https://github.com/gqgs/upscalejs

JavaScript image upscaling using super resolution AI models
https://github.com/gqgs/upscalejs

image nodejs onnxruntime upscale upscaler vue

Last synced: 3 months ago
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JavaScript image upscaling using super resolution AI models

• Host: GitHub
• URL: https://github.com/gqgs/upscalejs
• Owner: gqgs
• Created: 2022-04-03T00:24:48.000Z (almost 3 years ago)
• Default Branch: master
• Last Pushed: 2022-06-19T11:47:49.000Z (over 2 years ago)
• Last Synced: 2024-04-23T10:34:35.145Z (10 months ago)
• Topics: image, nodejs, onnxruntime, upscale, upscaler, vue
• Language: TypeScript
• Homepage: https://gqgs.github.io/upscalejs
• Size: 41.2 MB
• Stars: 19
• Watchers: 1
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md

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README

        
# upscalejs

Image upscaling using super resolution AI models.







## Usage

```ts

import { Upscaler } from "upscalejs"

const upscaler = new Upscaler()

const result = await upscaler.upscale(bitmap)

const canvas = document.createElement("canvas")

canvas.width = result.width

canvas.height = result.height

canvas.getContext("2d")?.putImageData(result, 0, 0)

```

### Node

```js

const fs = require("fs")

const { Upscaler, canvas } = require("upscalejs")

const upscaler = new Upscaler({

  base: "./node_modules/upscalejs/dist/"

})

const upscale = async (input, output) => {

  const img = await canvas.loadImage(input)

  const result = await upscaler.upscale(img)

  const write_stream = fs.createWriteStream(output)

  const upscale_canvas = canvas.createCanvas(result.width, result.height)

  upscale_canvas.getContext("2d").putImageData(result, 0, 0)

  const jpeg_stream = upscale_canvas.createJPEGStream()

  jpeg_stream.pipe(write_stream)

}

upscale("image.jpg", "upscaled.jpg")

```

You will need to copy the models and onnxruntime wasm files to your public folder e.g.:

```ts

const CopyPlugin = require("copy-webpack-plugin");

module.exports = {

  chainWebpack: config => {

    config

      .plugin("copy-webpack-plugin")

      .use(CopyPlugin)

      .tap(() => {

        return [{

          patterns: [

            {

              from: "./node_modules/upscalejs/dist/js/ort-*.wasm",

              to: "js/[name][ext]",

            },

            {

              from: "./node_modules/upscalejs/dist/models/*.onnx",

              to: "models/[name][ext]",

            }

          ],

        }]

      })

   }

}

```

Current available models were trained in anime images and are based on work done in the [Real-CUGAN](https://github.com/bilibili/ailab/tree/main/Real-CUGAN) project.

## Project Setup

```sh

npm install

```

### Compile and Hot-Reload for Development

```sh

npm run dev

```

### Type-Check, Compile and Minify for Production

```sh

npm run build

```

### Lint with [ESLint](https://eslint.org/)

```sh

npm run lint

```

### Test with [Vitest](https://github.com/vitest-dev/vitest)

```sh

npm run test

```