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GraphicsMagick
ByGraphicsMagickGraphicsMagick

GraphicsMagick

#10in Image Optimization
Discussions0
Followers65
OverviewDiscussionsAdoptionAlternativesIntegrations
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What is GraphicsMagick?

GraphicsMagick is the swiss army knife of image processing. Comprised of 267K physical lines (according to David A. Wheeler's SLOCCount) of source code in the base package (or 1,225K including 3rd party libraries) it provides a robust and efficient collection of tools and libraries which support reading, writing, and manipulating an image in over 88 major formats including important formats like DPX, GIF, JPEG, JPEG-2000, PNG, PDF, PNM, and TIFF.

GraphicsMagick is a tool in the Image Optimization category of a tech stack.

GraphicsMagick Pros & Cons

Pros of GraphicsMagick

  • ✓Used by flickr and etsy

Cons of GraphicsMagick

No cons listed yet.

GraphicsMagick Alternatives & Comparisons

What are some alternatives to GraphicsMagick?

OpenCV

OpenCV

OpenCV was designed for computational efficiency and with a strong focus on real-time applications. Written in optimized C/C++, the library can take advantage of multi-core processing. Enabled with OpenCL, it can take advantage of the hardware acceleration of the underlying heterogeneous compute platform.

Pillow

Pillow

It adds image processing capabilities to your Python interpreter. It provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities.

Cloudinary

Cloudinary

Cloudinary is a cloud-based service that streamlines websites and mobile applications' entire image and video management needs - uploads, storage, administration, manipulations, and delivery.

FFMPEG

FFMPEG

The universal multimedia toolkit.

scikit-image

scikit-image

scikit-image is a collection of algorithms for image processing.

imgix

imgix

imgix is the leading platform for end-to-end visual media processing. With robust APIs, SDKs, and integrations, imgix empowers developers to optimize, transform, manage, and deliver images and videos at scale through simple URL parameters.

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