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This article introduces the relevant knowledge of "what image processing tools Python has". In the operation of actual cases, many people will encounter such a dilemma, so let the editor lead you to learn how to deal with these situations. I hope you can read it carefully and be able to achieve something!

1. Scikit Image

Scikit-image is an open source Python package that can use the numpy array. It implements algorithms and utilities for research, education, and industrial applications. It is a fairly simple and straightforward library, even for newcomers to the Python ecosystem. The code is written by an active volunteer community with high-quality and peer-reviewed features.

Use

The package is imported as skimage, and most functions can be found in sub-modules. Some examples of skimage include:

Image filtering

Template matching using match template function

2. Numpy

Numpy is one of the core libraries in Python programming, which provides support for arrays. An image is essentially a standard Numpy array containing pixels of data points. Therefore, by using basic NumPy operations such as slicing, masking, and fancy indexing, we can modify the pixel values of the image. You can use skimage to load images and matplotlib to display images.

Resources

A complete list of resources and documents can be found on the official documentation page of Numpy.

Use

Use Numpy to mask the image

3. Scipy

Scipy is another core scientific module of Python, similar to Numpy, which can be used for basic image processing and processing tasks. Especially the sub-module scipy.ndimage. Provides functions that operate on an n-dimensional NumPy array. The software package currently includes linear and nonlinear filtering, binary morphology, b-spline interpolation and object measurement functions.

Use

Use SciPy and Gaussian filter to blur the image:

4. PIL/ Pillow

PIL (Python Imaging Library) is a free library of the Python programming language that supports opening, manipulating, and saving many different image file formats. However, with its last release in 2009, its development stagnated. Fortunately, there is Pillow, an active development branch of PIL, which is easier to install, supports all major operating systems, and supports Python3. The library contains basic image processing functions, including point manipulation, filtering using a set of built-in convolution cores, and color space conversion.

Use

Use ImageFilter to enhance the image in Pillow:

5. OpenCV-Python

OpenCV (Open Source computer Vision Library) is one of the most widely used computer vision application libraries. * OpenCV- python * is the python API of OpenCV. OpenCV-Python is not only fast because the background consists of code written in C / C++, but it is also easy to code and deploy (due to the Python wrapper in the foreground). This makes it a good choice for executing computing-intensive computer vision programs.

Use

The following example shows OpenCV-Python using pyramids in Image blend to create a new fruit called 'Orapple'.

6. SimpleCV

SimpleCV is also an open source framework for building computer vision applications. With it, you can access several high-performance computer vision libraries, such as OpenCV, without first understanding bit depth, file format, color space, and so on. The learning curve is much smaller than OpenCV, as their slogan says: make computer vision easier. Some proponents of SimpleCV are:

Even beginners can write simple machine vision tests.

Cameras, video files, images and video streams are all interoperable

Resources

The official documentation is very easy to understand and there are a large number of examples and use cases to follow.

Use

7. Mahotas

Mahotas is another computer vision and image processing library for Python. It includes traditional image processing functions, such as filtering and morphological operations, as well as more modern computer vision functions for feature computing, including point of interest detection and local descriptors. The interface is written in Python and is suitable for rapid development, but the algorithm is implemented in C++ and is tuned for speed. The Mahotas library is fast, concise, and even has minimal dependencies. Read their official papers to learn more.

Resources

The official documentation contains installation instructions, examples and even tutorials that can help you get started easily.

Use

The Mahotas library relies on using simple code to accomplish the task. For the problem of finding Wally'', Mahotas does a good job and requires a minimum of code. this is the source code.

8. SimpleITK

ITK or Insight Segmentation and Registration Toolkit is an open source cross-platform system that provides developers with a wide range of image analysis software tools. Among them, SimpleITK is a simplification layer built on top of ITK to promote its use in rapid prototyping, education, and interpretive languages. SimpleITK is an image analysis toolkit that contains a large number of components that support general filtering operations, image segmentation, and registration. SimpleITK itself is written in C++, but can be used in many programming languages, including Python.

Resources

A large number of Jupyter Notebooks are provided to illustrate the use of SimpleITK for educational and research activities. These Notebooks demonstrate the use of SimpleITK for interactive image analysis using Python and R programming languages.

Use

The following animation is a visualization of the accurate CT/MR registration process created with SimpleITK and Python.

9. Pgmagick

Pgmagick is a python-based wrapper for the GraphicsMagick library. The image processing system is sometimes called the Swiss Army knife for image processing. It provides a robust and efficient collection of tools and libraries that support reading, writing, and manipulating images in 88 major formats, including important formats such as DPX, GIF, JPEG, JPEG-2000, PNG, PDF, PNM, and TIFF.

Resources

There is a Github Repository dedicated to PgMagick with installation and requirements instructions. There is also a detailed user guid on this topic.

Use

There are few image processing activities that can be performed with pgmagick:

Image zooming:

Edge extraction:

10. Pycairo

Pycairo is a set of python bindings for the cairo graphics library. Cairo is a 2D graphics library for drawing vector graphics. Vector graphics are interesting because they do not lose clarity when resized or converted. Pycairo is a set of bindings to cairo that can be used to invoke cairo commands from Python.

Resources

Pycairo GitHub repository is a good resource with detailed instructions on installation and use. There is also a getting started guide with a short tutorial on Pycairo.

Use

Use Pycairo to draw lines, basic shapes, and radial gradients

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