Update README.md

README.md

@@ -18,56 +18,48 @@ size_categories:
 <!-- contents with emoji -->
 
 ## 🔔 News
+🔥[2025-12]: Our MMSI-Video-Bench has been integrated into [VLMEvalKit](https://github.com/open-compass/VLMEvalKit).
 🔥[2025-12]: We released our paper, benchmark, and evaluation codes.
 
 
-## Dataset Description
+## 📊 Data Details
 
-`frames.zip` contains all key frames corresponding to each question, 
-`videos.zip` contains all original video data (optional), 
-`ref_images.zip` includes the reference images used in the question descriptions, 
-and `mmsivideo.json` corresponds to the MMSI-Video-Bench annotations. Each sample follows the format below:
+All of our data is available on [Hugging Face](https://huggingface.co/datasets/rbler/MMSI-Video-Bench) and includes the following components:
 
-```python
-{
+🎥 **Video Data** (`videos.zip`): Contains the video clip file (.mp4) corresponding to each sample. This file is generally not required for most models.
+
+🎥 **Frame Data** (`frames.zip`): Contains the frames (.jpg) extracted from each sample's video at the **base sampling rate**. This rate ensures no key information loss during sampling.  Each frame file is named using the format `{timestamp}_frame_{base_interval}_{image_id}` (e.g., 00:06.00_frame_1.50_4), where the timestamp, also shown on the **top-left corner** of the frame, indicates its **capture time in the original recording**.
 
-        "id": "question_0004",
-        "type": "Planning",  // Type of the question (e.g., Spatial Construction, Motion Understanding, Planning, Prediction, Cross-View Reasoning)
-        "ref_images": [
-            "question_0004/image_content_1.png"  // List of reference images associated with the question
-        ],
-        "ori_question": "The video is shot from a bird's-eye view of a building. I will provide you with an image showing my position and orientation on the ground (the red dot represents my position and the arrow shows my orientation)<image>Please answer: If I want to view the statue from the front, how many paths are there to reach the target point? Among these paths, what is the shortest route?",
-        // Original question text; may contain placeholders like <image> to indicate where reference images should be shown
-        "options": [
-            "3 paths; the shortest path is to enter the building from the rear-right passage and walk straight to the target point",
-            ...
-        ],
-        "frames_list": [
-            [
-                "question_0004/dl3dv_0015_0/00:00.00_frame_1.00_0.jpg",
-                ...
-                // List of key frames for the corresponding video segment
-            ]
-        ],
-        "video_list": [
-            {
-                "path": "question_0004/dl3dv_0015_0.mp4",
-                "start": 0.0,
-                "end": 30.0,
-                "base_fps": 1.0
-            }
-        // List of information of the corresponding video segment
-        ]
-        "system_prompt": "Please answer questions based on video content. ...",
-        "task_prompt": "This task ...",
-        "user_prompt": "The video I provided to you is: <video>. Next, I will ask a question based on the video information. My question is: ...",
-        "format_prompt": " Please select the correct answer from the following options: ...",
-        "ground_truth": "D"
+🖼️ **Reference Image Data** (`ref_images.zip`): Contains the auxiliary images referenced in the questions for each sample.
 
+📝 **Text Annotation** (`mmsivideo.json`)：This file contains the annotation information for MMSI-Video-Bench. All time references in the questions correspond to the capture time in the original recording and **align with** the timestamp flag on each frame. Key fields include:
+
+```
+{
+  "ref_images": [Paths to auxiliary images referenced in the question,...],
+  "video_list": [
+    {
+      "path": Video clip file path,
+      "start": Timestamp (in seconds) of the first frame of the video clip in the original recording,
+      "end": Timestamp (in seconds) of the last frame of the video clip in the original recording,
+      "base_fps": Base sampling rate
+    },
+    ...
+  ],
+  "frames_list": [[Paths to frames sampled at the base sampling rate,...],...],
+  "system_prompt": "...",
+  "task_prompt": Task-specific prompt,
+  "user_prompt": Question text, with <video> as a placeholder for video and <image> for auxiliary images,
+  "format_prompt": Output format requirements,
+  "ground_truth": Correct answer
 }
 ```
 
-## Evaluation
+
+Unless otherwise specified, the model input generally consists of:
+`system_prompt + task_prompt + user_prompt + format_prompt`.
+
+## 🚀 Evaluation
 Please refer to the evaluation guidelines in our [github repo](https://github.com/InternRobotics/MMSI-Video-Bench).
 
 ## 🏆 Leaderboard