Improve dataset card: Add paper link, task categories, correct size, and sample usage

This PR enhances the dataset card for `SciPostLayoutTree` by:
- Linking the dataset to its corresponding paper: https://huggingface.co/papers/2511.18329
- Expanding the dataset description based on the paper abstract.
- Correcting the `size_categories` metadata to `1K<n<10K` to accurately reflect the dataset size of approximately 8,000 posters.
- Adding `task_categories: ['OTHER']` and relevant `tags` (`scientific-posters`, `layout-analysis`, `document-structure-analysis`) for better discoverability.
- Explicitly linking to the GitHub repository.
- Including a "Sample Usage" section with a code snippet for visualizing annotations, directly extracted from the GitHub README, to help users quickly get started.

README.md

@@ -1,10 +1,40 @@
----
-license: cc
-language:
-- en
-size_categories:
-- 10K<n<100K
----
-
-This is the dataset repository of a paper ''SciPostLayoutTree: A Dataset for Structural Analysis of Scientific Posters''.
-For dataset usage and reproduction steps, please refer to the instructions provided in the following repository: https://github.com/omron-sinicx/scipostlayouttree
+---
+language:
+- en
+license: cc
+size_categories:
+- 1K<n<10K
+task_categories:
+- OTHER
+tags:
+- scientific-posters
+- layout-analysis
+- document-structure-analysis
+---
+
+# SciPostLayoutTree: A Dataset for Structural Analysis of Scientific Posters
+
+This repository contains the SciPostLayoutTree dataset, introduced in the paper "[SciPostLayoutTree: A Dataset for Structural Analysis of Scientific Posters](https://huggingface.co/papers/2511.18329)".
+
+SciPostLayoutTree is a dataset of approximately 8,000 scientific posters annotated with reading order and parent-child relations. It is designed to facilitate research into structural analysis of scientific posters, which play a vital role in academic communication. The dataset specifically addresses challenges related to spatially complex relations, including upward, horizontal, and long-distance relationships, making it a valuable resource for building structure-aware interfaces.
+
+- **Paper**: [SciPostLayoutTree: A Dataset for Structural Analysis of Scientific Posters](https://huggingface.co/papers/2511.18329)
+- **Code/GitHub Repository**: [https://github.com/omron-sinicx/scipostlayouttree](https://github.com/omron-sinicx/scipostlayouttree)
+
+For detailed dataset construction, experimental setup, and reproduction steps, please refer to the comprehensive instructions provided in the [GitHub repository](https://github.com/omron-sinicx/scipostlayouttree).
+
+### Sample Usage
+
+You can visualize tree annotations using the script provided in the associated GitHub repository. First, install the necessary Python packages:
+
+```bash
+pip install opencv-python numpy matplotlib tqdm
+```
+
+Then, execute the visualization script:
+
+```bash
+python visualize_annotation.py
+```
+
+Please ensure you have completed the [Dataset Construction steps](https://github.com/omron-sinicx/scipostlayouttree#dataset-construction) outlined in the GitHub repository to prepare the data and annotation files before running the visualization.