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SciPy VS python pillow

Compare SciPy VS python pillow and see what are their differences

LibHunt
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
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  3. » Reviews
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SciPy logo SciPy

SciPy is a Python-based ecosystem of open-source software for mathematics, science, and engineering. 

python pillow logo python pillow

The friendly PIL fork (Python Imaging Library). Contribute to python-pillow/Pillow development by creating an account on GitHub.
  • SciPy Landing page
    Landing page //
    2023-07-26
  • python pillow Landing page
    Landing page //
    2023-08-18

SciPy features and specs

  • Comprehensive Library
    SciPy provides a wide range of scientific and technical computing tools, including modules for optimization, integration, interpolation, eigenvalue problems, algebraic equations, differential equations, statistics, and more.
  • Interoperability
    SciPy is built on top of NumPy, which means it naturally dovetails with other scientific computing libraries in the Python ecosystem, facilitating ease of integration and use in conjunction with libraries like Matplotlib and Pandas.
  • Active Community
    SciPy boasts a large, active community of developers and users, which provides extensive documentation, forums, and regular updates and improvements to the library.
  • Open-source
    Being an open-source library, SciPy promotes collaboration and adaptation, allowing users to contribute to its development and modify its tools to suit specific needs.

Possible disadvantages of SciPy

  • Complexity
    For beginners in scientific computing or programming, the comprehensive nature of SciPy can be overwhelming due to its broad range of functionalities and somewhat steep learning curve.
  • Performance Limitations
    Being a high-level library, SciPy may not be as performant as low-level implementations or specialized tools for very demanding computational tasks or large-scale data processing.
  • Dependency on NumPy
    While SciPy's reliance on NumPy ensures compatibility and ease of use within the Python ecosystem, it also means that its performance and limits are tied to those of NumPy.
  • Windows Limitations
    Some functions and modules of SciPy may not work as efficiently or might encounter compatibility issues when run on Windows operating systems compared to Unix-based systems.

python pillow features and specs

  • Wide Format Support
    Pillow supports a wide range of image file formats including JPEG, PNG, BMP, GIF, and TIFF, which makes it very versatile for various image processing needs.
  • Ease of Use
    The library is known for its simplicity and intuitive API, making it easy for beginners to quickly grasp the basics of image manipulation.
  • Active Development
    Pillow receives regular updates and community support, ensuring that it stays up-to-date and compatible with the latest Python versions.
  • Comprehensive Documentation
    Pillow has extensive documentation which provides clear and helpful guidance for both basic and advanced image processing tasks.
  • Integration
    The library integrates well with other Python libraries, which can be advantageous for more complex projects that require multiple dependencies.

Possible disadvantages of python pillow

  • Performance
    For very large images or complex transformations, Pillow might not be the most efficient in terms of performance compared to specialized libraries.
  • Limited Advanced Features
    While Pillow is great for basic to moderate image processing tasks, it might lack some advanced features found in more specialized image processing libraries.
  • Threading Limitations
    There might be some limitations and issues around threading, which can be a drawback for applications requiring concurrent image processing.
  • Learning Curve for Complex Features
    While basic features are easy to use, implementing more complex image manipulation tasks might require a steeper learning curve.

SciPy videos

+ Add

Numerical Computing With NumPy Tutorial | SciPy 2020 | Eric Olsen

More videos:

  • Tutorial - Land on Vector Spaces: Practical Linear Algebra with Python | SciPy 2019 Tutorial | L Barba, T Wang

python pillow videos

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Category Popularity

0-100% (relative to SciPy and python pillow)

SciPy

python pillow

Data Science And Machine Learning
64 64%
Data Science And Machine Learning
36% 36
Data Science Tools
100 100%
Data Science Tools
0% 0
Development Tools
0 0%
Development Tools
100% 100
Technical Computing
100 100%
Technical Computing
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare SciPy and python pillow

SciPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
SciPy is primarily used for mathematical and scientific computations, but sometimes it can also be used for basic image manipulation and processing tasks using the submodule scipy.ndimage.At the end of the day, images are just multidimensional arrays, SciPy provides a set of functions that are used to operate n-dimensional Numpy operations. SciPy provides some basic image...
Source: www.analyticsvidhya.com

python pillow Reviews

10 Python Libraries for Computer Vision
Pillow (PIL Fork) is a powerful library for image processing tasks. It supports various image formats and provides functionalities such as resizing, cropping, filtering, and adding text to images. Whether you’re working with photographs or generating visual content, Pillow offers an array of tools to manipulate images effectively.
Source: clouddevs.com

Social recommendations and mentions

Based on our record, SciPy seems to be more popular. It has been mentiond 17 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

SciPy mentions (17)

  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 9 months ago
  • Video Generation with Python
    Python has become a popular programming language for different applications, including data science, artificial intelligence, and web development. But, did you know creating and rendering fully customized videos with Python is also possible? At Stack Builders, we have successfully used Python libraries such as MoviePy, SciPy, and ImageMagick to generate videos with animations, text, and images. In this article, we... - Source: dev.to / over 1 year ago
  • Beginning Python: Project Management With PDM
    A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / over 1 year ago
  • Understanding Cosine Similarity in Python with Scikit-Learn
    SciPy: a library used for scientific and technical computing. It has a function that can calculate the cosine distance, which equals 1 minus the cosine similarity. - Source: dev.to / almost 2 years ago
  • PSA: You don't need fancy stuff to do good work.
    Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: about 2 years ago
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python pillow mentions (0)

We have not tracked any mentions of python pillow yet. Tracking of python pillow recommendations started around Mar 2021.

What are some alternatives?

When comparing SciPy and python pillow, you can also consider the following products

NumPy - NumPy is the fundamental package for scientific computing with Python

python xlrd - Please use openpyxl where you can... Contribute to python-excel/xlrd development by creating an account on GitHub.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

python docx - Create and modify Word documents with Python. Contribute to python-openxml/python-docx development by creating an account on GitHub.

Matplotlib - matplotlib is a python 2D plotting library which produces publication quality figures in a variety...

OpenCV - OpenCV is the world's biggest computer vision library

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