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Storyboarder VS NumPy

Compare Storyboarder VS NumPy and see what are their differences

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Storyboarder logo Storyboarder

Storyboarder makes it easy to visualize a story as fast you can draw stick figures.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Storyboarder Landing page
    Landing page //
    2019-05-27
  • NumPy Landing page
    Landing page //
    2023-05-13

Storyboarder features and specs

  • Ease of Use
    Storyboarder offers an intuitive interface that makes it easy for both beginners and professionals to create storyboards quickly.
  • Open Source
    Being an open-source tool, Storyboarder is free to use and has a community contributing to its development and improvement.
  • Integration
    Storyboarder seamlessly integrates with other drawing tools like Photoshop, allowing users to edit their boards in their preferred environment.
  • Pre-made Templates
    Storyboarder comes with a variety of pre-made templates and assets, reducing the time and effort required to create complex storyboards.
  • Collaboration Features
    Storyboarder facilitates collaboration by allowing multiple users to work on the same project, making it ideal for team projects.

Possible disadvantages of Storyboarder

  • Limited Advanced Features
    While Storyboarder is excellent for basic and intermediate use, it lacks some advanced features that professionals might need for more complex projects.
  • Performance Issues
    Some users have reported performance issues, such as lag or crashes, especially when working with very large files or many layers.
  • Learning Curve for Advanced Integration
    Though it integrates with other tools like Photoshop, there's a learning curve involved in efficiently using these integrations.
  • Dependency on External Software
    To fully utilize all its capabilities, users might need additional software like Photoshop, adding to the overall cost and complexity.
  • Limited Customer Support
    As an open-source tool, Storyboarder doesn't offer professional customer support, relying instead on community forums and documentation.

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.

Storyboarder videos

+ Add

Review: Storyboarder by Wonder Unit

More videos:

  • Review - Storyboarder by Wonder Unit Review - Story Board Software
  • Review - Storyboarder 2.0 Update - Wonder Unit

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 Storyboarder and NumPy)

Storyboarder

NumPy

Online Services
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Data Science And Machine Learning
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Data Science And Machine Learning
100% 100
Design Tools
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Data Science Tools
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Data Science Tools
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User comments

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Reviews

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

Storyboarder 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 Storyboarder. It has been mentiond 119 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.

Storyboarder mentions (22)

  • Question about Storyboards
    I use Stroyboarder by wonderunit (its free) https://wonderunit.com/storyboarder/ You can either draw in the app or make your scenes in another program and drop them in. Eg, I could make a bunch of frames in illustrator on separate artboards and drop them in. It also links up to photoshop with the press of a button. Source: almost 2 years ago
  • Here's a printable six panel storyboard for anyone to use
    Here's an awesome free tool to storyboard with imports and timelines https://wonderunit.com/storyboarder/. Source: about 2 years ago
  • Photoshop / Clip Studio standards for boxes
    Or for a more budget friendly option, take a look at Storyboarder by Wonder Unit This piece of software is nice, because it can work well with PSD's so you can use the tools in PS or CSP that you are comfortable with. Source: over 2 years ago
  • Anyone knows of a cheap software or app to storyboard a low budget indie film on?
    Https://wonderunit.com/storyboarder/ or give Blender’s new Storypencil add-on a try. Might want. Blender for VFX anyway. Source: over 2 years ago
  • Storyboard Pro 22 Crack
    Storyboarder, Blender for Storyboarding, any drawing software with animation features or software licenses distributed by your university, should provide you enough options to fulfill your tasks. Source: over 2 years ago
View more

NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 4 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 8 months ago
  • 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 / 8 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 9 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 9 months ago
View more

What are some alternatives?

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

Boords - Making storyboards can be fiddly.

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

Storyboard That - Storyboard That is the world's best online storyboard creator.

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

Microsoft Cortana - Microsoft Cortana – Digital Assistant app brings a smart assistant to your smartphone to help keep track of the important stuff, introduced by Microsoft.

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

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