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  1. Stackups
  2. Application & Data
  3. Video Hosting
  4. Application Streaming
  5. Amazon AppStream vs scikit-image

Amazon AppStream vs scikit-image

OverviewComparisonAlternatives

Overview

Amazon AppStream
Amazon AppStream
Stacks56
Followers64
Votes7
scikit-image
scikit-image
Stacks311
Followers129
Votes12
GitHub Stars6.4K
Forks2.3K

Amazon AppStream vs scikit-image: What are the differences?

What is Amazon AppStream? Stream resource intensive applications and games from the cloud. AppStream deploys and renders your application on AWS infrastructure and streams the output to mass-market devices, such as personal computers, tablets, and mobile phones. Because your application is running in the cloud, it can scale to handle vast computational and storage needs, regardless of the devices your customers are using. You can choose to stream either all or parts of your application from the cloud. Amazon AppStream enables use cases for games and applications that wouldn’t be possible running natively on mass-market devices. Using Amazon AppStream, your games and applications are no longer constrained by the hardware in your customer’s hands.

What is scikit-image? Image processing in Python. scikit-image is a collection of algorithms for image processing.

Amazon AppStream can be classified as a tool in the "Application Streaming" category, while scikit-image is grouped under "Image Processing and Management".

Some of the features offered by Amazon AppStream are:

  • Amazon AppStream includes a SDK that currently supports streaming applications from Microsoft Windows Server 2008 R2 to devices running FireOS, Android, iOS, and Microsoft Windows. &nbsp
  • A Mac OS X SDK is planned for 2014.
  • Remove Device Constraints- You can leverage the compute power of AWS to deliver experiences that wouldn’t normally be possible due to the GPU, CPU, memory or physical storage constraints of local devices.

On the other hand, scikit-image provides the following key features:

  • 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

"Customization" is the primary reason why developers consider Amazon AppStream over the competitors, whereas "More powerful" was stated as the key factor in picking scikit-image.

scikit-image is an open source tool with 4.3K GitHub stars and 1.79K GitHub forks. Here's a link to scikit-image's open source repository on GitHub.

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Detailed Comparison

Amazon AppStream
Amazon AppStream
scikit-image
scikit-image

AppStream deploys and renders your application on AWS infrastructure and streams the output to mass-market devices, such as personal computers, tablets, and mobile phones. Because your application is running in the cloud, it can scale to handle vast computational and storage needs, regardless of the devices your customers are using. You can choose to stream either all or parts of your application from the cloud. Amazon AppStream enables use cases for games and applications that wouldn’t be possible running natively on mass-market devices. Using Amazon AppStream, your games and applications are no longer constrained by the hardware in your customer’s hands.

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

Amazon AppStream includes a SDK that currently supports streaming applications from Microsoft Windows Server 2008 R2 to devices running FireOS, Android, iOS, and Microsoft Windows.  A Mac OS X SDK is planned for 2014.;Remove Device Constraints- You can leverage the compute power of AWS to deliver experiences that wouldn’t normally be possible due to the GPU, CPU, memory or physical storage constraints of local devices.;Multi Platform Support- You can write your application once and stream it to multiple device platforms. To support a new device, just write a small client to connect to your application.;Easy Updates- Because your application is centrally managed by Amazon AppStream, updating your application is as simple as providing a new version of your application to Amazon AppStream. That's all you need to do to immediately upgrade all of your customers without any action on their part.;Instant On- Streaming your application with AppStream lets your customers start using your application or game immediately, without the delays associated with large file downloads and time-consuming installations.;Improved Security- Unlike traditional boxed software and digital downloads, where your application is available for theft or reverse engineering, Amazon AppStream stores your application binary securely in AWS datacenters.;Automatic Scaling- You can use Amazon AppStream to specify capacity needs, and then the service automatically scales your streamed application and connects customers’ devices to it.
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
Statistics
GitHub Stars
-
GitHub Stars
6.4K
GitHub Forks
-
GitHub Forks
2.3K
Stacks
56
Stacks
311
Followers
64
Followers
129
Votes
7
Votes
12
Pros & Cons
Pros
  • 5
    Customization
  • 2
    Pricing
Pros
  • 6
    More powerful
  • 4
    Anaconda compatibility
  • 2
    Great documentation

What are some alternatives to Amazon AppStream, scikit-image?

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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