OpenCV
OpenCV

525
534
+ 1
71
scikit-image
scikit-image

47
77
+ 1
10
Add tool

OpenCV vs scikit-image: What are the differences?

Developers describe OpenCV as "Open Source Computer Vision Library". 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. On the other hand, scikit-image is detailed as "Image processing in Python". scikit-image is a collection of algorithms for image processing.

OpenCV and scikit-image can be primarily classified as "Image Processing and Management" tools.

Some of the features offered by OpenCV are:

  • C++, C, Python and Java interfaces and supports Windows, Linux, Mac OS, iOS and Android
  • More than 47 thousand people of user community and estimated number of downloads exceeding 7 million
  • Usage ranges from interactive art, to mines inspection, stitching maps on the web or through advanced robotics

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

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

OpenCV and scikit-image are both open source tools. It seems that OpenCV with 35.8K GitHub stars and 26.2K forks on GitHub has more adoption than scikit-image with 3.07K GitHub stars and 1.3K GitHub forks.

Pros of OpenCV
Pros of scikit-image

Sign up to add or upvote prosMake informed product decisions

Sign up to add or upvote consMake informed product decisions

What is 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.

What is scikit-image?

scikit-image is a collection of algorithms for image processing.
What companies use OpenCV?
What companies use scikit-image?

Sign up to get full access to all the companiesMake informed product decisions

What tools integrate with OpenCV?
What tools integrate with scikit-image?

Sign up to get full access to all the tool integrationsMake informed product decisions

What are some alternatives to OpenCV and scikit-image?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
CImg
It mainly consists in a (big) single header file CImg.h providing a set of C++ classes and functions that can be used in your own sources, to load/save, manage/process and display generic images.
OpenGL
It is a cross-language, cross-platform application programming interface for rendering 2D and 3D vector graphics. The API is typically used to interact with a graphics processing unit, to achieve hardware-accelerated rendering.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
OpenCL
It is the open, royalty-free standard for cross-platform, parallel programming of diverse processors found in personal computers, servers, mobile devices and embedded platforms. It greatly improves the speed and responsiveness of a wide spectrum of applications in numerous market categories including gaming and entertainment titles, scientific and medical software, professional creative tools, vision processing, and neural network training and inferencing.
See all alternatives
Interest over time