Datasets:
pierreguillou
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Update README.md
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README.md
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annotations_creators:
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- crowdsourced
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license: other
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pretty_name: DocLayNet
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size_categories:
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- 0K<n<1K
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tags:
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@@ -50,14 +50,36 @@ For all these reasons, I decided to process the DocLayNet dataset:
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- into 3 datasets of different sizes:
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- [DocLayNet small](https://huggingface.co/datasets/pierreguillou/DocLayNet-small) < 1.000k document images
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- [DocLayNet base](https://huggingface.co/datasets/pierreguillou/DocLayNet-base) < 10.000k document images- with associated texts,
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- and in a format facilitating their use by HF notebooks.
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*Note: the layout HF notebooks will greatly help participants of the IBM [ICDAR 2023 Competition on Robust Layout Segmentation in Corporate Documents](https://ds4sd.github.io/icdar23-doclaynet/)!*
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### Download
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```
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```
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### HF notebooks
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annotations_creators:
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- crowdsourced
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license: other
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pretty_name: DocLayNet small
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size_categories:
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- 0K<n<1K
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tags:
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- into 3 datasets of different sizes:
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- [DocLayNet small](https://huggingface.co/datasets/pierreguillou/DocLayNet-small) < 1.000k document images
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- [DocLayNet base](https://huggingface.co/datasets/pierreguillou/DocLayNet-base) < 10.000k document images- with associated texts,
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- DocLayNet large with full dataset (to be done)
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- and in a format facilitating their use by HF notebooks.
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*Note: the layout HF notebooks will greatly help participants of the IBM [ICDAR 2023 Competition on Robust Layout Segmentation in Corporate Documents](https://ds4sd.github.io/icdar23-doclaynet/)!*
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### Download & overview
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```
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# !pip install -q datasets
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from datasets import load_dataset
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dataset_small = load_dataset("pierreguillou/DocLayNet-small")
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# overview of dataset_small
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DatasetDict({
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train: Dataset({
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features: ['id', 'texts', 'bboxes_block', 'bboxes_line', 'categories', 'image', 'pdf', 'page_hash', 'original_filename', 'page_no', 'num_pages', 'original_width', 'original_height', 'coco_width', 'coco_height', 'collection', 'doc_category'],
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num_rows: 691
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})
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validation: Dataset({
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features: ['id', 'texts', 'bboxes_block', 'bboxes_line', 'categories', 'image', 'pdf', 'page_hash', 'original_filename', 'page_no', 'num_pages', 'original_width', 'original_height', 'coco_width', 'coco_height', 'collection', 'doc_category'],
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num_rows: 64
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})
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test: Dataset({
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features: ['id', 'texts', 'bboxes_block', 'bboxes_line', 'categories', 'image', 'pdf', 'page_hash', 'original_filename', 'page_no', 'num_pages', 'original_width', 'original_height', 'coco_width', 'coco_height', 'collection', 'doc_category'],
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num_rows: 49
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})
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})
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```
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### HF notebooks
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