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--- |
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dataset_info: |
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features: |
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- name: File |
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dtype: string |
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- name: Date |
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dtype: int64 |
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- name: OCR_toInput |
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dtype: string |
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- name: OCR_aligned |
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dtype: string |
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- name: GS_aligned |
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dtype: string |
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- name: Ground_truth_aligned |
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dtype: string |
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- name: Ground_truth |
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dtype: string |
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- name: distance |
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dtype: int64 |
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- name: cer |
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dtype: float64 |
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- name: wer |
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dtype: float64 |
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splits: |
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- name: train |
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num_bytes: 11573638 |
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num_examples: 765 |
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- name: dev |
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num_bytes: 1056634 |
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num_examples: 95 |
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- name: test |
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num_bytes: 1782846 |
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num_examples: 97 |
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download_size: 9457542 |
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dataset_size: 14413118 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: dev |
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path: data/dev-* |
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- split: test |
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path: data/test-* |
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task_categories: |
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- image-to-text |
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language: |
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- fr |
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tags: |
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- OCR |
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- NLP |
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- TAL |
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pretty_name: Split ICDAR2017 dataset |
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--- |
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This dataset is a filtered version of the *ICDAR2017* Competition on Handwritten Text Recognition, focusing on monograph texts written between 1800 and 1900. It consists of a total of **957 documents**, divided into training, validation, and testing sets, and is designed for post-correction of OCR (Optical Character Recognition) text. |
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- **Total Documents**: 957 |
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- **Training Set**: 765 |
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- **Validation Set**: 95 |
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- **Test Set**: 97 |
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## Purpose |
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The dataset aims to improve the accuracy of digitized texts by providing a reliable Ground Truth for comparison and correction, specifically addressing the challenges of French text of 19th century. |
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## Structure |
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The dataset is organized as follows: |
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```plaintext |
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dataset/ |
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├── train/ |
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│ ├── file1.txt |
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│ ├── file2.txt |
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│ └── ... |
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├── dev/ |
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│ ├── file1.txt |
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│ ├── file2.txt |
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│ └── ... |
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├── test/ |
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│ ├── file1.txt |
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│ ├── file2.txt |
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│ └── ... |
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└── metadata.csv # This file contains metadata for each txt file |
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``` |
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- **Content** [#.txt] |
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- **1st line**: "[OCR_toInput] " => Raw OCRed text to be denoised. |
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- **2nd line**: "[OCR_aligned] " => Aligned OCRed text. |
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- **3rd line**: "[GS_aligned] " => Aligned Gold Standard. |
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The alignment was made at the character level using "@" symbols. "#" symbols correspond to the absence of GS either related to alignment uncertainities or related to unreadable characters in the source document. |
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For a better view of the alignment, make sure to disable the "word wrap" option in your text editor. |
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## Author Information |
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Prepared by **Mikhail Biriuchinskii**, an engineer in Natural Language Processing at Sorbonne University. |
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## Original Dataset Reference |
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For more information, visit the original dataset source: [ICDAR2017 Competition on Post-OCR Text Correction](http://l3i.univ-larochelle.fr/ICDAR2017PostOCR). |
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## Copyright |
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The original corpus is publicly accessible, and I do not hold any rights to this deployment of the corpus. |
