Duplicate from alibabagroup/CMGUI

Co-authored-by: Wensheng <wensheng0503@users.noreply.huggingface.co>

.gitattributes

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+*.z* filter=lfs diff=lfs merge=lfs -text
+screenshot_zip/*.zip filter=lfs diff=lfs merge=lfs -text
+screenshot_zip/screenshot_eval.zip filter=lfs diff=lfs merge=lfs -text
+episode_annotation_train.jsonl filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,175 @@
+---
+license: cc-by-4.0
+language:
+- zh
+tags:
+- agent
+pretty_name: CMGUI
+size_categories:
+- 100K<n<1M
+---
+# <p align="center"><b>CMGUI Dataset</b></p>
+<p align="center">
+📄 <a href="https://github.com/alibaba/MobiZen-GUI"> Project </a>  |
+🌐 <a href="https://huggingface.co/alibabagroup/MobiZen-GUI-4B">Model in Hugging Face</a>  |
+🌐 <a href="https://modelscope.cn/models/GUIAgent/MobiZen-GUI-4B">Model in ModelScope</a> 
+
+<p align="center">
+  <a href="https://huggingface.co/datasets/alibabagroup/CMGUI/blob/main/README.md">English</a> |
+  <a href="https://huggingface.co/datasets/alibabagroup/CMGUI/blob/main/README_CN.md">简体中文</a>
+</p>
+
+**CMGUI** (Chinese Mobile GUI) is a large-scale, high-quality dataset constructed for developing GUI agents on Chinese mobile applications. The dataset contains **18k episodes** (i.e., trajectories) with **98k steps** collected from more than **50** real-world Chinese mobile apps, covering diverse functional domains such as e-commerce (e.g., Taobao, Pinduoduo), social media (e.g., Rednote, Douyin), and local services (e.g., Meituan, Amap).
+
+**CMGUI-Bench**, the corresponding navigation benchmark derived from CMGUI, comprises 386 episodes and 2,547 steps spanning 44 widely used Chinese apps, featuring multi-choice action annotations to accommodate diverse GUI manipulations where multiple valid actions may exist in each step. Both CMGUI and CMGUI-Bench are rigorously human-verified with precise bounding box annotations, addressing the critical scarcity of high-quality open-source Chinese mobile GUI datasets.
+
+### Key Features
+
+- **Chinese-focused**: Specifically designed for Chinese mobile applications and mobile user interactions
+- **High-quality annotations**: Each episode includes human-verified actions and human-annotated bounding boxes
+- **Multi-resolution support**: Screenshots captured at various device resolutions (e.g., 720x1280, 1080x2400, 1440x3200)
+- **Rich action space**: Supports CLICK, TYPE, SWIPE, and other common mobile interaction patterns
+- **Real-world tasks**: Instructions are designed to reflect practical user scenarios in Chinese mobile app ecosystems
+
+## Dataset Structure
+
+The CMGUI dataset is organized as follows:
+
+```
+CMGUI/
+├── README.md                      # This file
+├── episode_annotation_train.jsonl # Training episode annotations (JSONL format, one episode per line)
+├── episode_annotation_test.jsonl  # Testing/benchmarking episode annotations (JSONL format, one episode per line)
+├── screenshot_zip/                # Directory containing screenshot archives
+│   ├── screenshot_train.zip       # Main screenshot archive for training
+│   ├── screenshot_train.z01       # Split archive part 1
+│   ├── screenshot_train.z02       # Split archive part 2
+│   ├── ...
+│   └── screenshot_test.zip        # Screenshot archive for testing/benchmarking
+└── screenshot/                    # Extracted screenshots (PNG files)
+    ├── 47b85366-5449-4894-9ece-beb2b1b41ced.png
+    ├── 4c0cd4d6-4935-42b2-a867-cf4f4142d2f0.png
+    └── ...
