Which is Better Image Optimization Libraries?
sharp vs imagemin-pngquant vs imagemin-mozjpeg vs imagemin-jpegtran vs imagemin-webp
1 Year
sharpimagemin-pngquantimagemin-mozjpegimagemin-jpegtranimagemin-webpSimilar Packages:
What's Image Optimization Libraries?

These libraries are designed to optimize images for web use, reducing file sizes while maintaining quality. They support various formats and provide different optimization techniques, making them essential tools for web developers aiming to improve site performance and load times. By utilizing these packages, developers can ensure that images are delivered efficiently, enhancing user experience and reducing bandwidth costs.

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sharp6,155,39829,009503 kB1062 months agoApache-2.0
imagemin-pngquant375,2913167.28 kB155 months agoMIT
imagemin-mozjpeg356,7122517.29 kB243 years agoMIT
imagemin-jpegtran243,7281194.07 kB811 days agoMIT
imagemin-webp186,6294966.18 kB202 years agoMIT
Feature Comparison: sharp vs imagemin-pngquant vs imagemin-mozjpeg vs imagemin-jpegtran vs imagemin-webp

Compression Type

  • sharp: Supports various compression techniques, including lossy and lossless, and allows for extensive image manipulation.
  • imagemin-pngquant: Utilizes lossy compression specifically for PNG images, allowing for significant size reduction with minimal quality loss.
  • imagemin-mozjpeg: Offers both lossy and lossless compression options, with advanced features for optimizing JPEG images.
  • imagemin-jpegtran: Lossless compression for JPEG images, ensuring no quality degradation while reducing file size.
  • imagemin-webp: Supports lossy and lossless compression for WebP images, providing excellent quality at reduced file sizes.

Format Support

  • sharp: Supports multiple formats including JPEG, PNG, WebP, TIFF, and more, making it versatile for various image processing needs.
  • imagemin-pngquant: Optimizes PNG images, making it the go-to choice for this format.
  • imagemin-mozjpeg: Primarily targets JPEG images but offers better handling of progressive JPEGs.
  • imagemin-jpegtran: Specifically designed for JPEG images, focusing on optimizing this format.
  • imagemin-webp: Converts and optimizes images to the WebP format, which is gaining popularity for web use.

Performance

  • sharp: Extremely fast and efficient, capable of processing large batches of images in real-time.
  • imagemin-pngquant: Optimizes PNG images quickly, but lossy compression may introduce slight quality changes.
  • imagemin-mozjpeg: Provides faster compression with better quality at lower file sizes compared to standard JPEG compression.
  • imagemin-jpegtran: Efficient and fast for lossless JPEG compression, but may not be as fast as lossy alternatives.
  • imagemin-webp: Highly efficient in compressing images, often resulting in smaller file sizes compared to JPEG and PNG.

Ease of Use

  • sharp: Comprehensive API with extensive documentation, allowing for complex image processing tasks.
  • imagemin-pngquant: Easy to use with minimal setup required for PNG optimization.
  • imagemin-mozjpeg: User-friendly with straightforward configuration options for advanced JPEG optimization.
  • imagemin-jpegtran: Simple API, easy to integrate into existing projects for JPEG optimization.
  • imagemin-webp: Straightforward API for converting images to WebP format, making it accessible for developers.

Use Cases

  • sharp: Great for dynamic image processing scenarios, such as generating thumbnails or resizing images on-the-fly.
  • imagemin-pngquant: Perfect for projects that rely heavily on PNG images, such as graphic-heavy websites and applications.
  • imagemin-mozjpeg: Ideal for applications that require high-quality JPEG images with optimized file sizes, such as e-commerce sites.
  • imagemin-jpegtran: Best suited for websites that prioritize image quality and need to maintain original JPEG fidelity.
  • imagemin-webp: Recommended for modern web applications aiming for optimal performance with reduced image sizes.
How to Choose: sharp vs imagemin-pngquant vs imagemin-mozjpeg vs imagemin-jpegtran vs imagemin-webp
  • sharp: Choose sharp if you need a high-performance image processing library that supports a wide range of formats and offers powerful features like resizing, cropping, and format conversion. It's ideal for applications requiring real-time image manipulation and processing.
  • imagemin-pngquant: Select imagemin-pngquant if your focus is on optimizing PNG images. This package uses lossy compression to significantly reduce file sizes while maintaining acceptable quality. It's perfect for projects that heavily utilize PNG images and need to optimize them for faster loading times.
  • imagemin-mozjpeg: Opt for imagemin-mozjpeg when you require advanced JPEG compression features, including support for progressive JPEGs. This package is suitable for scenarios where you want to achieve the best possible balance between image quality and file size, especially for web applications that prioritize loading speed.
  • imagemin-jpegtran: Choose imagemin-jpegtran if you need a simple, lossless JPEG compression tool that maintains the original quality of images. It's ideal for projects where preserving image fidelity is crucial and where you want to minimize file size without any quality loss.
  • imagemin-webp: Use imagemin-webp when you want to convert images to the WebP format, which provides superior compression and quality characteristics compared to JPEG and PNG. This is particularly beneficial for modern web applications aiming for high performance and reduced image sizes across various browsers.
README for sharp

sharp

sharp logo

The typical use case for this high speed Node-API module is to convert large images in common formats to smaller, web-friendly JPEG, PNG, WebP, GIF and AVIF images of varying dimensions.

It can be used with all JavaScript runtimes that provide support for Node-API v9, including Node.js (^18.17.0 or >= 20.3.0), Deno and Bun.

Resizing an image is typically 4x-5x faster than using the quickest ImageMagick and GraphicsMagick settings due to its use of libvips.

Colour spaces, embedded ICC profiles and alpha transparency channels are all handled correctly. Lanczos resampling ensures quality is not sacrificed for speed.

As well as image resizing, operations such as rotation, extraction, compositing and gamma correction are available.

Most modern macOS, Windows and Linux systems do not require any additional install or runtime dependencies.

Documentation

Visit sharp.pixelplumbing.com for complete installation instructions, API documentation, benchmark tests and changelog.

Examples

npm install sharp
const sharp = require('sharp');

Callback

sharp(inputBuffer)
  .resize(320, 240)
  .toFile('output.webp', (err, info) => { ... });

Promise

sharp('input.jpg')
  .rotate()
  .resize(200)
  .jpeg({ mozjpeg: true })
  .toBuffer()
  .then( data => { ... })
  .catch( err => { ... });

Async/await

const semiTransparentRedPng = await sharp({
  create: {
    width: 48,
    height: 48,
    channels: 4,
    background: { r: 255, g: 0, b: 0, alpha: 0.5 }
  }
})
  .png()
  .toBuffer();

Stream

const roundedCorners = Buffer.from(
  '<svg><rect x="0" y="0" width="200" height="200" rx="50" ry="50"/></svg>'
);

const roundedCornerResizer =
  sharp()
    .resize(200, 200)
    .composite([{
      input: roundedCorners,
      blend: 'dest-in'
    }])
    .png();

readableStream
  .pipe(roundedCornerResizer)
  .pipe(writableStream);

Contributing

A guide for contributors covers reporting bugs, requesting features and submitting code changes.

Licensing

Copyright 2013 Lovell Fuller and others.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.