sharp vs jimp vs gm vs imagemagick
Image Processing Libraries for Node.js Comparison
1 Year
sharpjimpgmimagemagickSimilar Packages:
What's Image Processing Libraries for Node.js?

Image processing libraries in Node.js provide developers with tools to manipulate and transform images efficiently. These libraries can handle various tasks such as resizing, cropping, filtering, and converting image formats. They are essential for applications that require dynamic image generation, optimization, or manipulation, making them invaluable in web development, especially for e-commerce, social media, and content management systems.

Package Weekly Downloads Trend
Github Stars Ranking
Stat Detail
Package
Downloads
Stars
Size
Issues
Publish
License
sharp11,179,63630,215522 kB1164 days agoApache-2.0
jimp1,486,075-4.03 MB-7 months agoMIT
gm448,6976,975121 kB368a month agoMIT
imagemagick26,7781,817-8212 years ago-
Feature Comparison: sharp vs jimp vs gm vs imagemagick

Performance

  • sharp:

    Sharp is known for its exceptional performance, leveraging native C++ bindings for fast image processing. It is optimized for speed and memory usage, making it the best choice for high-performance applications.

  • jimp:

    Jimp is a pure JavaScript library, making it easy to use but not as fast as native solutions. It is suitable for smaller images and simpler tasks but may struggle with performance on larger images or heavy processing.

  • gm:

    gm is built on GraphicsMagick, which is designed for high performance in batch processing. However, it may not be as fast as sharp for individual image transformations due to its reliance on external binaries.

  • imagemagick:

    ImageMagick is powerful but can be slower compared to other libraries, especially for large images or complex operations. Its extensive feature set can lead to performance overhead if not optimized properly.

Ease of Use

  • sharp:

    Sharp provides a straightforward API that is easy to use, especially for those familiar with JavaScript. Its clear documentation and examples make it accessible for developers of all skill levels.

  • jimp:

    Jimp is designed to be user-friendly, with a simple API that is easy to understand. It is a great choice for developers who want to quickly implement image processing without dealing with complex configurations.

  • gm:

    gm has a command-line interface that can be less intuitive for beginners. However, it offers extensive documentation and examples, which can help users get accustomed to its syntax and capabilities.

  • imagemagick:

    ImageMagick also has a steep learning curve due to its command-line nature and extensive options. While powerful, it may require more time to master for new users.

Supported Formats

  • sharp:

    Sharp supports modern image formats such as WebP, AVIF, JPEG, PNG, and TIFF. Its ability to handle newer formats makes it a strong choice for web applications aiming for performance and quality.

  • jimp:

    Jimp supports common formats like JPEG, PNG, and BMP. However, it lacks support for some advanced formats, which may limit its use in certain scenarios.

  • gm:

    gm supports a wide range of image formats, including JPEG, PNG, GIF, and TIFF. It is versatile and can handle many common image types, making it suitable for various applications.

  • imagemagick:

    ImageMagick supports an extensive array of image formats, often more than any other library. This makes it ideal for applications that need to work with diverse image types.

Image Manipulation Features

  • sharp:

    Sharp excels in image manipulation, offering a rich set of features including resizing, rotation, and format conversion. Its performance and efficiency make it ideal for real-time image processing.

  • jimp:

    Jimp provides basic image manipulation features, such as resizing, cropping, and filtering. While it is sufficient for simple tasks, it may lack advanced features found in more robust libraries.

  • gm:

    gm offers a comprehensive set of image manipulation features, including resizing, cropping, rotating, and applying filters. It is suitable for complex image processing tasks.

  • imagemagick:

    ImageMagick is renowned for its extensive image manipulation capabilities, allowing for intricate transformations, effects, and compositing. It is highly customizable but may require more effort to implement specific features.

Community and Support

  • sharp:

    Sharp has a growing community and excellent documentation, making it easy to get support. It is widely used in production environments, which contributes to a wealth of shared knowledge and resources.

  • jimp:

    Jimp has a smaller community compared to others, but it is actively maintained. Its simplicity makes it easy to find support for basic tasks, though advanced issues may be less documented.

  • gm:

    gm has a dedicated community and good documentation, but it may not be as widely used as some other libraries, which can affect the availability of community support.

  • imagemagick:

    ImageMagick has a large and active community, with extensive documentation and resources available. This makes it easier to find help and examples for complex tasks.

How to Choose: sharp vs jimp vs gm vs imagemagick
  • sharp:

    Choose sharp if performance is a priority, as it is optimized for speed and memory efficiency. It is particularly effective for handling large images and supports modern image formats, making it a great choice for web applications.

  • jimp:

    Select jimp if you prefer a pure JavaScript solution that is easy to use and lightweight. It is ideal for simple image processing tasks and does not require native dependencies, making it suitable for serverless environments.

  • gm:

    Choose gm (GraphicsMagick) if you need a comprehensive set of image processing features and are comfortable with a command-line interface. It is particularly useful for batch processing and supports a wide range of image formats.

  • imagemagick:

    Opt for imagemagick if you require extensive image manipulation capabilities and need to work with a variety of formats. It is highly versatile and suitable for complex image processing tasks, but may have a steeper learning curve due to its extensive options.

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.