+```
+
+## Episode Annotation Format
+
+The dataset is split into training and testing sets, stored in `episode_annotation_train.jsonl` and `episode_annotation_test.jsonl` respectively. Each line in these JSONL files represents one episode. Below is the detailed field description:
+
+### Episode Data Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `split` | `str` | Dataset split identifier ("train" or "test") |
+| `episode_id` | `int` | Unique identifier for this episode |
+| `instruction` | `str` | Natural language instruction describing the task (in Chinese) |
+| `app` | `str` | Name of the primary mobile application used in this episode |
+| `episode_length` | `int` | Total number of steps in this episode |
+
+### Step Data Fields
+
+The `step_data` field is a list of step objects, each containing the following fields:
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `step_id` | `int` | Zero-indexed step number indicating the position in the episode sequence |
+| `screenshot` | `str` | Filename of the screenshot for this step (located in `screenshot/` directory) |
+| `screenshot_width` | `int` | Width of the screenshot in pixels |
+| `screenshot_height` | `int` | Height of the screenshot in pixels |
+| `action` | `str` | The action type performed at this step. See below for action types |
+| `type_text` | `str` | Text input for TYPE actions; empty string for other action types |
+| `touch_coord` | `list[int]` | Touch coordinates `[x, y]` where the action starts. `[-1, -1]` for non-coordinate actions |
+| `lift_coord` | `list[int]` | Lift coordinates `[x, y]` where the action ends. `[-1, -1]` for non-coordinate actions |
+| `bbox` | `list[list[int]]` | List of bounding box coordinates `[[x1, y1, x2, y2], ...]` of the target UI element(s). Empty list `[]` if not applicable |
+
+**Note:** In the train split, the number of bounding boxes in `bbox` is less than or equal to 1; in the test split, the number of bounding boxes in `bbox` can greater than 1, indicating that multiple UI elements are valid to click on in the corresponding step.
+
+### Action Types
+
+| Action | Description | Parameter |
+|--------|-------------|------------------|
+| **CLICK** | Single tap/click on a UI element | `touch_coord` = `lift_coord` = click position |
+| **LONG_PRESS** | Long press on a UI element | `touch_coord` = `lift_coord` = press position |
+| **SWIPE** | Swipe/scroll gesture | `touch_coord` = start position, `lift_coord` = end position |
+| **TYPE** | Text input action | text in `type_text` |
+| **KEY_BACK** | Press Back button | - |
+| **KEY_HOME** | Press Home button | - |
+| **WAIT** | Wait for page/content to load | - |
+| **STOP** | Task completion signal | - |
+
+### Coordinate System
+
+- All coordinates are in **absolute pixel values** relative to the screenshot dimensions
+- Origin `(0, 0)` is at the **top-left corner** of the screen
+- Bounding box format: `[[x1, y1, x2, y2], ...]` where each `(x1, y1)` is the top-left corner and `(x2, y2)` is the bottom-right corner of a UI element
+
+### Example Episode Structure
+
+```json
+{
+    "split": "train",
+    "episode_id": 0,
+    "instruction": "打开腾讯地图，搜索“望京医院”，发起步行导航",
+    "app": "腾讯地图",
+    "episode_length": 9,
+    "step_data": [
+        {
+            "step_id": 0,
+            "screenshot": "47b85366-5449-4894-9ece-beb2b1b41ced.png",
+            "screenshot_width": 1080,
+            "screenshot_height": 2400,
+            "action": "CLICK",
+            "type_text": "",
+            "touch_coord": [
+                538,
+                643
+            ],
+            "lift_coord": [
+                538,
+                643
+            ],
+            "bbox": [
+                [
+                    474,
+                    581,
+                    604,
+                    708
+                ]
+            ]
+        },
+        // ... more steps
+    ]
+}
+```
+
+## Screenshots Extraction Instructions
+
+To extract all screenshots to the `screenshot/` directory:
+
+**Training screenshots:**
+```bash
+unzip screenshot_zip/screenshot_train.zip -d .
+```
+The `unzip` command will automatically detect and merge the split archives (`.z01`, `.z02`, etc.) during extraction.
+
+**Test screenshots:**
+```bash
+unzip screenshot_zip/screenshot_test.zip -d .
+```
+
+
+
+## Citation
+If you find this dataset helpful in your research, please cite the following paper:
+```
+@article{xie2026secagent,
+    title={SecAgent: Efficient Mobile GUI Agent with Semantic Context}, 
+    author={Yiping Xie and Song Chen and Jingxuan Xing and Wei Jiang and Zekun Zhu and Yingyao Wang and Pi Bu and Jun Song and Yuning Jiang and Bo Zheng},
+    journal={arXiv preprint arXiv:2603.08533},
+    year={2026}
+}
+```
+
+## License
+
+<a rel="license" href="http://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.

