Update README.md

README.md

@@ -19,7 +19,7 @@ size_categories:
 
 ## 📦 Dataset Description
 
-This repository contains the **test set with human-annotated object captions** used to evaluate captioning consistency in the ICCV 2025 paper.
+This repository contains the **test set with human-annotated object captions** used to evaluate captioning consistency in the paper [Embodied Image Captioning (ICCV 2025)](https://arxiv.org/abs/2504.08531).
 
 The data is collected from simulated indoor environments (Gibson and HM3D), where an agent explores the scene and captures RGB views of objects from different perspectives. Each object is annotated with a **single human-written caption**, verified to describe the object consistently across multiple views.
 
@@ -31,21 +31,32 @@ This test set enables rigorous evaluation of object-level image captioning model
 
 - `images/`:
   - `gibson/`:
-    - `gibson_rg/`: File containing the images collected using random goal exploration policy (.npy)
-    - `gibson_fr/`: File containing the images collected using frontier exploration policy (.npy)
-    - `gibson_cla/`: File containing the images collected using CLA exploration policy (.npy)
-    
-- `annotations`:
+    - `gibson_rg/`: Images collected using a random goal exploration policy (.npz)
+    - `gibson_fr/`: Images collected using a frontier exploration policy (.npz)
+    - `gibson_cla/`: Images collected using a CLA exploration policy (.npz)
+
+- `annotations/`:
   - `gibson_annotations.csv`
   - `hm3d_annotations.csv`
-    - `filename`: Path to the image file 
-    - `episode_id`: Scene identifier
-    - `object_id`: Unique object instance ID
-    - `bbox`: Bounding box coordinates (format: x, y, w, h)
-    - `caption`: Human-annotated caption for the object
+    - `filename`: Path to the image file  
+    - `episode_id`: Scene identifier  
+    - `object_id`: Unique object instance ID  
+    - `bbox`: Bounding box coordinates (format: x, y, w, h)  
+    - `caption`: Human-annotated caption for the object  
 
 ---
 
+## ⬇️ How to Download
+
+You can download the dataset using the [🤗 Datasets library](https://huggingface.co/docs/datasets/) with the following code:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("TommyBsk/Embodied-Captioning")
+```
+
+
 ## 🧪 Intended Use
 
 This test set is for **evaluation only**.