| --- |
| license: cdla-permissive-1.0 |
| language: |
| - en |
| pretty_name: ADIP-DocLayNet-English |
| size_categories: |
| - 10K<n<100K |
| task_categories: |
| - image-to-text |
| - object-detection |
| tags: |
| - document-layout-analysis |
| - document-parsing |
| - ocr |
| - reading-order |
| - doclaynet |
| - adip |
| dataset_info: |
| features: |
| - name: page_id |
| dtype: string |
| - name: image |
| dtype: image |
| - name: width |
| dtype: int32 |
| - name: height |
| dtype: int32 |
| - name: doc_category |
| dtype: string |
| - name: collection |
| dtype: string |
| - name: original_filename |
| dtype: string |
| - name: page_no |
| dtype: int32 |
| - name: page_hash |
| dtype: string |
| - name: layout_prompt |
| dtype: string |
| - name: layout |
| dtype: string |
| - name: ocr_format |
| dtype: string |
| - name: ocr_prompt |
| dtype: string |
| - name: ocr |
| dtype: string |
| splits: |
| - name: train |
| num_examples: 69076 |
| - name: validation |
| num_examples: 6477 |
| - name: test |
| num_examples: 4991 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-*.parquet |
| - split: validation |
| path: data/validation-*.parquet |
| - split: test |
| path: data/test-*.parquet |
| --- |
| |
| # ADIP-DocLayNet-English |
|
|
| 80,544 English document pages from [DocLayNet v1.2](https://huggingface.co/datasets/docling-project/DocLayNet-v1.2), |
| re-annotated in the **ADIP** (Arabic Document Intelligence Platform) document-parsing format. Each page has two |
| supervised records: |
|
|
| * **ADIP layout parsing**: the page's document metadata, every element as a hierarchy (page → regions → ADIP |
| element kinds) with boxes on a 0–1000 grid, the reading order, and the relations between elements. |
| * **Transcription**: the page text in reading order, either as ADIP element JSON (id, kind, pixel box, text) or as |
| plain text. |
|
|
| The element kinds, categories and document types come from the ADIP-Naqsh taxonomy (162 element kinds in 9 |
| categories). The records use the same fields and value conventions as ADIP's Arabic document annotations, so English |
| and Arabic pages can be mixed in one training set or evaluated with one parser. |
|
|
| | Split | Pages | ADIP layout records | Transcription records (JSON / plain text) | |
| |---|---|---|---| |
| | train | 69,076 | 69,076 | 34,138 / 34,554 | |
| | validation | 6,477 | 6,477 | 3,186 / 3,260 | |
| | test | 4,991 | 4,991 | 2,493 / 2,458 | |
|
|
| The splits are DocLayNet's own. A page whose box has no text (for example, a page that is one picture) has a layout |
| record but no transcription. 41 pages whose layout record exceeded about 12k tokens were left out. |
|
|
| ## Loading |
|
|
| ```python |
| import json |
| from datasets import load_dataset |
| |
| ds = load_dataset("ADIP-QCRI/ADIP-DocLayNet-English", split="validation") |
| row = ds[0] |
| row["image"] # PIL image of the page (JPEG, 1025 x 1025) |
| layout = json.loads(row["layout"]) |
| row["ocr_format"], row["ocr"] # "json" or "text" |
| ``` |
|
|
| ## Columns |
|
|
| | Column | Content | |
| |---|---| |
| | `page_id` | `doclaynet_<first 16 hex digits of the DocLayNet page hash>` | |
| | `image` | the page image, as in DocLayNet (1025 × 1025 px) | |
| | `width`, `height` | image size in pixels | |
| | `doc_category`, `collection`, `original_filename`, `page_no`, `page_hash` | DocLayNet source metadata | |
| | `layout_prompt`, `layout` | the ADIP layout-parsing instruction and its answer (compact JSON string) | |
| | `ocr_format`, `ocr_prompt`, `ocr` | `json` or `text`, the transcription instruction and its answer | |
|
|
| ## The ADIP layout record |
|
|
| ```json |
| { |
| "document": { |
| "type": "financial_report", |
| "script": {"primary": "en", "direction": "ltr", "diacritics": "none", "ligatures": "none", |
| "numerals": "western", "kashida": "none"}, |
| "script_style": "system_serif_latin", "estimated_century": "21st", |
| "paper_color": "white", "ink_color": "black", "readability": 5, "complexity": 3, |
| "page_size_px": [1025, 1025] |
| }, |
| "reading_order": ["elem_0001_01", "elem_0001_02"], |
| "reading_order_elements": ["elem_0001", "elem_0001_01", "elem_0001_01_01", "..."], |
| "elements": [{ |
| "id": "elem_0001", "slot": "page", "kind": "page", "bbox_2d": [0, 0, 1000, 1000], "level": 0, "...": "...", |
| "children": [{ |
| "id": "elem_0001_01", "slot": "main_text_region", "kind": "body", "bbox_2d": [116, 115, 942, 743], |
| "level": 1, "parent": "elem_0001", "script": "en", "direction": "ltr", "layer": 1, |
| "filled": true, "fill_ratio": 0.97, "order": 2, |
| "children": [{ |
| "id": "elem_0001_01_01", "kind": "body_text", "category": "structural_body", |
| "bbox_2d": [147, 88, 837, 118], "level": 2, "parent": "elem_0001_01", |
| "font": "system_serif_latin", "ink": "black", "script": "en", "direction": "ltr", |
| "layer": 2, "lines": 2, "order": 3 |
| }] |
| }] |
| }], |