README_CN.md

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+# <p align="center"><b>CMGUI 数据集</b></p>
+<p align="center">
+📄 <a href="https://github.com/alibaba/MobiZen-GUI"> 项目主页 </a>  |
+🌐 <a href="https://huggingface.co/alibabagroup/MobiZen-GUI-4B">Hugging Face 模型</a>  |
+🌐 <a href="https://modelscope.cn/models/GUIAgent/MobiZen-GUI-4B">ModelScope 模型</a> 
+
+<p align="center">
+  <a href="https://huggingface.co/datasets/alibabagroup/CMGUI/blob/main/README.md">English</a> |
+  <a href="https://huggingface.co/datasets/alibabagroup/CMGUI/blob/main/README_CN.md">简体中文</a>
+</p>
+
+**CMGUI** (Chinese Mobile GUI) 是一个大规模、高质量的数据集，专门为开发中文移动应用的 GUI 智能体而构建。该数据集包含从 **50 多个**真实中文移动应用中收集的 **18k 条轨迹** 和 **98k 个单步**，涵盖电商（如淘宝、拼多多）、社交媒体（如小红书、抖音）和本地服务（如美团、高德地图）等多个功能领域。
+
+**CMGUI-Bench** 是从 CMGUI 派生出的对应导航基准，包含 386 条轨迹和2,547 个单步，跨越 44 个广泛使用的中文应用，具有多选动作标注，以适应每个单步可能存在多个有效操作的多样化 GUI 操作场景。CMGUI 和 CMGUI-Bench 都经过严格的人工验证，并带有精确的边界框标注，解决了高质量开源中文移动 GUI 数据集严重稀缺的问题。
+
+### 核心特性
+
+- **面向中文**：专为中文移动应用和移动用户交互设计
+- **高质量标注**：每条轨迹都包含人工验证的动作和人工标注的边界框
+- **多分辨率支持**：在不同设备分辨率（如 720x1280、1080x2400、1440x3200）下捕获截图
+- **丰富的动作空间**：支持 CLICK、TYPE、SWIPE 等常见移动交互模式
+- **真实任务**：指令设计反映了中文移动应用生态系统中的实际用户场景
+
+## 数据集结构
+
+CMGUI 数据集的组织结构如下：
+
+```
+CMGUI/
+├── README.md                      # 本文件
+├── episode_annotation_train.jsonl # 训练轨迹标注（JSONL 格式，每行一个轨迹）
+├── episode_annotation_test.jsonl  # 测试轨迹标注（JSONL 格式，每行一个轨迹）
+├── screenshot_zip/                # 包含屏幕截图归档的目录
+│   ├── screenshot_train.zip       # 训练集主要屏幕截图归档
+│   ├── screenshot_train.z01       # 分割归档第 1 部分
+│   ├── screenshot_train.z02       # 分割归档第 2 部分
+│   ├── ...
+│   └── screenshot_test.zip        # 测试/基准截图归档
+└── screenshot/                    # 解压后的截图（PNG 文件）
+    ├── 47b85366-5449-4894-9ece-beb2b1b41ced.png
+    ├── 4c0cd4d6-4935-42b2-a867-cf4f4142d2f0.png
+    └── ...
