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https://github.com/wykerd/waifu2x-node
Image Super-Resolution in NodeJS using libw2xc from waifu2x-converter-cpp.
https://github.com/wykerd/waifu2x-node
cpp image image-processing node-module node-native-addons nodejs opencv upscale upscaler waifu2x waifu2x-converter-cpp
Last synced: 4 months ago
JSON representation
Image Super-Resolution in NodeJS using libw2xc from waifu2x-converter-cpp.
- Host: GitHub
- URL: https://github.com/wykerd/waifu2x-node
- Owner: Wykerd
- Created: 2020-05-16T22:04:11.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2022-01-28T23:49:11.000Z (about 3 years ago)
- Last Synced: 2024-10-03T08:38:02.327Z (4 months ago)
- Topics: cpp, image, image-processing, node-module, node-native-addons, nodejs, opencv, upscale, upscaler, waifu2x, waifu2x-converter-cpp
- Language: C++
- Size: 153 KB
- Stars: 5
- Watchers: 2
- Forks: 0
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Waifu2x Converter for NodeJS
NodeJS bindings / wrapper for using [libw2xc from waifu2x-converter-cpp](https://github.com/DeadSix27/waifu2x-converter-cpp)
Used to upscale photos or Anime-style art using convolutional neural networks.
# Usage
This module currently only supports GNU/Linux and Windows.
## Prerequisites
This project requires node-gyp to build, make sure it is installed using ```npm install -g node-gyp```
### Windows x64
Make sure you have node-gyp setup correctly. You'll need Visual Studio 2015 or later installed to compile the source. See https://www.npmjs.com/package/node-gyp#on-windows for more info.
Dependencies are installed automatically but require 7z to extract the binaries, make sure it is installed at the default install path `C:\Program Files\7-Zip\7z.exe`
The install scripts should install all dependencies automatically so no additional setup is required.
### Linux
Install the dependencies listed below.
Make sure the you install it in one of the linker's search directories. It should be by default if you use your package manager or follow the build instructions below.
#### OpenCV
Install OpenCV using your distrobution's package manager.
On arch you'll use ```pacman -S opencv```
#### waifu2x-converter-cpp
- AUR (ArchLinux based distros)
- [waifu2x-converter-cpp-git](https://aur.archlinux.org/packages/waifu2x-converter-cpp-git/)
- Fedora
- [waifu2x-converter-cpp](https://apps.fedoraproject.org/packages/waifu2x-converter-cpp)
- Other Linux
- Build from source. See instructions here https://github.com/DeadSix27/waifu2x-converter-cpp/blob/master/BUILDING.md
## Installation
Install using npm
```
npm install waifu2x-node
```
## Synchronous Examples
### Upscaling a file
```typescript
import { W2XCJS, DEFAULT_MODELS_DIR } from 'waifu2x-node';
const converter = new W2XCJS();
const err = converter.loadModels(DEFAULT_MODELS_DIR);
if (!err) {
const conv_err = converter.convertFile("in.png", "out.webp");
if (!err) {
console.log('File converted successfully');
}
}
```
### Upscale a buffer
```typescript
import { W2XCJS, DEFAULT_MODELS_DIR } from 'waifu2x-node';
import fs from 'fs';
const converter = new W2XCJS();
const err = converter.loadModels(DEFAULT_MODELS_DIR);
if (!err) {
const input_buffer = fs.readFileSync("in.png");
const output_buffer = converter.convertBuffer(input_buffer, '.JPG'); // second parameter is the file extension to encode to.
fs.writeFileSync("out.jpg", output_buffer);
}
```
## Asynchronous examples
Asynchronous functions only work on GPU processor types due to instabilities on the CPU
### Upscaling using callbacks
```typescript
import { W2XCJS, DEFAULT_MODELS_DIR } from 'waifu2x-node';
import fs from 'fs';
const converter = new W2XCJS();
const err = converter.loadModels(DEFAULT_MODELS_DIR); // model loading is synchronous
if (!err) {
fs.readFile("in.png", (err, input_buffer) => {
if (err) throw err;
converter.convertBufferAsync(input_buffer, '.WEBP', { /* AsyncOptions */ }, dst_buffer => {
fs.writeFile("out.webp", dst_buffer, err => {
if (err) throw err;
})
})
});
}
```
### Upscaling using promises
The library provides a wrapper class for using promises
```typescript
import { W2XCJS, DEFAULT_MODELS_DIR, W2XCJSPromises } from 'waifu2x-node';
import fs from 'fs';
const promises = new W2XCJSPromises(new W2XCJS());
const err = promises.converter.loadModels(DEFAULT_MODELS_DIR); // model loading is synchronous
if (!err) {
(async () => {
const input_buffer = await fs.promises.readFile("in.png");
const dst_buffer = await promises.convertBuffer(input_buffer, '.WEBP', { /* AsyncOptions */ });
await fs.promises.writeFile("out.webp", dst_buffer);
})();
}
```
### Asynchronous convert options (AsyncOptions)
Abstract of the library source for reference, you could also generate the documentation for more detailed overview.
```typescript
interface AsyncOptions {
// encoding options for destination buffer.
imwrite_params: ImwriteParams;
// denoising options (number value from -1 to 3 where -1 is no denoising)
denoise_level: DenoiseLevel;
// Scale factor.
scale: number;
}
```
```typescript
interface ImwriteParams {
// quality factor for webp and jpeg from 0 to 101 where 101 is lossless.
webp_quality?: number;
jpeg_quality?: number;
// compression factor for png from 0 to 9 where 9 is smallest size and longest time.
png_compression?: number;
}
```
# Documentation
Documentation is generated using TypeDoc, run `npm run docs:build` to build the documentation and `npm run docs:serve` to serve a local copy of the documentation.