Update README.md

README.md

@@ -1,73 +1,153 @@
 ---
-dataset_info:
-  features:
-  - name: image
-    dtype: image
-  - name: bbox
-    sequence:
-      sequence: float64
-  - name: category_id
-    sequence: int64
-  - name: segmentation
-    sequence:
-      sequence:
-        sequence: float64
-  - name: area
-    sequence: float64
-  - name: iscrowd
-    sequence: int64
-  - name: pdf_cells
-    list:
-      list:
-      - name: bbox
-        sequence: float64
-      - name: font
-        struct:
-        - name: color
-          sequence: int64
-        - name: name
-          dtype: string
-        - name: size
-          dtype: float64
-      - name: text
-        dtype: string
-  - name: metadata
-    struct:
-    - name: coco_height
-      dtype: int64
-    - name: coco_width
-      dtype: int64
-    - name: collection
-      dtype: string
-    - name: doc_category
-      dtype: string
-    - name: image_id
-      dtype: int64
-    - name: num_pages
-      dtype: int64
-    - name: original_filename
-      dtype: string
-    - name: original_height
-      dtype: float64
-    - name: original_width
-      dtype: float64
-    - name: page_hash
-      dtype: string
-    - name: page_no
-      dtype: int64
-  splits:
-  - name: test
-    num_bytes: 1996722627.125
-    num_examples: 4999
-  - name: val
-    num_bytes: 2494706174.875
-    num_examples: 6489
-  - name: train
-    num_bytes: 28179797029.125
-    num_examples: 69375
-  download_size: 31783096529
-  dataset_size: 32671225831.125
+annotations_creators:
+- crowdsourced
+license: other
+pretty_name: DocLayNet
+size_categories:
+- 10K<n<100K
+tags:
+- layout-segmentation
+- COCO
+- document-understanding
+- PDF
+task_categories:
+- object-detection
+- image-segmentation
+task_ids:
+- instance-segmentation
 ---
-# Dataset Card for "DocLayNet-v1.1"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+# Dataset Card for DocLayNet v1.1
+
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+- [Dataset Structure](#dataset-structure)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Annotations](#annotations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** https://developer.ibm.com/exchanges/data/all/doclaynet/
+- **Repository:** https://github.com/DS4SD/DocLayNet
+- **Paper:** https://doi.org/10.1145/3534678.3539043
+
+### Dataset Summary
+
+DocLayNet provides page-by-page layout segmentation ground-truth using bounding-boxes for 11 distinct class labels on 80863 unique pages from 6 document categories. It provides several unique features compared to related work such as PubLayNet or DocBank:
+
+1. *Human Annotation*: DocLayNet is hand-annotated by well-trained experts, providing a gold-standard in layout segmentation through human recognition and interpretation of each page layout
+2. *Large layout variability*: DocLayNet includes diverse and complex layouts from a large variety of public sources in Finance, Science, Patents, Tenders, Law texts and Manuals
+3. *Detailed label set*: DocLayNet defines 11 class labels to distinguish layout features in high detail.
+4. *Redundant annotations*: A fraction of the pages in DocLayNet are double- or triple-annotated, allowing to estimate annotation uncertainty and an upper-bound of achievable prediction accuracy with ML models
+5. *Pre-defined train- test- and validation-sets*: DocLayNet provides fixed sets for each to ensure proportional representation of the class-labels and avoid leakage of unique layout styles across the sets.
+
+
+## Dataset Structure
+
+This dataset is structured differently from the other repository [ds4sd/DocLayNet](https://huggingface.co/datasets/ds4sd/DocLayNet), as this one includes the content (PDF cells) of the detections, and abandons the COCO format.
+
+* `image`: page PIL image.
+* `bboxes`: a list of layout bounding boxes.
+* `category_id`: a list of class ids corresponding to the bounding boxes.
+* `segmentation`: a list of layout segmentation polygons.
+* `pdf_cells`: a list of lists corresponding to `bbox`. Each list contains the PDF cells (content) inside the bbox.
+* `metadata`: page and document metadetails.
+
+Bounding boxes classes / categories:
+
+```
+1: Caption
+2: Footnote
+3: Formula
+4: List-item
+5: Page-footer
+6: Page-header
+7: Picture
+8: Section-header
+9: Table
+10: Text
+11: Title
+```
+
+
+The `["metadata"]["doc_category"]` field uses one of the following constants:
+
+```
+* financial_reports,
+* scientific_articles,
+* laws_and_regulations,
+* government_tenders,
+* manuals,
+* patents
+```
+
+
+### Data Splits
+
+The dataset provides three splits
+- `train`
+- `val`
+- `test`
+
+## Dataset Creation
+
+### Annotations
+
+#### Annotation process
+
+The labeling guideline used for training of the annotation experts are available at [DocLayNet_Labeling_Guide_Public.pdf](https://raw.githubusercontent.com/DS4SD/DocLayNet/main/assets/DocLayNet_Labeling_Guide_Public.pdf).
+
+
+#### Who are the annotators?
+
+Annotations are crowdsourced.
+
+
+## Additional Information
+
+### Dataset Curators
+
+The dataset is curated by the [Deep Search team](https://ds4sd.github.io/) at IBM Research.
+You can contact us at [deepsearch-core@zurich.ibm.com](mailto:deepsearch-core@zurich.ibm.com).
+
+Curators:
+- Christoph Auer, [@cau-git](https://github.com/cau-git)
+- Michele Dolfi, [@dolfim-ibm](https://github.com/dolfim-ibm)
+- Ahmed Nassar, [@nassarofficial](https://github.com/nassarofficial)
+- Peter Staar, [@PeterStaar-IBM](https://github.com/PeterStaar-IBM)
+
+### Licensing Information
+
+License: [CDLA-Permissive-1.0](https://cdla.io/permissive-1-0/)
+
+
+### Citation Information
+
+
+```bib
+@article{doclaynet2022,
+  title = {DocLayNet: A Large Human-Annotated Dataset for Document-Layout Segmentation},
+  doi = {10.1145/3534678.353904},
+  url = {https://doi.org/10.1145/3534678.3539043},
+  author = {Pfitzmann, Birgit and Auer, Christoph and Dolfi, Michele and Nassar, Ahmed S and Staar, Peter W J},
+  year = {2022},
+  isbn = {9781450393850},
+  publisher = {Association for Computing Machinery},
+  address = {New York, NY, USA},
+  booktitle = {Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
+  pages = {3743–3751},
+  numpages = {9},
+  location = {Washington DC, USA},
+  series = {KDD '22}
+}
+```