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  1. Stackups
  2. Application & Data
  3. Image Optimization
  4. Image Processing And Management
  5. ImageMagick vs scikit-image

ImageMagick vs scikit-image

OverviewComparisonAlternatives

Overview

scikit-image
scikit-image
Stacks311
Followers129
Votes12
GitHub Stars6.4K
Forks2.3K
ImageMagick
ImageMagick
Stacks94
Followers93
Votes0
GitHub Stars14.8K
Forks1.5K

ImageMagick vs scikit-image: What are the differences?

  1. Implementation: ImageMagick is a command-line tool that allows image processing and manipulation, while scikit-image is a Python library that provides various image processing algorithms as functions.
  2. Programming Language: ImageMagick is not tied to a specific programming language, making it more versatile for different environments, whereas scikit-image is designed specifically for Python, making it easier to integrate with other data analysis libraries in the Python ecosystem.
  3. Community Support: ImageMagick has a larger community base and has been around for a longer period, providing extensive documentation and resources, while scikit-image, although popular, has a smaller community compared to ImageMagick.
  4. Ease of Use: ImageMagick focuses on providing quick and simple image processing tools through command-line interfaces, while scikit-image provides a more comprehensive set of algorithms for in-depth image analysis and manipulation.
  5. Performance: ImageMagick is known for its speed and efficiency in handling large batches of images, making it ideal for batch processing tasks, whereas scikit-image may be slower in processing large sets of images due to its Python environment.
  6. Flexibility: ImageMagick offers a wide range of image file format support and can work with various image types easily, while scikit-image may have limitations in working with some specific file formats or specialized image processing tasks.

In Summary, the key differences between ImageMagick and scikit-image lie in their implementation, programming language support, community backing, ease of use, performance, and flexibility.

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Detailed Comparison

scikit-image
scikit-image
ImageMagick
ImageMagick

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

It is a free and open-source software suite for displaying, converting, and editing raster image and vector image files. It can read and write images in a variety of formats (over 200) including PNG, JPEG, GIF, HEIC, TIFF, DPX, EXR, WebP, Postscript, PDF, and SVG.

Provides I/O, filtering, morphology, transformations, measurement, annotation, color conversions, test data sets, etc.;Written in Python with a well-commented source code;Has had 5,709 commits made by 116 contributors representing 29,953 lines of code;Released under BSD-3-Clause license
Color Quantization; Posterization; Dithering; Halftone dithering; Liquid rescaling; Transparency; GIF animation; Blur; Sharpen; Composite.
Statistics
GitHub Stars
6.4K
GitHub Stars
14.8K
GitHub Forks
2.3K
GitHub Forks
1.5K
Stacks
311
Stacks
94
Followers
129
Followers
93
Votes
12
Votes
0
Pros & Cons
Pros
  • 6
    More powerful
  • 4
    Anaconda compatibility
  • 2
    Great documentation
No community feedback yet
Integrations
No integrations available
Java
Java
PHP
PHP
Ruby
Ruby
Haxe
Haxe
.NET
.NET
C++
C++
Perl
Perl
Common Lisp
Common Lisp

What are some alternatives to scikit-image, ImageMagick?

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.

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.

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.

ImageKit

ImageKit

ImageKit offers a real-time URL-based API for image & video optimization, streaming, and 50+ transformations to deliver perfect visual experiences on websites and apps. It also comes integrated with a Digital Asset Management solution.

Cloudimage

Cloudimage

Effortless image resizing, optimization and CDN delivery. Make your site fully responsive and really fast.

Kraken.io

Kraken.io

It supports JPEG, PNG and GIF files. You can optimize your images in two ways - by providing an URL of the image you want to optimize or by uploading an image file directly to its API.

ImageEngine

ImageEngine

ImageEngine is an intelligent Image CDN that dynamically optimizes image content tailored to the end users device. Using device intelligence at the CDN edge, developers can greatly simplify their image management process while accelerating their site.

FFMPEG

FFMPEG

The universal multimedia toolkit.

GStreamer

GStreamer

It is a library for constructing graphs of media-handling components. The applications it supports range from simple Ogg/Vorbis playback, audio/video streaming to complex audio (mixing) and video (non-linear editing) processing.

GraphicsMagick

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.

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