Update README.md

README.md

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 ---
-license: gpl-3.0
+tags:
+- coreml
+- image-to-image
+- deepmosaics
+- computer-vision
+- vision
+license: mit
 ---
+
+# DeepMosaics - CoreML Version
+
+This repository contains the Apple CoreML conversions of the pre-trained models from the original [DeepMosaics](https://github.com/HypoX64/DeepMosaics) project by HypoX64.
+
+DeepMosaics is a powerful tool for automatic video and image processing. By converting these models to **CoreML**, iOS and macOS developers can easily integrate these capabilities directly into their Apple ecosystem applications, taking full advantage of on-device hardware acceleration (Apple Neural Engine and GPU).
+
+## 📦 Available Models
+
+
+* `add_mosaic.mlmodel` - 用於為圖片/影片添加馬賽克
+* `clean_mosaic_HD.mlmodel` - 用於去除馬賽克 (HD 高清版)
+* `clean_mosaic_video.mlmodel` - 用於去除影片中的馬賽克
+
+## 🚀 How to Use (Swift)
+
+1. Download the desired `.mlmodel` or `.mlpackage` file from the **[Files and versions](https://huggingface.co/)** tab.
+2. Drag and drop the file into your **Xcode** project.
+3. Xcode will automatically generate the Swift class for the model.
+4. Use it in your code:
+
+```swift
+import CoreML
+import Vision
+
+// 1. 初始化模型 (請替換成你的模型名稱)
+let model = try! clean_mosaic_HD(configuration: MLModelConfiguration())
+
+// 2. 準備輸入 (請根據你的模型實際的輸入規格修改)
+// 例如，如果模型吃的是 CVPixelBuffer：
+// let input = clean_mosaic_HDInput(inputImage: pixelBuffer)
+
+// 3. 執行推論
+// let output = try! model.prediction(input: input)
+
+// 4. 取得結果
+// let resultImage = output.outputImage
+```
+
+> **Note:** Please refer to Xcode's CoreML model inspector to see the exact expected input and output shapes (e.g., Image size or MultiArray dimensions).
+
+## ⚖️ Acknowledgements & License
+
+- Original Project: [HypoX64/DeepMosaics](https://github.com/HypoX64/DeepMosaics)
+- All credit for the original architecture and pre-trained weights goes to the original authors.
+- The models are provided under the same license as the original project.