Update README.md

README.md

@@ -1,5 +1,5 @@
 ---
-license: cc-by-nc-4.0
+license: cc-by-nc-sa-4.0
 pretty_name: Urban-ImageNet
 task_categories:
   - image-classification
@@ -19,36 +19,34 @@ tags:
   - image-text-retrieval
   - instance-segmentation
   - computational-urban-studies
+  - urban-ai
   - chinese-cities
   - husic
-  - multi-task
+  - cross-modal-retrieval
   - multi-modal
   - scene-classification
   - urban-space-perception
 ---
 
-<!-- =========================================================
-     Urban-ImageNet — Hugging Face Dataset Card
-     Paper: https://arxiv.org/abs/2605.09936
-     GitHub: https://github.com/yiasun/dataset-2
-     ========================================================= -->
 
-# Urban-ImageNet
+# 🏙️ Urban-ImageNet
 
-> **Urban-ImageNet** is a large-scale multi-modal dataset and benchmark for urban space perception from user-generated social media imagery.
+**A Large-Scale Multi-Modal Dataset and Evaluation Framework for Urban Space Perception from User-generated Social Media Imagery.**
 
-[![arXiv](https://img.shields.io/badge/arXiv-2605.09936-b31b1b.svg)](https://arxiv.org/abs/2605.09936)
-[![GitHub](https://img.shields.io/badge/GitHub-yiasun%2Fdataset--2-blue?logo=github)](https://github.com/yiasun/dataset-2)
-[![License: CC BY-NC 4.0](https://img.shields.io/badge/License-CC%20BY--NC%204.0-lightgrey.svg)](https://creativecommons.org/licenses/by-nc/4.0/)
+<p align="center">
+  <a href="https://arxiv.org/abs/2605.09936"><img src="https://img.shields.io/badge/arXiv-2605.09936-b31b1b.svg" alt="arXiv"/></a>
+  <a href="https://github.com/yiasun/dataset-2"><img src="https://img.shields.io/badge/GitHub-yiasun%2Fdataset--2-black?logo=github" alt="GitHub"/></a>
+  <a href="https://huggingface.co/datasets/yiasun/urban-imagenet"><img src="https://img.shields.io/badge/🤗%20HuggingFace-Dataset-yellow" alt="HuggingFace"/></a>
+  <img src="https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey" alt="License"/>
+  <img src="https://img.shields.io/badge/Images-2M%2B-blue" alt="Scale"/>
+  <img src="https://img.shields.io/badge/Cities-24-green" alt="Cities"/>
+</p>
 
----
-
-<!-- Replace the path below with the actual uploaded framework figure -->
-![Urban-ImageNet Framework Overview](Figures/01-Overall-Framework.jpg)
-*Figure 1: The Urban-ImageNet framework — addressing current limitations in urban perception evaluation. The dataset bridges general-purpose vision benchmarks and domain-specific urban research needs through the HUSIC taxonomy and three unified benchmark tasks.*
+> Urban-ImageNet fills a critical gap between computer vision and urban studies by treating cities not simply as visual scenes, but as lived, socially produced, and experientially activated spaces.
 
 ---
 
+
 ## Overview
 
 **ImageNet** taught models to recognise objects. **Urban-ImageNet** teaches them to understand how people *experience* cities.
@@ -63,6 +61,10 @@ The corpus contains over **2 million** public Weibo image–text pairs collected
 | **T2** | Cross-modal image–text retrieval    | Image ↔ Text (bidirectional)          |
 | **T3** | Instance segmentation               | Image → Object masks + bounding boxes |
 
+<!-- Replace the path below with the actual uploaded framework figure -->
+![Urban-ImageNet Framework Overview](Figures/01-Overall-Framework.jpg)
+*Figure 1: The Urban-ImageNet framework — addressing current limitations in urban perception evaluation. The dataset bridges general-purpose vision benchmarks and domain-specific urban research needs through the HUSIC taxonomy and three unified benchmark tasks.*
+
 ---
 
 ## Dataset Variants