udapte readme

README.md

@@ -336,6 +336,48 @@ dataset_info:
 
 **Causal3D** is a comprehensive benchmark designed to evaluate models’ abilities to uncover *latent causal relations* from structured and visual data. This dataset integrates **3D-rendered scenes** with **tabular causal annotations**, providing a unified testbed for advancing *causal discovery*, *causal representation learning*, and *causal reasoning* with **vision-language models (VLMs)** and **large language models (LLMs)**.
 
+## 🖼️ Visual Previews
+
+Below are example images from different Causal3D scenes:
+
+<table>
+  <tr>
+    <td align="center">
+      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/parabola.png" width="250"/><br/>parabola
+    </td>
+    <td align="center">
+      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/convex.png" width="250"/><br/>convex
+    </td>
+  </tr>
+  <tr>
+    <td align="center">
+      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/magnetic.png" width="200"/><br/>magnetic
+    </td>
+    <td align="center">
+      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/pendulum.png" width="200"/><br/>pendulum
+    </td>
+    <td align="center">
+      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/reflection.png" width="200"/><br/>reflection
+    </td>
+  </tr>
+  <tr>
+    <td align="center">
+      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/seesaw.png" width="200"/><br/>seesaw
+    </td>
+    <td align="center">
+      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/spring.png" width="200"/><br/>spring
+    </td>
+    <td align="center">
+      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/water_flow.png" width="200"/><br/>water_flow
+    </td>
+  </tr>
+</table>
+
+<!-- - `causal_graph.json`: Ground-truth causal structure (as adjacency matrix or graph).
+- `view_info.json`: Camera/viewpoint metadata.
+- `split.json`: Recommended train/val/test splits for benchmarking. -->
+
+
 ## 📚 Usage
 
 #### 🔹 Option 1: Load from Hugging Face
@@ -365,11 +407,9 @@ croissant_dataset = mlc.Dataset(
     "https://www.kaggle.com/datasets/dsliu0011/causal3d-image-dataset/croissant/download"
 )
 
-# List available record sets
 record_sets = croissant_dataset.metadata.record_sets
 print(record_sets)
 
-# Load records from the first record set
 df = pd.DataFrame(croissant_dataset.records(record_set=record_sets[0].uuid))
 print(df.head())
 ```
@@ -394,48 +434,6 @@ Each sub-dataset (scene) contains:
 - `images/`: Rendered images under different camera views and backgrounds.
 - `tabular.csv`: Instance-level annotations including object attributes in causal graph.
 
-
-## 🖼️ Visual Previews
-
-Below are example images from different Causal3D scenes:
-
-<table>
-  <tr>
-    <td align="center">
-      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/parabola.png" width="250"/><br/>parabola
-    </td>
-    <td align="center">
-      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/convex.png" width="250"/><br/>convex
-    </td>
-  </tr>
-  <tr>
-    <td align="center">
-      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/magnetic.png" width="200"/><br/>magnetic
-    </td>
-    <td align="center">
-      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/pendulum.png" width="200"/><br/>pendulum
-    </td>
-    <td align="center">
-      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/reflection.png" width="200"/><br/>reflection
-    </td>
-  </tr>
-  <tr>
-    <td align="center">
-      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/seesaw.png" width="200"/><br/>seesaw
-    </td>
-    <td align="center">
-      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/spring.png" width="200"/><br/>spring
-    </td>
-    <td align="center">
-      <img src="https://huggingface.co/datasets/LLDDSS/Causal3D/resolve/main/preview/water_flow.png" width="200"/><br/>water_flow
-    </td>
-  </tr>
-</table>
-
-<!-- - `causal_graph.json`: Ground-truth causal structure (as adjacency matrix or graph).
-- `view_info.json`: Camera/viewpoint metadata.
-- `split.json`: Recommended train/val/test splits for benchmarking. -->
-
 ---
 
 ## 🎯 Evaluation Tasks