update README

README.md

@@ -72,12 +72,11 @@ The dataset was procedurally generated using **NVIDIA Isaac Sim** and **Omnivers
 
 ### Dataset Summary
 
-Visual Perspective Taking is a challenging task that traditionally requires large amounts of precisely labelled real-world data. This dataset serves as a proof-of-concept to explore the viability of using high-fidelity synthetic data as a scalable and cost-effective alternative for metric spatial grounding.
+This dataset serves to explore the viability of using high-fidelity synthetic data as a scalable and cost-effective alternative for metric spatial grounding in the context of Visual Perspective Taking.
 
 The data consists of renders of a target object (**mug**) placed on a tabletop in a shared workspace scene containing a humanoid agent (**x-bot**). For each rendered image, the dataset contains separate entries for each entity, providing its semantic class and exact 6-DOF pose relative to the camera.
 
 * **Total Examples:** 20,000 (derived from 10,000 unique scenes)
-* **Generator:** NVIDIA Omniverse Replicator
 * **Objects:** `mug`, `xbot_humanoid`
 
 ---
@@ -86,9 +85,9 @@ The data consists of renders of a target object (**mug**) placed on a tabletop i
 
 The dataset contains the following fields for each instance:
 
-* **`image`**: A `PIL.Image.Image` object containing the rendered RGB image ($512 \times 512$ pixels).
+* **`image`**: A `PIL.Image.Image` object containing the rendered RGB image ($512 X 512$ pixels).
 * **`semantic_class`**: A `string` indicating the class of the entity for which the pose is provided (e.g., "mug" or "humanoid").
-* **`transform`**: A `string` representing the full $4\times4$ transformation matrix that maps points from the camera's coordinate frame to the object's local coordinate frame.
+* **`transform`**: A `string` representing the full $4 X 4$ transformation matrix that maps points from the camera's coordinate frame to the object's local coordinate frame.
 * **`Tx`, `Ty`, `Tz`**: The translation components (`float`) of the object's pose in metres, extracted from the transformation matrix.
 * **`rot_x`, `rot_y`, `rot_z`, `rot_w`**: The unit quaternion components (`float`) representing the rotation of the object relative to the camera.
 
@@ -110,13 +109,11 @@ The data is split into training, validation, and test sets. Critically, the spli
 
 You can load and use the dataset with the `datasets` library. 
 
-**Note for Reviewers:** Please replace `[ANONYMOUS_USER]/[REPO_NAME]` below with the repository ID where this dataset is currently hosted.
-
 ```python
 from datasets import load_dataset
 
 # Load the dataset from the Hugging Face Hub
-dataset = load_dataset("[ANONYMOUS_USER]/[REPO_NAME]")
+dataset = load_dataset("anonymous-authors-2025/AnonymousDataset")
 
 # Access an example from the training set
 example = dataset['train'][42]