbers-*
      - split: test
        path: data/test-*
      - split: test_numbers
        path: data/test_numbers-*

META

https://github.com/open-mmlab/mmocr/blob/main/dataset_zoo/icdar2013/metafile.yml

Name: 'Incidental Scene Text IC13'
Paper:
  Title: ICDAR 2013 Robust Reading Competition
  URL: https://www.imlab.jp/publication_data/1352/icdar_competition_report.pdf
  Venue: ICDAR
  Year: '2013'
  BibTeX: '@inproceedings{karatzas2013icdar,
  title={ICDAR 2013 robust reading competition},
  author={Karatzas, Dimosthenis and Shafait, Faisal and Uchida, Seiichi and Iwamura, Masakazu and i Bigorda, Lluis Gomez and Mestre, Sergi Robles and Mas, Joan and Mota, David Fernandez and Almazan, Jon Almazan and De Las Heras, Lluis Pere},
  booktitle={2013 12th international conference on document analysis and recognition},
  pages={1484--1493},
  year={2013},
  organization={IEEE}}'
Data:
  Website: https://rrc.cvc.uab.es/?ch=2
  Language:
    - English
  Scene:
    - Natural Scene
  Granularity:
    - Word
  Tasks:
    - textdet
    - textrecog
    - textspotting
  License:
    Type: N/A
    Link: N/A
  Format: .txt