Update README.md

README.md

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----
-license: cc-by-nc-sa-4.0
----
+---
+license: cc-by-nc-sa-4.0
+task_categories:
+- video-classification
+- visual-question-answering
+- question-answering
+language:
+- en
+size_categories:
+- n<1K
+---
+
+# MORSE-500 Benchmark
+
+<table>
+  <tr>
+    <td style="padding: 0;">
+      <a href="https://morse-500.github.io">
+        <img src="https://img.shields.io/badge/Website-1E90FF?style=for-the-badge&logo=firefox&logoColor=ffffff&labelColor" alt="Website">
+      </a>
+    </td>
+    <td style="padding: 0;">
+      <a href="https://huggingface.co/datasets/video-reasoning/morse-500">
+        <img src="https://img.shields.io/badge/Data-D5A848?style=for-the-badge&logo=huggingface&logoColor=ffffff&labelColor" alt="Data">
+      </a>
+    </td>
+    <td style="padding: 0;">
+      <a href="https://huggingface.co/datasets/video-reasoning/morse-500-view">
+        <img src="https://img.shields.io/badge/View-D5A848?style=for-the-badge&logo=huggingface&logoColor=ffffff&labelColor" alt="Viewer">
+      </a>
+    </td>
+    <td style="padding: 0;">
+      <a href="https://github.com/morse-benchmark/morse-500">
+        <img src="https://img.shields.io/badge/Code-000000?style=for-the-badge&logo=github&logoColor=white" alt="Code">
+      </a>
+    </td>
+    <td style="padding: 0;">
+      <a href="https://arxiv.org/abs/TBA">
+        <img src="https://img.shields.io/badge/arXiv-TBA-b31b1b.svg?style=for-the-badge" alt="arXiv">
+      </a>
+    </td>
+  </tr>
+</table>
+
+## 🔥 News
+- **May 15, 2025**: We release **`MORSE-500`**, 500 programmatically generated videos across six reasoning categories: abstract, mathematical, physical, planning, spatial, and temporal, to stress-test multimodal reasoning. Frontier models including OpenAI o3 and Gemini 2.5 Pro score lower than 25% accuracy (see 🏆[`Leaderboard`](https://morse-500.github.io/#leaderboard)).
+- **Visit 🤗 Data: [`morse-500`](https://huggingface.co/datasets/video-reasoning/morse-500) for newer updates**
+
+## 📦 Resource
+- 🌐 Websie: [`morse-500`](https://morse-500.github.io)
+- 🤗 Data: [`morse-500`](https://huggingface.co/datasets/video-reasoning/morse-500)
+- 🤗 Video Viewer: [`morse-500-view`](https://huggingface.co/datasets/video-reasoning/morse-500-view)
+- 💻 Code: [`morse-500`](https://github.com/morse-benchmark/morse-500)
+- 📝 Paper: [`arXiv:TBA`](https://arxiv.org/abs/xxx)
+
+
+## ✨ Key Features
+
+| Aspect | Details |
+| --- | --- |
+| **Fresh & Portable** | 500 newly cooked video clips + CSV metadata that runs fast |
+| **Scalable Difficulty** | Videos are generated programmatically so we can dial up complexity and release harder versions as models improve |
+| **Diverse Categories** | Spanning  *Abstract, Mathematical, Physical, Planning, Spatial, Temporal (+ Causal)* – a vibrant mix of the reasoning types that matter |
+| **Pure Visual Reasoning** | Questions are baked right into the videos. No text crutches, no shortcuts – if you can't see it, you can't solve it |
+| **Developer-Friendly** | A “[-view](https://huggingface.co/datasets/video-reasoning/morse-500-view)” subset streams directly on **Hugging Face**, making browsing and debugging smoother than a sunny afternoon |
+
+
+## 📂 Dataset Structure
+
+- `test.csv`: Contains the dataset metadata, including video file name, query, ground_truth, question_text, and category
+- `test.zip`: Contains all MP4 video files
+- `test_sz512.zip`: Contains MP4 video files resized to 512px for longside while keeping the original aspect ratio
+
+## ⚡ Quick Start
+
+```bash
+### In bash ###
+# download the videos
+git clone https://huggingface.co/datasets/video-reasoning/morse-500
+
+# unzip the videos
+cd morse-500
+# unzip test.zip -d test                # original size
+unzip test_sz512.zip -d test_sz512    # long side resized to 512
+
+
+### In python ###
+# load dataset metadata ("idx", "video", "query", "question_text", "ground_truth", "category")
+from datasets import load_dataset
+dataset = load_dataset('video-reasoning/morse-500')
+dataset = dataset['test']
+video_root = 'test_sz512' # use the resize videos
+
+# run your model on the benchmark
+for i, example in enumerate(dataset):
+  video_path = f"{video_root}/" + example["video"]
+  print(f"Processing {i} {video_path}")
+  query = "Answer the question in this video."
+  gt = example['ground_truth']
+
+  # if your model has video support
+  answer = query_video(model_name, video_path, query)
+  # otherwise query with image frames, default 2 fps capped at 32 total frames
+  # answer = query_video_frames(model_name, video_path, query, fps=2, max_num_frames=32)
+  
+  print(f"Answer: {answer}")
+  print(f"GT: {gt}")
+```
+
+Example query_video function
+```python
+model_name = "xxx"
+openai_api_key = "xxx"
+openai_api_base = "xxx"
+client = OpenAI(
+  api_key=openai_api_key,
+  base_url=openai_api_base,
+)
+
+
+def encode_b64(file_path):
+  with open(file_path, "rb") as file:
+      return base64.b64encode(file.read()).decode("utf-8")
+
+base64_video = encode_b64(video_path)
+video_url = f"data:video/mp4;base64,{base64_video}"
+
+response = client.chat.completions.create(
+    model=model_name,
+    messages=[
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "text",
+                    "text": query
+                },
+                {
+                    "type": "video_url",
+                    "video_url": {"url": video_url},
+                },
+            ],
+        }
+    ],
+)
+
+result = response.choices[0].message.content
+print(result)
+```
+## More scripts can be found on Github https://github.com/morse-benchmark/morse-500