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README.md

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+# Real-CUGAN Models for TensorFlow.js
+
+[![Hugging Face Repo](https://img.shields.io/badge/🤗%20Hugging%20Face-Repo-yellow)](https://huggingface.co/shammisw/real-cugan-tensorflowjs)
+[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
+
+This repository provides pre-converted models of **Real-CUGAN** (Real-World-Oriented Cascaded U-Net for Anime Image Super-Resolution) in the **TensorFlow.js GraphModel format**, ready for use in web browsers and Node.js environments.
+
+These models are optimized for upscaling anime-style images and illustrations with high fidelity, speed, and reduced noise.
+
+## ✨ Features
+
+* **High-Quality Anime Upscaling:** Specifically trained for cartoons and anime, preserving sharp lines and details.
+* **Web Ready:** Run directly in the browser with TensorFlow.js for client-side image processing.
+* **Multiple Scales & Models:** Includes various models for different upscaling factors and noise reduction levels.
+* **Lightweight & Fast:** CUGAN is designed to be more efficient than many larger GAN-based upscalers.
+
 ---
-license: apache-2.0
+
+## 🚀 Usage Example
+
+To use these models, you will need to have TensorFlow.js set up in your project.
+
+```bash
+# Using npm
+npm install @tensorflow/tfjs
+
+# Using yarn
+yarn add @tensorflow/tfjs
+```
+
+Here is a basic example of how to load and run a model in JavaScript:
+
+```javascript
+import * as tf from '@tensorflow/tfjs';
+
+// The URL to the model.json file in this repository
+const MODEL_URL = '[https://huggingface.co/shammisw/real-cugan-tensorflowjs/resolve/main/real-cugan-models/realcugan/4x-conservative-64/model.json](https://huggingface.co/shammisw/real-cugan-tensorflowjs/resolve/main/real-cugan-models/realcugan/4x-conservative-64/model.json)';
+
+async function upscaleImage(imageElement) {
+  try {
+    // 1. Load the model
+    console.log('Loading model...');
+    const model = await tf.loadGraphModel(MODEL_URL);
+    console.log('Model loaded.');
+
+    // 2. Prepare the input tensor from an HTMLImageElement
+    // Models are trained on float32 tensors, normalized to the [0, 1] range.
+    const inputTensor = tf.browser.fromPixels(imageElement)
+      .toFloat()
+      .div(255.0)
+      .expandDims(0); // Add batch dimension: [h, w, c] -> [1, h, w, c]
+
+    // 3. Run inference
+    console.log('Running inference...');
+    const outputTensor = model.execute(inputTensor);
+
+    // 4. Process the output and display it on a canvas
+    const outputCanvas = document.getElementById('output-canvas');
+    await tf.browser.toPixels(outputTensor.squeeze(), outputCanvas);
+    console.log('Upscaling complete!');
+
+    // 5. Clean up tensors
+    tf.dispose([inputTensor, outputTensor]);
+
+  } catch (error) {
+    console.error('Failed to upscale image:', error);
+  }
+}
+
+// Find your input image element and pass it to the function
+const myImage = document.getElementById('my-input-image');
+upscaleImage(myImage);
+```
+
 ---
+
+## 📂 Available Models
+
+This repository contains the following converted models. The number in the model name (e.g., `-64`) refers to the tile size used during conversion, which can affect performance and memory usage.
+
+| Model Type       | Scale | Denoise Level | Path                                               |
+| :--------------- | :---: | :-----------: | :------------------------------------------------- |
+| **Conservative** |  2x   |       -       | `real-cugan-models/realcugan/2x-conservative-64/`  |
+| **Conservative** |  4x   |       -       | `real-cugan-models/realcugan/4x-conservative-64/`  |
+| *More models can be added here as they are converted.* |       |               |                                                    |
+
+---
+
+## 🙏 Acknowledgements & Credits
+
+This repository only contains the converted models. All credit for the research and training of the original models goes to their respective creators.
+
+* **Original Real-CUGAN Models:** The foundational research and PyTorch models were developed by **Bilibili AI Lab**. Their incredible work made this possible.
+    * **GitHub Repository:** [bilibili/ailab/Real-CUGAN](https://github.com/bilibili/ailab/tree/main/Real-CUGAN)
+
+* **TensorFlow.js Conversion:** The methodology for converting these models to TensorFlow.js format was adapted from the excellent **[web-realesrgan](https://github.com/ts-ai/web-realesrgan)** project, which provided a clear path for on-device super-resolution in the browser.
+
+---
+
+## 📜 License
+
+The code and configuration in this repository are released under the **MIT License**.
+
+The original Real-CUGAN models are subject to their own license terms as specified in the [official Real-CUGAN repository](https://github.com/bilibili/ailab/tree/main/Real-CUGAN). Please ensure compliance with their license if you use these models.