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Piskel VS NumPy

Compare Piskel VS NumPy 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. sponsored
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Piskel logo Piskel

Piskel is a website where designers online create sprites or pixel art.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Piskel Landing page
    Landing page //
    2022-06-24
  • NumPy Landing page
    Landing page //
    2023-05-13

Piskel features and specs

  • User-Friendly Interface
    Piskel offers a simple and intuitive interface that is easy to navigate, making it accessible for beginners.
  • Online Access
    As a web-based tool, Piskel can be accessed from any device with an internet connection, allowing for flexible usage without the need for installation.
  • Real-Time Preview
    Piskel provides a real-time preview of animations, allowing users to see immediate results of their edits and adjustments.
  • Free to Use
    Piskel is entirely free to use, which makes it an attractive option for individuals and educators with limited budgets.
  • Export Options
    The application supports multiple export formats including GIFs and spritesheets, making it versatile for various use cases.
  • Open Source
    As an open-source project, Piskel allows users to contribute to its development and customize the tool to better fit their needs.

Possible disadvantages of Piskel

  • Limited Advanced Features
    Piskel lacks some advanced features that professional pixel artists might require, such as layer effects and complex animation timelines.
  • Dependence on Internet
    Being an online application, Piskel's use is constrained by internet availability and speed, which can be a limitation for users with unstable connections.
  • Performance Issues
    For larger projects with numerous frames or high resolutions, Piskel can experience performance lags and slowdowns.
  • No Mobile App
    While Piskel can be accessed from mobile browsers, it does not have a dedicated mobile app, which can affect usability on smaller screens.
  • Basic Drawing Tools
    The drawing tools are relatively basic compared to other professional graphic design software, which may limit creative options.
  • Privacy Concerns
    As an online tool, there may be concerns around data privacy and the security of stored projects or exported files.

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Analysis of NumPy

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

Piskel videos

+ Add

How to Create Pixel Art and Animations with Piskel Tutorial 1 - What is Piskel?

NumPy videos

+ Add

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Category Popularity

0-100% (relative to Piskel and NumPy)

Piskel

NumPy

Graphic Design Software
100 100%
Graphic Design Software
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Art Tools
100 100%
Art Tools
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Piskel and NumPy. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Piskel and NumPy

Piskel Reviews

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NumPy 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
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Social recommendations and mentions

Based on our record, NumPy should be more popular than Piskel. It has been mentiond 122 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.

Piskel mentions (13)

  • My Eye of Cthulhu and Twins resprites.
    I use Aseprite. If you're looking for a free tool to get into pixel art, I recommend piskelapp.com, as it's what I used for something like five years. Source: almost 4 years ago
  • Does anyone know a free resource for thousands of 2D assets?
    You could use piskel and import that image as a spritesheet, tell it each asset size and export each one individually, not sure how other do this there's probably a better way. Source: almost 4 years ago
  • Made a Vaporwave-esc background for a w.i.p game, thought I'd share here
    I don't use sprite, but I did use a tool for the transition of colors. I use a site known as piskel where they have a built in dithering tool. Source: about 4 years ago
  • Bit Screens | Edition 1
    Each NFT is 1/50 and were created live on stream at twitch.tv/Jomigloy. These were created using a combination of piskelapp.com and Aseprite. Each NFT is 132 frames and I had a blast making them. With this project I'm trying to evoke feelings of nostalgia with the machine base, and the screen allows me to convey a message. In this case, I'm spreading Loopring hype on these screens. The last few weeks collecting L2... Source: over 4 years ago
  • I'm in need of your strongest potions
    Ooh, what website? I know piskelapp.com (I love that site) lets you save to keep working on it later or export to create a video file, but if you're using another one I'd love to check it out! Source: over 4 years ago
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NumPy mentions (122)

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What are some alternatives?

When comparing Piskel and NumPy, you can also consider the following products

Aseprite - Aseprite is an art program dedicated to the creation of pixel art.

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

Grafx2 - GrafX2 is a bitmap paint program inspired by the Amiga programs Deluxe Paint and Brilliance.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Pixen - Pixen is a professional pixel art editor designed for working with low-resolution raster art, such as those 8-bit sprites found in old-school video games.

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

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