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Image

Image processing library.

This library support encode/decode these formats:

Format Input Output
RawPixels RGBA 8 bits pixels
JPEG Baseline and progressive Baseline JPEG
PNG All supported color types Same as decoding
BMP Rgb8, Rgba8, Gray8, GrayA8
ICO
TIFF Baseline(no fax support) + LZW + PackBits Rgb8, Rgba8, Gray8
WebP No
AVIF No
PNM PBM, PGM, PPM, standard PAM
DDS DXT1, DXT3, DXT5 No
TGA Rgb8, Rgba8, Bgr8, Bgra8, Gray8, GrayA8
OpenEXR Rgb32F, Rgba32F (no dwa compression) Rgb32F, Rgba32F (no dwa compression)
farbfeld

See index.d.ts for API reference.

CI

Support matrix

node10 node12 node14 node16 node18
Windows x64
Windows x32
macOS x64
macOS arm64 (m chips)
Linux x64 gnu
Linux x64 musl
Linux arm gnu
Linux arm64 gnu
Linux arm64 musl
Android arm64
Android armv7
FreeBSD x64

Performance

System info

OS: macOS 12.3.1 21E258 arm64
Host: MacBookPro18,2
Kernel: 21.4.0
Shell: zsh 5.8
CPU: Apple M1 Max
GPU: Apple M1 Max
Memory: 9539MiB / 65536MiB
node bench/bench.mjs

@napi-rs/image 202 ops/s
sharp 169 ops/s
In webp suite, fastest is @napi-rs/image
@napi-rs/image 26 ops/s
sharp 24 ops/s
In avif suite, fastest is @napi-rs/image
UV_THREADPOOL_SIZE=10 node bench/bench.mjs

@napi-rs/image 431 ops/s
sharp 238 ops/s
In webp suite, fastest is @napi-rs/image
@napi-rs/image 36 ops/s
sharp 32 ops/s
In avif suite, fastest is @napi-rs/image

@napi-rs/image

See Full documentation for @napi-rs/image

Example

You can clone this repo and run the following command to taste the example below:

  • yarn install
  • node example.mjs
Optimization Raw Raw Size Optimized Size
losslessCompressPng()
Lossless
CC-BY-SA 3.0 by Niabot 888K 736K
pngQuantize({ maxQuality: 75 })
Lossy
CC-BY-SA 3.0 by Niabot 888K 248K
compressJpeg()
Lossless
192K 184K
compressJpeg(75)
Lossy
192K 104K
new Transformer(PNG).webpLossless()
Lossless
CC-BY-SA 3.0 by Niabot 888K 588K
new Transformer(PNG).webp(75)
Lossy
CC-BY-SA 3.0 by Niabot 888K 64K
Transformer(PNG).avif({ quality: 100 })
Lossless
CC-BY-SA 3.0 by Niabot 888K 536K
new Transformer(PNG).avif({ quality: 75, chromaSubsampling: ChromaSubsampling.Yuv420 })
Lossy
CC-BY-SA 3.0 by Niabot 888K 64K
import { readFileSync, writeFileSync } from 'fs'

import {
  losslessCompressPng,
  compressJpeg,
  pngQuantize,
  Transformer,
  ResizeFilterType,
  ChromaSubsampling,
} from '@napi-rs/image'
import chalk from 'chalk'

const PNG = readFileSync('./un-optimized.png')
const JPEG = readFileSync('./un-optimized.jpg')
// https://github.com/ianare/exif-samples/blob/master/jpg/orientation/portrait_5.jpg
const WITH_EXIF = readFileSync('./with-exif.jpg')

writeFileSync('optimized-lossless.png', await losslessCompressPng(PNG))

console.info(chalk.green('Lossless compression png done'))

writeFileSync(
  'optimized-lossy.png',
  await pngQuantize(PNG, {
    maxQuality: 75,
  }),
)

console.info(chalk.green('Lossy compression png done'))

writeFileSync('optimized-lossless.jpg', await compressJpeg(readFileSync('./un-optimized.jpg')))

console.info(chalk.green('Lossless compression jpeg done'))

writeFileSync('optimized-lossy.jpg', await compressJpeg(readFileSync('./un-optimized.jpg'), { quality: 75 }))

console.info(chalk.green('Lossy compression jpeg done'))

writeFileSync('optimized-lossless.webp', await new Transformer(PNG).webpLossless())

console.info(chalk.green('Lossless encoding webp from PNG done'))

writeFileSync('optimized-lossy-png.webp', await new Transformer(PNG).webp(75))

console.info(chalk.green('Encoding webp from PNG done'))

writeFileSync('optimized-lossless-png.avif', await new Transformer(PNG).avif({ quality: 100 }))

console.info(chalk.green('Lossless encoding avif from PNG done'))

writeFileSync(
  'optimized-lossy-png.avif',
  await new Transformer(PNG).avif({ quality: 75, chromaSubsampling: ChromaSubsampling.Yuv420 }),
)

console.info(chalk.green('Lossy encoding avif from PNG done'))

writeFileSync(
  'output-exif.webp',
  await new Transformer(WITH_EXIF)
    .rotate()
    .resize(450 / 2, null, ResizeFilterType.Lanczos3)
    .webp(75),
)

console.info(chalk.green('Encoding webp from JPEG with EXIF done'))
Description
Image processing library.
Readme MIT 66 MiB
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