README.md

---
license: gpl-3.0
library_name: transformers.js
tags:
- apisr
- super-resolution
pipeline_tag: image-to-image
---

https://github.com/Kiteretsu77/APISR with ONNX weights to be compatible with Transformers.js.


## Usage (Transformers.js)

If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@huggingface/transformers) using:
```bash
npm i @huggingface/transformers
```

**Example:** Upscale an image with `Xenova/4x_APISR_GRL_GAN_generator-onnx`.
```js
import { pipeline } from '@huggingface/transformers';

// Create image-to-image pipeline
const upscaler = await pipeline('image-to-image', 'Xenova/4x_APISR_GRL_GAN_generator-onnx', {
    dtype: "fp32",
});

// Upscale an image
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/anime.png';
const output = await upscaler(url);
// RawImage {
//   data: Uint8Array(16588800) [ ... ],
//   width: 2560,
//   height: 1920,
//   channels: 3
// }

// (Optional) Save the upscaled image
output.save('upscaled.png');
```

<details>
  <summary>See example output</summary>

  Input image:

  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/w2bnLTYnxxNjX-amzYq6A.png)
  
  Output image:
  
  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/8sMM1ZGSuPfujECIcM8rY.png)

</details>

![image/gif](https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/_KGxxVF1gmwnYV5m6Tsf2.gif)

---

Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using [🤗 Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).