+```
+
+## 轨迹标注格式
+
+数据集分为训练集和测试集，分别存储在 `episode_annotation_train.jsonl` 和 `episode_annotation_test.jsonl` 中。这些 JSONL 文件中的每一行代表一条轨迹。以下是详细的字段说明：
+
+### 轨迹数据字段
+
+| 字段 | 类型 | 描述 |
+|-------|------|-------------|
+| `split` | `str` | 数据集划分标识符（"train" 或 "test"） |
+| `episode_id` | `int` | 轨迹的唯一标识符 |
+| `instruction` | `str` | 描述任务的自然语言指令（中文） |
+| `app` | `str` | 轨迹中使用的主要移动应用名称 |
+| `episode_length` | `int` | 轨迹中的总单步数 |
+
+### 单步数据字段
+
+`step_data` 字段是一个单步对象列表，每个对象包含以下字段：
+
+| 字段 | 类型 | 描述 |
+|-------|------|-------------|
+| `step_id` | `int` | 从0开始的单步编号，表示在 episode 序列中的位置 |
+| `screenshot` | `str` | 该单步的截图文件名（位于 `screenshot/` 目录中） |
+| `screenshot_width` | `int` | 截图的宽度（像素） |
+| `screenshot_height` | `int` | 截图的高度（像素） |
+| `action` | `str` | 在该单步执行的动作类型。见下方动作类型说明 |
+| `type_text` | `str` | TYPE 动作的文本输入；其他动作类型为空字符串 |
+| `touch_coord` | `list[int]` | 动作开始的触摸坐标 `[x, y]`。非坐标动作为 `[-1, -1]` |
+| `lift_coord` | `list[int]` | 动作结束的抬起坐标 `[x, y]`。非坐标动作为 `[-1, -1]` |
+| `bbox` | `list[list[int]]` | 目标 UI 元素的边界框坐标列表 `[[x1, y1, x2, y2], ...]`。不适用则为空列表 `[]` |
+
+**注意:** 在训练集中，`bbox` 中的边界框数量小于或等于 1；在测试集中，`bbox` 中的边界框数量可以大于 1，表示在对应单步中存在多个可点击的有效 UI 元素。
+
+### 动作类型
+
+| 动作 | 描述 | 参数 |
+|--------|-------------|------------------|
+| **CLICK** | 单击/点击 UI 元素 | `touch_coord` = `lift_coord` = 点击位置 |
+| **LONG_PRESS** | 长按 UI 元素 | `touch_coord` = `lift_coord` = 按压位置 |
+| **SWIPE** | 滑动/滚动手势 | `touch_coord` = 起始位置，`lift_coord` = 结束位置 |
+| **TYPE** | 文本输入动作 | `type_text` 中的文本 |
+| **KEY_BACK** | 按返回键 | - |
+| **KEY_HOME** | 按主页键 | - |
+| **WAIT** | 等待页面/内容加载 | - |
+| **STOP** | 任务完成信号 | - |
+
+### 坐标系统
+
+- 所有坐标都是相对于截图尺寸的**绝对像素值**
+- 原点 `(0, 0)` 位于屏幕的**左上角**
+- 边界框格式：`[[x1, y1, x2, y2], ...]`，其中每个 `(x1, y1)` 是 UI 元素的左上角，`(x2, y2)` 是右下角
+
+### 轨迹数据示例
+
+```json
+{
+    "split": "train",
+    "episode_id": 0,
+    "instruction": "打开腾讯地图，搜索“望京医院”，发起步行导航",
+    "app": "腾讯地图",
+    "episode_length": 9,
+    "step_data": [
+        {
+            "step_id": 0,
+            "screenshot": "47b85366-5449-4894-9ece-beb2b1b41ced.png",
+            "screenshot_width": 1080,
+            "screenshot_height": 2400,
+            "action": "CLICK",
+            "type_text": "",
+            "touch_coord": [
+                538,
+                643
+            ],
+            "lift_coord": [
+                538,
+                643
+            ],
+            "bbox": [
+                [
+                    474,
+                    581,
+                    604,
+                    708
+                ]
+            ]
+        },
+        // ... more steps
+    ]
+}
+```
+
+## 截图解压说明
+
+将所有截图解压到 `screenshot/` 目录：
+
+**训练集截图：**
+```bash
+unzip screenshot_zip/screenshot_train.zip -d .
+```
+`unzip` 命令会在解压过程中自动检测并合并分卷归档（`.z01`、`.z02` 等）。
+
+**测试集截图：**
+```bash
+unzip screenshot_zip/screenshot_test.zip -d .
+```
+
+## 引用
+如果您发现该数据集对您的研究有帮助，请引用以下论文：
+```
+@article{xie2026secagent,
+    title={SecAgent: Efficient Mobile GUI Agent with Semantic Context}, 
+    author={Yiping Xie and Song Chen and Jingxuan Xing and Wei Jiang and Zekun Zhu and Yingyao Wang and Pi Bu and Jun Song and Yuning Jiang and Bo Zheng},
+    journal={arXiv preprint arXiv:2603.08533},
+    year={2026}
+}
+```
+
+## 许可证
+
+<a rel="license" href="http://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br />本作品采用 <a rel="license" href="http://creativecommons.org/licenses/by/4.0/">知识共享署名 4.0 国际许可协议</a> 进行许可。

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