Add dataset card

README.md

@@ -1,29 +1,18 @@
 ---
-dataset_info:
-  features:
-  - name: task_name
-    dtype: string
-  - name: video_idx
-    dtype: string
-  - name: domain
-    dtype: string
-  - name: prompt
-    dtype: string
-  - name: first_frame
-    dtype: image
-  - name: final_frame
-    dtype: image
-  - name: ground_truth_video
-    dtype: binary
-  splits:
-  - name: in_domain
-    num_bytes: 88652293
-    num_examples: 250
-  - name: out_of_domain
-    num_bytes: 85824995
-    num_examples: 250
-  download_size: 132875656
-  dataset_size: 174477288
+language:
+- en
+license: apache-2.0
+task_categories:
+- visual-question-answering
+- video-classification
+tags:
+- video
+- reasoning
+- benchmark
+- i2v
+pretty_name: VBVR-Bench
+size_categories:
+- n<1K
 configs:
 - config_name: default
   data_files:
@@ -32,3 +21,45 @@ configs:
   - split: out_of_domain
     path: data/out_of_domain-*
 ---
+
+# VBVR-Bench
+
+Re-hosted copy of [Video-Reason/VBVR-Bench-Data](https://huggingface.co/datasets/Video-Reason/VBVR-Bench-Data),
+converted to standard HuggingFace parquet format.
+
+## Splits
+- **`in_domain`**: 50 tasks x 5 samples = 250 entries (tasks overlap with the VBVR training set).
+- **`out_of_domain`**: 50 tasks x 5 samples = 250 entries (held-out reasoning tasks).
+
+## Schema
+
+| field | type | notes |
+|---|---|---|
+| `task_name` | string | e.g. `G-13_grid_number_sequence_data-generator` |
+| `video_idx` | string | zero-padded sample id (`00000`..`00004`) |
+| `domain` | string | duplicates split name; convenient for filtering |
+| `prompt` | string | task description fed to the I2V model |
+| `first_frame` | Image (PNG) | I2V condition frame |
+| `final_frame` | Image (PNG) | expected final frame |
+| `ground_truth_video` | binary (MP4) | reference video — decode with decord / PyAV |
+
+## Quick load
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("pufanyi/VBVR-Bench", split="in_domain")
+sample = ds[0]
+sample["first_frame"]          # PIL.Image
+sample["prompt"]               # str
+sample["ground_truth_video"]   # raw MP4 bytes
+
+# Decode the video with decord
+import decord, io
+vr = decord.VideoReader(io.BytesIO(sample["ground_truth_video"]))
+```
+
+## Links
+- Upstream dataset: [Video-Reason/VBVR-Bench-Data](https://huggingface.co/datasets/Video-Reason/VBVR-Bench-Data)
+- Evaluation kit: [Video-Reason/VBVR-EvalKit](https://github.com/Video-Reason/VBVR-EvalKit)
+- Project page: [video-reason.com](https://video-reason.com/)