Update README.md

README.md

@@ -8,13 +8,16 @@ language:
 
 # MMEB-V2 (Massive Multimodal Embedding Benchmark)
 
-Building upon on our original [MMEB](https://arxiv.org/abs/2410.05160), MMEB-V2 expands the evaluation scope to include five new tasks: four video-based tasks — Video Retrieval, Moment Retrieval, Video Classification, and Video Question Answering — and one task focused on visual documents, Visual Document Retrieval. This comprehensive suite enables robust evaluation of multimodal embedding models across static, temporal, and structured visual data settings.
+Building upon on our original [**MMEB**](https://arxiv.org/abs/2410.05160), **MMEB-V2** expands the evaluation scope to include five new tasks: four video-based tasks — Video Retrieval, Moment Retrieval, Video Classification, and Video Question Answering — and one task focused on visual documents, Visual Document Retrieval. This comprehensive suite enables robust evaluation of multimodal embedding models across static, temporal, and structured visual data settings.
+
+**This Hugging Face repository contains only the raw image and video files used in MMEB-V2, which need to be downloaded in advance.**
+The test data for each task in MMEB-V2 is available [here](https://huggingface.co/VLM2Vec) and will be automatically downloaded and used by our code. More details on how to set it up are provided in the following sections.
 
 |[**Github**](https://github.com/TIGER-AI-Lab/VLM2Vec) | [**🏆Leaderboard**](https://huggingface.co/spaces/TIGER-Lab/MMEB) | [**📖MMEB-V2/VLM2Vec-V2 Paper (TBA)**](https://arxiv.org/abs/2410.05160) | | [**📖MMEB-V1/VLM2Vec-V1 Paper**](https://arxiv.org/abs/2410.05160) |
 
 
 ## 🚀 What's New
-- **\[2025.05\]** Initial release.
+- **\[2025.05\]** Initial release of MMEB-V2.
 
 
 ## Dataset Overview
@@ -25,7 +28,10 @@ We present an overview of the MMEB-V2 dataset below:
 
 ## Dataset Structure
 
-Below is the directory structure for this Huggingface Repo:
+The directory structure of this Hugging Face repository is shown below. 
+For video tasks, we provide both sampled frames and raw videos (the latter will be released later). For image tasks, we provide the raw images.
+Files from each meta-task are zipped together, resulting in six files. For example, ``video_cls.tar.gz`` contains the sampled frames for the video classification task.
+
 ```
 
 → video-tasks/
@@ -34,15 +40,42 @@ Below is the directory structure for this Huggingface Repo:
 │   ├── video_qa.tar.gz
 │   ├── video_ret.tar.gz
 │   └── video_mret.tar.gz
-├── raw videos/ (TBA)
-│   ├── video_cls.tar.gz
-│   ├── video_qa.tar.gz
-│   ├── video_ret.tar.gz
-│   └── video_mret.tar.gz
+├── raw videos/ (To be released)
 
 → image-tasks/
 ├── mmeb_v1.tar.gz
 └── visdoc.tar.gz
 
+```
+
+After downloading and unzipping these files locally, you can organize them as shown below. (You may choose to use ``Git LFS`` or ``wget`` for downloading.)
+Then, simply specify the correct file path in the configuration file used by your code.
 
 ```
+
+→ MMEB
+├── video-tasks/
+│   └── frames/
+│       ├── video_cls/
+│       │   ├── UCF101/
+│       │   │   └── video_1/          # video ID
+│       │   │       ├── frame1.png    # frame from video_1
+│       │   │       ├── frame2.png
+│       │   │       └── ...
+│       │   ├── HMDB51/
+│       │   ├── Breakfast/
+│       │   └── ...                   # other datasets from video classification category
+│       ├── video_qa/
+│       │   └── ...                   # video QA datasets
+│       ├── video_ret/
+│       │   └── ...                   # video retrieval datasets
+│       └── video_mret/
+│           └── ...                   # moment retrieval datasets
+├── image-tasks/
+│   ├── mmeb_v1/
+│   │   └── ...                       # MMEB-V1 datasets
+│   └── visdoc/
+│       └── ...                       # visual document retrieval datasets
+
+
+```