Update README.md

Updated the README with all the details

README.md

@@ -3,153 +3,144 @@ license: mit
 task_categories:
 - image-to-text
 language:
+- en
 - hi
 - te
-- en
-- ur
+- ta
 - or
+- ur
 - ml
+- zh
+- pa
+- gu
+- bn
 pretty_name: MUSTARD
 size_categories:
 - 1K<n<10K
+tags:
+- Table
+- TSR
+- Table Structure
+- Table Recognition
 ---
-# Dataset Card for Dataset Name
-
-<!-- Provide a quick summary of the dataset. -->
-
-This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
+# Dataset Card for MUSTARD
 
 ## Dataset Details
 
 ### Dataset Description
 
-<!-- Provide a longer summary of what this dataset is. -->
-
-
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/613ed32082b4af22cbd7fdca/yXvn-AdHkVag1JHYXgPXJ.png)
+MUSTARD (Multilingual Scanned and Scene Table Structure Recognition Dataset) is a diverse dataset curated for table structure recognition across multiple languages. The dataset consists of tables extracted from magazines, including printed, scanned, and scene-text tables, labeled with Optimized Table Structure Language (OTSL) sequences. It is designed to facilitate research in multilingual table structure recognition, particularly for non-English documents.
 
+![Sample MUSTARD images](./resources/mustard_samples.png)
 
+- **Curated by:** IIT Bombay LEAP OCR Team
+- **Funded by:** IRCC, IIT Bombay, and MEITY, Government of India
+- **Shared by:** IIT Bombay LEAP OCR Team
+- **Language(s) (NLP):** Hindi, Telugu, English, Urdu, Oriya, Malayalam, Assamese, Bengali, Gujarati, Kannada, Punjabi, Tamil, Chinese
+- **License:** MIT
 
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
+### Dataset Sources
 
-### Dataset Sources [optional]
-
-<!-- Provide the basic links for the dataset. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** [GitHub Repository](https://github.com/IITB-LEAP-OCR/SPRINT)
+- **Paper:** [SPRINT: Script-agnostic Structure Recognition in Tables (ICDAR 2024)](https://arxiv.org/abs/2503.11932)
+- **Dataset Download:** [Hugging Face Link](https://huggingface.co/datasets/badrivishalk/MUSTARD)
 
 ## Uses
 
-<!-- Address questions around how the dataset is intended to be used. -->
-
 ### Direct Use
 
-<!-- This section describes suitable use cases for the dataset. -->
-
-[More Information Needed]
+MUSTARD is primarily intended for training and evaluating table structure recognition models, especially those dealing with multilingual and script-agnostic document analysis.
 
 ### Out-of-Scope Use
 
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-
-[More Information Needed]
+The dataset should not be used for tasks unrelated to table structure recognition. Additionally, any application involving sensitive data extraction should ensure compliance with relevant legal and ethical guidelines.
 
 ## Dataset Structure
 
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
-
-[More Information Needed]
+The dataset consists of:
+- **1428 tables** across 13 languages.
+- Labels provided in **OTSL format**.
+- A mixture of **printed, scanned, and scene-text tables**.
 
 ## Dataset Creation
 
 ### Curation Rationale
 
-<!-- Motivation for the creation of this dataset. -->
-
-[More Information Needed]
+The dataset was created to address the lack of multilingual table structure recognition resources, enabling research beyond English-centric datasets.
 
 ### Source Data
 
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-
 #### Data Collection and Processing
 
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-
-[More Information Needed]
+- Tables were sourced from various magazines.
+- Labeled using **OTSL sequences** to provide a script-agnostic representation.
+- Ground truth annotations were validated for accuracy.
 
 #### Who are the source data producers?
 
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-
-[More Information Needed]
-
-### Annotations [optional]
+The dataset was curated by researchers at IIT Bombay, specializing in OCR and document analysis.
 
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
+### Annotations
 
-#### Annotation process
+#### Annotation Process
 
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-
-[More Information Needed]
+- Tables were manually labeled using **OTSL sequences**.
+- Verification was performed to ensure consistency.
+- Annotations were aligned with **HTML-based table representations** for interoperability.
 
 #### Who are the annotators?
 
-<!-- This section describes the people or systems who created the annotations. -->
-
-[More Information Needed]
+Annotations were performed by research scholars and experts in OCR and document processing at IIT Bombay.
 
 #### Personal and Sensitive Information
 
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-
-[More Information Needed]
+The dataset does not contain personally identifiable or sensitive information.
 
 ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
+- **Bias:** The dataset is derived primarily from magazines, which may not fully represent all document styles.
+- **Limitations:** The dataset size is limited (1428 tables), and performance may vary on unseen data sources.
+- **Risks:** Use in sensitive domains should be accompanied by proper validation and legal compliance.
 
 ### Recommendations
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+Users should be aware of dataset limitations and biases when applying models trained on MUSTARD to other real-world scenarios.
 
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
+## Citation
 
-## Citation [optional]
+If you use this dataset in your research, please cite it as:
 
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+```
+@InProceedings{10.1007/978-3-031-70549-6_21,
+author="Kudale, Dhruv and Kasuba, Badri Vishal and Subramanian, Venkatapathy and Chaudhuri, Parag and Ramakrishnan, Ganesh",
+editor="Barney Smith, Elisa H. and Liwicki, Marcus and Peng, Liangrui",
+title="SPRINT: Script-agnostic Structure Recognition in Tables",
+booktitle="Document Analysis and Recognition - ICDAR 2024",
+year="2024",
+publisher="Springer Nature Switzerland",
+address="Cham",
+pages="350--367",
+isbn="978-3-031-70549-6",
+url = "https://arxiv.org/abs/2503.11932"
+}
+```
 
-**BibTeX:**
+## More Information
 
-[More Information Needed]
+For further details, refer to:
+- **SPRINT Model:** [GitHub Repository](https://github.com/IITB-LEAP-OCR/SPRINT)
+- **Pretrained Models:** [Model Releases](https://github.com/IITB-LEAP-OCR/SPRINT/releases/tag/models)
+- **Dataset Download:** [Hugging Face Dataset](https://huggingface.co/datasets/badrivishalk/MUSTARD)
 
-**APA:**
+## Dataset Card Authors
 
-[More Information Needed]
+- Badri Vishal Kasuba
+- Dhruv Kudale
 
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Dataset Card Authors [optional]
+## Dataset Card Contact
 
-[More Information Needed]
+For queries, contact the authors via their respective institutional affiliations.
 
-## Dataset Card Contact
+## License
 
-[More Information Needed]
+The dataset is licensed under the **MIT License**, allowing for free use and modification with proper attribution.