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scikit-image vs ImageKit: What are the differences?
Developers describe scikit-image as "Image processing in Python". scikit-image is a collection of algorithms for image processing. On the other hand, ImageKit is detailed as "Automate image optimization on all platforms". It is an image optimization solution that offers smart image optimization in real-time, enabling you to easily optimize images via dynamic resizing and cropping as well as seamless and fast delivery. The software allows you to reduce images sizes while retaining high quality resolution.
scikit-image and ImageKit belong to "Image Processing and Management" category of the tech stack.
Some of the features offered by scikit-image are:
- 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
On the other hand, ImageKit provides the following key features:
- Image Processing
- Image Optimization
- Image Compression
scikit-image is an open source tool with 3.23K GitHub stars and 1.38K GitHub forks. Here's a link to scikit-image's open source repository on GitHub.
Pros of ImageKit
- Pay as you go pricing4
- Unlimited thumbnail storage4
- Unlimited transformations4
- Easy to integrate4
- Forever free plan3
- S3 integration3
- SDKs for many languages2
- Quick support2
- Media library for asset management-tag,organise,search1
- Performance alerts & Optimization report1
- Reduces developer efforts1
- AI based Smart cropping1
- Fast image delivery1
Pros of scikit-image
- More powerful6
- Anaconda compatibility4
- Great documentation1