Add v3.2.0 Windows .exe and macOS arm64 .dmg installers; refresh model card

.gitattributes

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 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 TOM.exe filter=lfs diff=lfs merge=lfs -text
+TOM-Tongue-Segmentation-v3.2.0.exe filter=lfs diff=lfs merge=lfs -text
+TOM-Tongue-Segmentation-v3.2.0-arm64.dmg filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,203 @@
----
-license: mit
----
+---
+license: mit
+language:
+  - en
+  - zh
+tags:
+  - tongue-segmentation
+  - tcm
+  - traditional-chinese-medicine
+  - medical-imaging
+  - image-segmentation
+  - desktop-app
+library_name: pytorch
+pipeline_tag: image-segmentation
+---
+
+# TOM 舌象分割工具 · TOM Tongue Segmentation
+
+> AI 驱动的中医舌象智能分割工具 · AI-powered tongue segmentation for TCM research
+
+<p align="center">
+  <img src="https://raw.githubusercontent.com/orangeshushu/TOM-Tongue-Segmentation-Model/main/docs/assets/icon.png" alt="TOM app icon" width="128">
+</p>
+
+[![GitHub](https://img.shields.io/badge/GitHub-orangeshushu%2FTOM--Tongue--Segmentation--Model-black?logo=github)](https://github.com/orangeshushu/TOM-Tongue-Segmentation-Model)
+[![Release](https://img.shields.io/github/v/release/orangeshushu/TOM-Tongue-Segmentation-Model)](https://github.com/orangeshushu/TOM-Tongue-Segmentation-Model/releases)
+[![Platform](https://img.shields.io/badge/platform-Windows%20%7C%20macOS-blue)](https://github.com/orangeshushu/TOM-Tongue-Segmentation-Model/releases)
+[![License](https://img.shields.io/badge/license-MIT-green)](https://github.com/orangeshushu/TOM-Tongue-Segmentation-Model/blob/main/LICENSE)
+
+**[🇨🇳 中文](#-中文版) · [🇺🇸 English](#-english)**
+
+---
+
+## 🇨🇳 中文版
+
+一款面向中医研究与临床的舌象分割桌面工具，自动从舌头照片中分离出舌体区域，支持单张精修和批量处理。
+
+### ✨ 功能特性
+
+- 🎯 **一键自动分割** —— 打开图片即自动识别舌头区域，通常 1–3 秒完成
+- 🎨 **交互式微调** —— 通过点击 / 框选快速修正分割结果，每次标注后自动重算
+- 📁 **批量处理** —— 整个文件夹一次性处理,可同时输出多种格式
+- 💾 **三种输出格式** —— 透明背景 PNG · 二值掩膜 · 叠加可视化
+- ⚡ **高精度模式** —— 可选 GrabCut 边界精修，更贴合舌体边缘
+- 🌏 **中英双语界面** —— 一键切换中文 / English
+- 🪟 **绿色安装** —— 双击安装即用，无需 Python / CUDA 环境
+
+### 📥 下载安装
+
+可直接从本仓库下载，或前往 [**GitHub Releases**](https://github.com/orangeshushu/TOM-Tongue-Segmentation-Model/releases) 页面：
+
+| 文件 | 大小 | 平台 |
+|---|---|---|
+| [`TOM-Tongue-Segmentation-v3.2.0.exe`](./TOM-Tongue-Segmentation-v3.2.0.exe) | 565 MB | Windows 10 / 11（64 位） |
+| [`TOM-Tongue-Segmentation-v3.2.0-arm64.dmg`](./TOM-Tongue-Segmentation-v3.2.0-arm64.dmg) | 354 MB | macOS 11+（Apple Silicon） |
+
+**Windows**：双击 `.exe` 运行安装向导，可选择：
+- **语言**：中文 / English（界面语言可在安装后随时切换）
+- **安装位置**：默认 `%LOCALAPPDATA%\Programs\TOM舌象分割工具\`
+- **桌面快捷方式**：是否创建
+
+安装完成后从开始菜单或桌面快捷方式启动。
+
+**macOS**：双击 `.dmg` 挂载，将 `TOM Tongue Segmentation.app` 拖入 `Applications` 文件夹即可。首次启动时由于未经 Apple 公证，可能提示「无法验证开发者」——请在 `Applications` 中**右键点击应用 → 选择「打开」→ 在弹窗中再次点「打开」**即可正常运行，之后双击启动不再提示。