| "relations": [{"type": "next", "from": "elem_0001_01_01", "to": "elem_0001_01_02"}] |
| } |
| ``` |
|
|
| * **document**: ADIP document type, script profile, script style, estimated century, paper and ink colour, |
| readability (1–5), complexity (1–5) and page size. |
| * **elements**: the page; its regions (`header_region`, `main_text_region`, `footer_region`); and the ADIP elements |
| inside them. Each element has its id, slot or kind, ADIP category, `bbox_2d` = [x0, y0, x1, y1] on a 0–1000 grid of |
| the page, level, parent, font class, ink colour, script, direction, layer, number of text lines and position in |
| the reading order. |
| * **reading_order** lists the region ids in reading order. **reading_order_elements** lists every element id in |
| reading order. |
| * **relations**: `next` between consecutive elements in reading order, and `inside` for an element whose box lies |
| at least 90% inside a larger element of another region. |
| |
| ## The transcription record |
| |
| * `json`: `[{"id", "kind", "bbox": {"x", "y", "w", "h"} in pixels, "text"}, ...]`, one entry per text-bearing |
| element, in reading order. The text comes from the PDF text cells of the element's box, grouped into lines. |
| * `text`: the same text as plain text, one element per paragraph, in reading order. |
| |
| ## DocLayNet classes → ADIP element kinds |
| |
| | DocLayNet | ADIP kind | ADIP category | Region | |
| |---|---|---|---| |
| | Text | body_text | structural_body | main_text_region | |
| | Section-header | heading | structural_body | main_text_region | |
| | List-item | list | structural_body | main_text_region | |
| | Caption | caption | structural_body | main_text_region | |
| | Title | title | metadata | main_text_region | |
| | Table | table | block_assets | main_text_region | |
| | Picture | figure | block_assets | main_text_region | |
| | Formula | math_block | block_assets | main_text_region | |
| | Page-header | header | navigation_reference | header_region | |
| | Page-footer | page_number if the text is a page number, else footer | navigation_reference | footer_region | |
| | Footnote | footnote | navigation_reference | footer_region | |
| |
| DocLayNet document categories map to ADIP document types: financial reports → `financial_report`, manuals → |
| `technical_manual`, scientific articles → `scientific_article`, laws and regulations → `regulation`, patents → |
| `patent`, government tenders → `specification`. |
| |
| Element counts over all splits: body_text 510,377; list 185,660; heading 142,884; header 58,022; figure 45,976; |
| page_number 39,758; table 34,733; footer 31,120; math_block 25,027; caption 22,524; footnote 6,318; title 5,071. |
| |
| ## Derived values |
| |
| Boxes, classes and text are DocLayNet's own annotations. DocLayNet has no reading order and no visual metadata, so |
| these values are derived by fixed rules. Treat them as estimates: |
| |
| * **Reading order**: the header region left to right, then the main region, then the footer region (footnotes |
| first, then page footers). In the main region, a block wider than 60% of the text area is read on its own; the |
| blocks between such blocks are read column by column, with the column taken from the box centre. |
| * **Fonts** (`script_style`, element `font`): `system_serif_latin`, `system_sans_latin` or `system_mono_latin`, |
| from the PDF font names. ADIP's font taxonomy covers Arabic script, and these are the Latin counterparts of its |
| `system_serif_arabic` and `system_sans_arabic` classes. |
| * **Colours**: `paper_color` comes from the page background pixels. `ink_color` and element `ink` come from the |
| colour of the PDF text cells. |
| * **estimated_century**: from a year in the source file name, otherwise `21st`. |
| * **readability** is 5 (born-digital pages). **complexity** (1–5) comes from the number of blocks, the number of |
| columns and the number of tables, figures and formulas. |
| * **Lines**: the number of text lines in the element, from its PDF text cells. |
| |
| ## License and attribution |
| |
| This dataset is a modified version of DocLayNet v1.2 and is distributed under the same license, |
| [CDLA-Permissive-1.0](https://cdla.dev/permissive-1-0/) (full text in `LICENSE`). The page images, boxes, classes, |
| text cells and source metadata are © the DocLayNet authors and data providers. The modifications are the ADIP |
| re-annotation described above. If you use this dataset, please cite DocLayNet: |
| |
| ```bibtex |
| @inproceedings{pfitzmann2022doclaynet, |
| title = {DocLayNet: A Large Human-Annotated Dataset for Document-Layout Segmentation}, |
| author = {Pfitzmann, Birgit and Auer, Christoph and Dolfi, Michele and Nassar, Ahmed S. and Staar, Peter}, |
| booktitle = {Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining}, |
| pages = {3743--3751}, |
| year = {2022}, |
| doi = {10.1145/3534678.3539043} |
| } |
| ``` |
| |
| ## Contact |
| |
| Ehsan Asgari, easgari@hbku.edu.qa |
| |
