Hugging Face's logo

Xenova
/
4x_APISR_GRL_GAN_generator-onnx

Image-to-Image
Transformers.js
ONNX
swin2sr
apisr
super-resolution
Model card Files Community
1
4x_APISR_GRL_GAN_generator-onnx / README.md
Xenova's picture
Xenova HF staff
Update README.md
70bfbf9 verified
preview code
|
raw
history blame contribute delete
1.94 kB
metadata
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 JavaScript library from NPM using:

npm i @xenova/transformers

Example: Upscale an image with Xenova/4x_APISR_GRL_GAN_generator-onnx.

import { pipeline } from '@xenova/transformers';

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

// 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');
See example output

Input image:

image/png

Output image:

image/png

image/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 and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).