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---
license: apache-2.0
language: en
library_name: tensorflowjs
tags:
- real-cugan
- super-resolution
- image-upscaling
- anime
- tensorflowjs
- image-to-image
---
# Real-CUGAN Models for TensorFlow.js
[](https://huggingface.co/shammisw/real-cugan-tensorflowjs)
[](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.
---
## 🚀 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 **Apache-2.0**.
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.
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