We have collection of more than 1 Million open source products ranging from Enterprise product to small libraries in all platforms. We aggregate information from all open source repositories. Search and find the best for your needs. Check out projects section.
imaginary - Fast, simple, stateless HTTP microservice for high-level image processing with first-class support for Docker & Heroku
Fast HTTP microservice written in Go for high-level image processing backed by bimg and libvips. imaginary can be used as private or public HTTP service for massive image processing with first-class support for Docker & Heroku. It's almost dependency-free and only uses net/http native package without additional abstractions for better performance.Supports multiple image operations exposed as a simple HTTP API, with additional optional features such as API token authorization, gzip compression, HTTP traffic throttle strategy and CORS support for web clients.
image image-processing resize-images libvips crop-image microservice docker watermark jpeg png webp gif go-librarylibvips - A fast image processing library with low memory needs.
libvips is a 2D image processing library. Compared to similar libraries, libvips runs quickly and uses little memory. libvips is licensed under the LGPL 2.1+. It has around 300 operations covering arithmetic, histograms, convolutions, morphological operations, frequency filtering, colour, resampling, statistics and others. It supports a large range of numeric formats, from 8-bit int to 128-bit complex. It supports a good range of image formats, including JPEG, TIFF, PNG, WebP, FITS, Matlab, OpenEXR, PDF, SVG, HDR, PPM, CSV, GIF, Analyze, DeepZoom, and OpenSlide. It can also load images via ImageMagick or GraphicsMagick.
libvips python-bindings jpeg openslide imagemagick tiff gif webp graphicsmagick openexrSharp - High performance Node.js image processing
The typical use case for this high speed Node.js module is to convert large images in common formats to smaller, web-friendly JPEG, PNG and WebP images of varying dimensions.Resizing an image is typically 4x-5x faster than using the quickest ImageMagick and GraphicsMagick settings.
webp image-processing jpeg png nodejs tiff svg libvips exif icc image performance crop resize overlay gif dzi thumbnail embed thumbnail-service apiimgproxy - Fast and secure standalone server for resizing and converting remote images
imgproxy is a fast and secure standalone server for resizing and converting remote images. The main principles of imgproxy are simplicity, speed, and security. imgproxy can be used to provide a fast and secure way to replace all the image resizing code of your web application (like calling ImageMagick or GraphicsMagick, or using libraries), while also being able to resize everything on the fly, fast and easy. imgproxy is also indispensable when handling lots of image resizing, especially when images come from a remote source.
image resize-images crop-image microservice docker jpeg png libvipsbimg - Small Go package for fast high-level image processing powered by libvips C library
Small Go package for fast high-level image processing using libvips via C bindings, providing a simple, elegant and fluent programmatic API.bimg was designed to be a small and efficient library supporting a common set of image operations such as crop, resize, rotate, zoom or watermark. It can read JPEG, PNG, WEBP natively, and optionally TIFF, PDF, GIF and SVG formats if libvips@8.3+ is compiled with proper library bindings.
libvips watermark crop-image image processing resize jpeg png webp crop image-processing go-libraryruby-vips - Ruby extension for the libvips image processing library.
This gem provides a Ruby binding for the libvips image processing library. Programs that use ruby-vips don't manipulate images directly, instead they create pipelines of image processing operations building on a source image. When the end of the pipe is connected to a destination, the whole pipeline executes at once, streaming the image in parallel from source to destination a section at a time.
libvips image-processingimage-resizer - On-the-fly image resizing using Node.js and GraphicsMagick. Heroku Ready!
image-resizer is a Node.js application that sits as a custom origin to your CDN and will resize/optimise images on-the-fly. It is Heroku ready, but can also be deployed easily to any cloud provider (has been used with success on AWS). The primary goal for this project was to abstract the need to set image dimensions during the upload and storage phase of images in a modern web application.
image resize node sharp libvips heroku optimizationvips - Go Bindings for Vips (a super fast image processor)
This package is powered by the blazingly fast libvips image processing library, originally created in 1989 at Birkbeck College and currently maintained by JohnCupitt. The typical use case for this high speed package is to convert large images of many formats to smaller, web-friendly JPEG, PNG images of varying dimensions.
vips jpeg imagemagick libvipsmort - Storage and image processing server written in Go
An S3-compatible image processing server written in Go. Still in active development.