+
+### 🚀 使用方法
+
+#### 单张图片处理
+
+![单张图片界面](https://raw.githubusercontent.com/orangeshushu/TOM-Tongue-Segmentation-Model/main/docs/main_zh_single.png)
+
+1. 点击 **打开图片**，选择一张舌头照片
+2. 等待 1–3 秒，应用自动完成分割
+3. 如对结果不满意，可进行交互式微调：
+   - **Shift + 左键拖动**：框选舌头区域（最准确）
+   - **左键点击**：标记舌头（前景点）
+   - **右键点击**：标记背景
+   - 每次标注后会自动重新分割
+4. 满意后点击 **保存结果**，选择输出文件夹
+5. 自动生成三种输出：透明背景 PNG · 二值掩膜 · 叠加可视化图
+
+#### 批量处理
+
+![批量处理界面](https://raw.githubusercontent.com/orangeshushu/TOM-Tongue-Segmentation-Model/main/docs/main_zh_batch.png)
+
+1. 切换到 **批量处理** 标签页
+2. 选择 **输入文件夹**（内含待处理的舌头图片）
+3. 选择 **输出文件夹**
+4. 勾选需要的输出类型（抠图 / 掩膜 / 叠加图）
+5. 可选：勾选 **高精度模式**（GrabCut 边界精修，每张多耗时约零点几秒）
+6. 点击 **开始批量分割**
+7. 进度条和日志会实时显示处理状态
+
+支持的图片格式：`.jpg` `.jpeg` `.png` `.bmp` `.tif` `.tiff` `.webp`
+
+#### 切换语言
+
+点击右上角 **EN / 中** 按钮即可在中英文之间切换。
+
+### 📋 系统要求
+
+- **操作系统**：Windows 10 / 11（64 位）· macOS 11 Big Sur 或更高（Apple Silicon，M1/M2/M3/M4）
+- **内存**：4 GB RAM 以上（推荐 8 GB）
+- **磁盘空间**：约 1.5 GB
+- **加速**：Windows 可选 GPU 加速 · macOS 自动启用 Apple MPS 加速（CPU 也能正常运行）
+
+---
+
+## 🇺🇸 English
+
+A desktop tongue-segmentation tool for TCM research and clinical use. Automatically isolates the tongue region from a photograph, with support for single-image fine-tuning and batch processing.
+
+### ✨ Features
+
+- 🎯 **One-click auto segmentation** — Tongue region is identified automatically on opening, typically in 1–3 seconds
+- 🎨 **Interactive fine-tuning** — Click / box-select to correct results; re-segments after every edit
+- 📁 **Batch processing** — Process an entire folder at once, output multiple formats simultaneously
+- 💾 **Three output formats** — Transparent PNG cutout · Binary mask · Overlay visualization
+- ⚡ **High-accuracy mode** — Optional GrabCut boundary refinement for tighter edges
+- 🌏 **Bilingual UI** — Switch between English and 中文 with one click
+- 🪟 **Standalone install** — Double-click installer, no Python / CUDA setup required
+
+### 📥 Download & Install
+
+Download directly from this repository, or visit the [**GitHub Releases**](https://github.com/orangeshushu/TOM-Tongue-Segmentation-Model/releases) page:
+
+| File | Size | Platform |
+|---|---|---|
+| [`TOM-Tongue-Segmentation-v3.2.0.exe`](./TOM-Tongue-Segmentation-v3.2.0.exe) | 565 MB | Windows 10 / 11 (64-bit) |
+| [`TOM-Tongue-Segmentation-v3.2.0-arm64.dmg`](./TOM-Tongue-Segmentation-v3.2.0-arm64.dmg) | 354 MB | macOS 11+ (Apple Silicon) |
+
+**Windows**: Double-click the `.exe` to run the installer wizard, which lets you choose:
+- **Language**: 中文 / English (UI language can be switched anytime after install)
+- **Install location**: defaults to `%LOCALAPPDATA%\Programs\TOM Tongue Segmentation\`
+- **Desktop shortcut**: yes / no
+
+Launch from the Start menu or desktop shortcut after install.
