Skip to content

Make your sever-side Jimp code run 10x faster!

License

MIT and 2 other licenses found

Licenses found

MIT
LICENSE
MIT
IMAGEJS_LICENSE
MIT
ORIGINAL_JIMP_LICENSE
Notifications You must be signed in to change notification settings

jimp-dev/jimp-native

Repository files navigation

Jimp Native

Make your sever-side Jimp code run 10x faster!

Jimp-native is a fast C++ re-implementation of Jimp

Installation

Run npm install jimp-native in your existing project and import Jimp from 'jimp-native'. Jimp native aims to be a drop-in replacement for Jimp. If your code is already working with Jimp it should also work with Jimp native. If you need even more performance, check out Multithreading

Multithreading

It's highly recommended to use the asynchronous version of an image operation where possible.

Depending on how you call Jimp native methods, calls will be either singlethreaded or multithreaded. There's two ways to have the library run in multithreaded mode for a given operation:

  • This library ships an Async version of each method (e.g. resize becomes resizeAsync) these methods return a promise and also cause said operation to run on another thread.
  • If you provide a callback to any covered image operation, that method will run on another thread.

Documentation

See Jimp's documentation, this library should function the same way. The only difference you'll need to keep in mind is that any Async version of a call returns a promise and does not expect a callback function.

Accuracy

Jimp native aims to be visually indistinguishable from Jimp. Tests are usually kept to a ∓ 0.392% tolerance for each colour component of a pixel. There are cases where the tolerances are set higher, notably blur and some resize algorithms. Reasoning for this usually comes down to speed benefits of using another algorithm or using integer arithmetic over JavaScript doubles. In any case, unless you need 100% accuracy on a binary level, using this library should be fine output-wise.

Coverage

The following Jimp plugins/functions have been optimized with this library:

  • composite ✅
  • blit ✅
  • blur ✅
  • circle ✅
  • colour 🟨
    • brightness ✅
    • contrast ✅
    • posterize ✅
    • grayscale/greyscale ✅
    • opacity ✅
    • sepia ✅
    • fade ✅
    • convolution ✅
    • opaque ✅
    • pixelate ✅
    • convolute ✅
    • colour/color ⛔
  • contain 🟨 (uses resize internally so it's covered)
  • cover 🟨 (crop and resize internally so it's covered)
  • crop ✅
    • crop ✅
    • autocrop ✅
  • displace ⛔
  • dither ✅
    • dither16 ✅
    • dither565 ✅
  • fisheye ⛔
  • gaussian ⛔ (can be done by using convolution for now, or just using blur if a true gaussian blur isn't required)
  • invert ✅
  • mask ✅
  • normalize ⛔
  • print 🟨 (uses blit internally so it's covered)
  • resize ✅
  • rotate ✅
  • scale 🟨 (uses resize internally so it's covered)
  • shadow ⛔
  • threshold ⛔

Performance

The following numbers are some samples from a benchmark on a Core i9-13900K using a 512x512 image. You can find the benchmark code and all results with differing image sizes in the benchmark folder.

Singlethreaded

Operations using the synchronous API

Operation avg. time Jimp avg. time Jimp native
Gaussian blur convolution 149.08ms 22.42ms
Rotate 90deg 11.25ms 1.77ms
Crop 3.26ms 180.84μs
Default resize 2x 17.95ms 15.40ms
Bicubic resize 2x 59.44ms 18.19ms
Nearest neighbour resize 2x 18.04ms 1.55ms

Multithreaded

Operations using the callback/async API (32 calls launched at the same time). Imagine a busy web server handling tons of requests at once.

Only jimp native is able to use multiple threads out of the box, so note that while the benchmark runs the same code on both implementations, only jimp native is actually multithreading in these examples. In other words, the more cores your CPU has the more drastic the improvement.

Operation time taken Jimp time taken Jimp native
Gaussian blur convolution 4.73sec 56.52ms
Rotate 90deg 401.64ms 14.73ms
Crop 105.03ms 1.90ms
Default resize 2x 589.60ms 49.05ms

// TODO

Here are some things I'd like to look into doing with this project:

  • Implement remaining Jimp plugins / functions
  • Handle image decoding in C++
  • Build WASM version
  • Improve the testing harness and benchmarking tool

Licensing

Most C++ optimized functions are based on their JavaScript equivalents in Jimp. Jimp and Jimp native are both available under the MIT license. For the original license, see ORIGINAL_JIMP_LICENSE, for the license that applies to this port, see LICENSE.

Jimp also contains portions of source code from other projects. C++ ports of this code will be marked with licensing info where applicable. External projects that have been partially ported to work with Jimp native include:

About

Make your sever-side Jimp code run 10x faster!

Resources

License

MIT and 2 other licenses found

Licenses found

MIT
LICENSE
MIT
IMAGEJS_LICENSE
MIT
ORIGINAL_JIMP_LICENSE

Stars

Watchers

Forks

Packages

No packages published