image-processing storage docker jpeg png webp resize-images crop-image resize tranform libvips dockerfile s3 images microservice processing thumbnailsnode-imaginary - Minimalist node.js command-line & programmatic API client for imaginary
Minimalist node.js CLI & programmatic stream capable interface for imaginary server.Supports multiple image operations such as resize, crop, zoom, watermark, rotate... and both local and remote URL based image source processing, and additionally provides a simple balancing feature to use multiple imaginary servers.
imaginary image-processing resize resize-images crop watermark-image image-manipulation client-library image convesion processing vips imagemagick convert resolution images rotate flip libvips enlarge watermarklua-vips - Lua binding for the libvips image processing library
This is a Lua binding for the libvips image processing library. libvips is a fast image processing library with low memory needs. lua-vips uses ffi and needs luajit 2.0 or later. The libvips documentation includes a handy searchable table of every operation in libvips. This is a good place to check if it supports some feature you need. Read on to see how to call libvips operations.
libvips vips image-processing-libraryphp-vips - php binding for libvips
php-vips is a binding for libvips for PHP 7. libvips is fast and needs little memory. The vips-php-bench repository tests php-vips against imagick and gd. On that test, and on my laptop, php-vips is around four times faster than imagick and needs 10 times less memory.
libvips php-extension php-bindingsdragonfly_libvips - Dragonfly analysers and processors for libvips image processing library.
libvips is a 2D image processing library. Compared to similar libraries, libvips runs quickly and uses little memory. libvips is licensed under the LGPL 2.1+. If you run into trouble installing libvips with Ruby introspection on Linux, follow the build steps here. Please note the importance of gobject-introspection and libgirepository1.0-dev plus the export GI_TYPELIB_PATH=/usr/local/lib/girepository-1.0/ and ldconfig.
dragonfly libvipslibvips-lambda - libvips Executable for AWS Lambda
libvips is a 2D image processing library. Compared to similar libraries, libvips runs quickly and uses little memory. libvips is licensed under the LGPL 2.1+. We use libvips for image manipulation, primarily tiling image pyramids for blueprints and other construction industry artifacts, which results in about seven thousand vips executions a day for the past several years. We have long wanted to move that processing to AWS Lambda, and were hung up on getting a vips executable into AWS.
aws-lambda libvips vips-executions dockergulp-sharp - Gulp plugin to resize image using sharp (libvips binding for nodejs)
Because of other occupation, I can't maintain it anymore. If you find this project usefull, please fork it. Please note that new issues / pr messages will be ignored. Thanks.
gulp gulp-sharp gulpplugin sharp jpeg png webp tiff resize thumbnail sharpen crop embed libvips vips fast buffer streamnode-vips - Experiment with a libvips binding for node using ffi
It's mostly complete, it seems stable, and it passes the tests suite with no errors or leaks. It can reliably thumbnail 10,000 jpeg images in constant memory and without falling over. Probably. Most operations are instant -- it only makes sense to use async for things which will trigger a pixel loop.
ffi libvips vipsnet-vips - Mono/.NET bindings for libvips
This NuGet package provides a Mono/.NET binding for the libvips image processing library. This binding passes the vips test suite cleanly with no leaks on Windows, macOS and Linux.
libvips image-processing pinvoke bindings monodreamcanvas - DeepDream experiment
Rest of the dependencies are listed in package.json and will be installed automatically. Run these in separate terminal windows for best results.
tensorflow tensorflow-experiments wsrpc nodejs libvips cairoretinal - 🏙 Retinal is a Serverless AWS Lambda service for resizing images on-demand or event-triggered
Serverless Framework-based AWS Lambda function triggered by S3 events to resize images with the excellent Sharp module. By using the Sharp module (which uses the libvips library), image processing can be 3x-5x faster than using ImageMagick, thus reducing the time your function spends running, which can potentially dramatically decrease your lambda function's cost. The function's behaviour can be controlled entirely with configuration. A tool to take images uploaded to an S3 bucket and produce one or more images of varying sizes, optimizations and other operations all controlled from a simple configuration file. It does this by creating an AWS Lambda function with the help of the Serverless Framework.
aws-lambda serverless-framework libvips sharp-library resized-images serverless-functions sharp serverless aws ava es2017 aws-s3 nodejs image-processing lqip sqip on-the-fly image resize optimize
We have large collection of open source products. Follow the tags from
Tag Cloud >>
Open source products are scattered around the web. Please provide information
about the open source projects you own / you use.
Add Projects.