+
+**macOS**: Double-click the `.dmg` to mount it, then drag `TOM Tongue Segmentation.app` into the `Applications` folder. Because the bundle is not Apple-notarized, the first launch may show *"cannot be verified"*. To get past it, **right-click the app in `Applications` → Open → Open** in the confirmation dialog. After that first launch, double-clicking works normally.
+
+### 🚀 How to Use
+
+#### Single Image
+
+![Single image UI](https://raw.githubusercontent.com/orangeshushu/TOM-Tongue-Segmentation-Model/main/docs/main_en_single.png)
+
+1. Click **Open Image** and pick a tongue photo
+2. Wait 1–3 seconds — the app segments automatically
+3. If you want to refine the result:
+   - **Shift + left-drag**: box the tongue region (most accurate)
+   - **Left click**: add a foreground (tongue) point
+   - **Right click**: mark background
+   - Re-segmentation runs after every edit
+4. When satisfied, click **Save Results** and pick an output folder
+5. Three outputs are produced: transparent PNG · binary mask · overlay visualization
+
+#### Batch Folder
+
+![Batch UI](https://raw.githubusercontent.com/orangeshushu/TOM-Tongue-Segmentation-Model/main/docs/main_en_batch.png)
+
+1. Switch to the **Batch Folder** tab
+2. Pick an **Input folder** (containing tongue images)
+3. Pick an **Output folder**
+4. Tick which output types you want (cutout / mask / overlay)
+5. Optional: enable **High accuracy** (GrabCut edge refine, adds a fraction of a second per image)
+6. Click **Start batch**
+7. Progress bar and log update in real time
+
+Supported image formats: `.jpg` `.jpeg` `.png` `.bmp` `.tif` `.tiff` `.webp`
+
+#### Switching Language
+
+Click the **EN / 中** button at the top-right to toggle between English and Chinese.
+
+### 📋 System Requirements
+
+- **OS**: Windows 10 / 11 (64-bit) · macOS 11 Big Sur or newer (Apple Silicon, M1/M2/M3/M4)
+- **RAM**: 4 GB or more (8 GB recommended)
+- **Disk**: ~1.5 GB
+- **Acceleration**: Optional GPU on Windows · Apple MPS used automatically on macOS (CPU also works)
+
+---
+
+## 📖 引用 · Citation
+
+如本工具对您的研究有帮助，欢迎引用我们的文章。
+If this tool helps your research, please cite our paper:
+
+> Xie, J., Zhang, Z., Poudel, B., Guo, C., Yu, Y., An, G., ... & Xu, D. (2026). **TOM: An open-source tongue segmentation method with multi-teacher distillation and task-specific data augmentation.** *Expert Systems with Applications*, 131499.
+
+🔗 [View on ScienceDirect](https://www.sciencedirect.com/science/article/pii/S0957417426004124)
+
+## 🏛️ 研发团队 · Developed by
+
+**[Digital Biology Laboratory (DBL)](https://digbio.missouri.edu/)**
+University of Missouri
+
+如本工具对您有帮助，欢迎给我们一个 ⭐ Star 以获取后续更新通知。
+If this tool helps you, a ⭐ star is appreciated — and you'll get notified of future updates.
+
+## 📄 版权 · Copyright
+
+© 2026 Digital Biology Laboratory · University of Missouri

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