Update README.md

README.md

@@ -9,13 +9,13 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 28126563.0
+    num_bytes: 28126563
     num_examples: 149
   - name: test
-    num_bytes: 10195323.0
+    num_bytes: 10195323
     num_examples: 50
   download_size: 36491665
-  dataset_size: 38321886.0
+  dataset_size: 38321886
 configs:
 - config_name: default
   data_files:
@@ -23,4 +23,120 @@ configs:
     path: data/train-*
   - split: test
     path: data/test-*
+license: mit
+task_categories:
+- question-answering
+language:
+- en
+size_categories:
+- n<1K
 ---
+
+# Dataset Card for FUNSD (JSON Format)
+
+This dataset contains the preprocessed **JSON format** of the [FUNSD dataset](https://guillaumejaume.github.io/FUNSD/), designed for **form understanding in noisy scanned documents**. It includes the original structure with annotations in JSON format, as per the original FUNSD dataset. This dataset is intended for document understanding tasks such as OCR, layout parsing, and key-value extraction.
+
+## Dataset Details
+
+### Dataset Description
+
+The **FUNSD (Form Understanding in Noisy Scanned Documents)** dataset is a collection of noisy scanned document images, designed for **OCR and form recognition tasks**. This version contains the **original JSON annotations** for training and testing models in form understanding tasks.
+
+- **Curated by:** [David (Tan) LE](https://github.com/tanle8)
+- **Language(s):** English (labels, tags)
+- **License:** Apache License 2.0 (from the original FUNSD dataset)
+
+### Dataset Sources
+
+- **Repository:** [Original FUNSD Dataset Repository](https://guillaumejaume.github.io/FUNSD/)
+- **Paper:** [Jaume et al., 2019](https://ieeexplore.ieee.org/document/8978100)
+
+---
+
+## Uses
+
+### Direct Use
+
+This dataset can be used for:
+- Fine-tuning **document understanding models** such as Donut, LayoutLM, and other OCR-based models.
+- Training and evaluating models for **form extraction** (questions, answers, headers).
+- Research in **key-value extraction and layout parsing**.
+
+---
+
+## Dataset Structure
+
+- **id:** Unique identifier for each document.
+- **image:** The document image (RGB format).
+- **text_output:** JSON annotations containing:
+  - `"form"`: A list of labeled fields (e.g., "question", "answer", "header").
+  - `"words"`: Word-level annotations with bounding boxes.
+  - `"linking"`: Relationships (e.g., links between "question" and "answer").
+
+### Splits
+- **Train:** 149 examples
+- **Test:** 50 examples
+
+---
+
+## Dataset Creation
+
+### Curation Rationale
+
+This version retains the original JSON format of the FUNSD dataset, making it easy to use for models designed for form understanding tasks without the need to convert to XML or TEI formats.
+
+### Source Data
+
+The dataset is sourced from the original **FUNSD** repository:
+- **Images:** Scanned document images.
+- **Annotations:** Original annotations in JSON format.
+
+#### Data Collection and Processing
+
+The dataset was not altered apart from formatting to maintain compatibility with the Hugging Face `datasets` library.
+
+---
+
+## Annotations
+
+### Annotation Process
+The annotations in JSON format contain:
+- **Bounding boxes** for each form element.
+- **Labels** for "question", "answer", "header", and "other".
+- **Linking information** to capture relationships between form elements.
+
+---
+
+## Bias, Risks, and Limitations
+
+### Risks and Limitations
+- The dataset contains noisy, real-world scanned documents that may not generalize to synthetic or clean data.
+- Some form layouts may not follow typical Western document standards, which could bias model training.
+
+---
+
+## Citation
+
+If you use this dataset, please cite the original paper:
+
+**BibTeX:**
+```bibtex
+@article{Jaume2019FUNSDAD,
+  title={FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents},
+  author={Guillaume Jaume and H. K. Ekenel and J. Thiran},
+  journal={2019 International Conference on Document Analysis and Recognition Workshops (ICDARW)},
+  year={2019},
+  volume={2},
+  pages={1-6}
+}
+```
+
+APA: Jaume, G., Ekenel, H. K., & Thiran, J. (2019). FUNSD: A dataset for form understanding in noisy scanned documents. 2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), 1–6.
+
+## Dataset Card Authors
+David (Tan) LE - [GitHub Profile](https://github.com/tanle8)
+
+## Dataset Card Contact
+For any issues or questions about this dataset, contact me through the HuggingFace message system.
+
+