Software Alternatives, Accelerators & Startups

ARToolKit VS Plotly

Compare ARToolKit VS Plotly and see what are their differences

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ARToolKit logo ARToolKit

The world's most widely used tracking library for augmented reality.

Plotly logo Plotly

Low-Code Data Apps
  • ARToolKit Landing page
    Landing page //
    2023-01-01
  • Plotly Landing page
    Landing page //
    2023-07-31

ARToolKit features and specs

  • Open-Source
    ARToolKit is open-source, which means it is free to use and can be modified to suit specific needs. This also encourages community contributions and transparency.
  • Cross-Platform Support
    Supports multiple platforms including Windows, macOS, Linux, Android, and iOS, which allows for wide-ranging application development.
  • Large Community
    Has a large user and developer community, providing a wealth of tutorials, forums, and third-party resources that can help in troubleshooting and learning.
  • Extensive SDK
    Includes a comprehensive Software Development Kit (SDK) that provides numerous features and functionalities for developing augmented reality applications.
  • Marker-Based Tracking
    Provides robust marker-based tracking, making it easier for developers to create stable and reliable AR experiences.

Possible disadvantages of ARToolKit

  • Steep Learning Curve
    Can be complex for beginners due to its extensive features and the need for understanding various aspects of augmented reality development.
  • Performance Limitations
    May not always offer the best performance compared to some newer AR frameworks, especially on lower-end devices.
  • Limited Natural Feature Tracking
    Primarily relies on marker-based tracking, with less robust support for natural feature tracking compared to other AR tools like ARCore or ARKit.
  • Outdated Documentation
    Some documentation may be outdated or not as comprehensive, making it challenging to find updated information or solutions to recent issues.
  • Maintenance and Updates
    Since it is community-driven, the frequency and quality of updates and maintenance can vary, potentially leading to bugs or compatibility issues.

Plotly features and specs

  • Interactivity
    Plotly offers highly interactive plots that allow users to pan, zoom, and hover over data points for more information. This enhances the user experience and provides deeper insights.
  • High-quality visualizations
    It provides aesthetically pleasing and highly customizable charts, making it suitable for publication-quality visuals.
  • Versatility
    Plotly supports multiple chart types including line charts, scatter plots, bar charts, and 3D plots, making it suitable for a wide range of applications.
  • Python integration
    Plotly is well-integrated with Python and works seamlessly with other popular data science libraries like Pandas, NumPy, and Scikit-learn.
  • Web-based
    The plots can be easily embedded in web applications or dashboards, making it ideal for sharing insights over the internet.
  • Open-source
    Plotly offers an open-source version, which allows users to create and share visualizations without any cost.

Possible disadvantages of Plotly

  • Performance
    Rendering very large datasets can sometimes be slow, which may not be suitable for real-time data visualization requirements.
  • Learning curve
    Even though the library is well-documented, the extensive range of features can have a steep learning curve for beginners.
  • Cost for advanced features
    While the basic functionality is free, more advanced features, such as export to certain formats and additional customizable options, require a paid subscription.
  • Dependency management
    Plotly has a number of dependencies that need to be managed properly, which can sometimes complicate the setup process.
  • Complexity
    For simple visualizations, Plotly might be overkill and simpler libraries like Matplotlib or Seaborn could be more appropriate.

Analysis of ARToolKit

Overall verdict

  • ARToolKit is considered a good choice for those looking to get started with AR development, especially for educational purposes or for projects where open-source compatibility is important. However, it might not be the best choice for high-end commercial applications, where more advanced and newer AR SDKs could offer better performance and easier integration.

Why this product is good

  • ARToolKit is a well-known open-source library for creating augmented reality (AR) applications. It is renowned for its robustness and long-standing presence in the AR community, providing developers with tools to overlay virtual imagery on the real world. Key features include marker tracking, support for various platforms, and the ability to integrate with other applications and systems. Its open-source nature ensures that developers can customize it to fit specific needs, and a large community exists for support and collaboration.

Recommended for

    ARToolKit is recommended for hobbyists, educators, and researchers who are interested in exploring AR technology. It is also suitable for developers who prefer open-source tools and need to create custom AR solutions without licensing fees. Additionally, those working on cross-platform AR projects may find it particularly useful because of its long-term support across different systems.

Analysis of Plotly

Overall verdict

  • Overall, Plotly is a strong choice for those looking to create dynamic and interactive data visualizations, thanks to its range of features and ease of integration with web technologies.

Why this product is good

  • Plotly is considered good because it offers a comprehensive suite of tools for creating interactive visualizations that can be used in web applications, reports, and dashboards. It supports many different types of plots, is easy to use for both beginners and experienced developers, and integrates well with popular programming languages like Python, R, and JavaScript.

Recommended for

    Plotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.

ARToolKit videos

AR SDK: Vuforia/Wikitude OR Open Source (ARToolkit)?

More videos:

  • Review - ARCore conflit with ARToolkit(Unreal4AR) Unreal Engine 4 - 2 Project Test
  • Demo - Augmented Reality Demo using the iPhone ARToolkit SDK and a Custom AR Marker

Plotly videos

Create Real-time Chart with Javascript | Plotly.js Tutorial

More videos:

  • Review - Introducing plotly.py 3.0
  • Review - Is Plotly The Better Matplotlib?
  • Tutorial - Plotly Tutorial 2021
  • Review - Data Visualization as The First and Last Mile of Data Science Plotly Express and Dash | SciPy 2021

Category Popularity

0-100% (relative to ARToolKit and Plotly)
Augmented Reality
100 100%
0% 0
Data Visualization
0 0%
100% 100
Photo & Video
100 100%
0% 0
Charting Libraries
0 0%
100% 100

User comments

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Reviews

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

ARToolKit Reviews

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Plotly Reviews

Best 8 Redash Alternatives in 2023 [In Depth Guide]
Plotly is specifically designed for companies who want to build and deploy analytic applications like dashboards using Python, Julia, or R without needing DevOps or Javascript developers.
Source: www.datapad.io
5 Best Python Libraries For Data Visualization in 2023
Plotly is a web-based data visualization toolkit that comes with unique functionalities such as dendrograms, 3D charts, and also contour plots, which is not very common in other libraries. It has a great API offering scatter plots, line charts, bar charts, error bars, box plots, and other visualizations. Plotly can even be accessed from a Python Notebook.
Top 8 Python Libraries for Data Visualization
Plotly is a free open-source graphing library that can be used to form data visualizations. Plotly (plotly.py) is built on top of the Plotly JavaScript library (plotly.js) and can be used to create web-based data visualizations that can be displayed in Jupyter notebooks or web applications using Dash or saved as individual HTML files. Plotly provides more than 40 unique...
5 top picks for JavaScript chart libraries
Plotly is a graphing library that’s available for various runtime environments, including the browser. It supports many kinds of charts and graphs that we can configure with a variety of options.

Social recommendations and mentions

Based on our record, Plotly seems to be more popular. It has been mentiond 34 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.

ARToolKit mentions (0)

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

Plotly mentions (34)

  • How to Analyze 47 Million Hacker News Posts: A Data Scientist's Dream Dataset Just Got Better
    Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization. - Source: dev.to / 6 months ago
  • Python for Data Visualization: Best Tools and Practices
    Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / over 1 year ago
  • Generative AI Powered QnA & Visualization Chatbot
    Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / over 1 year ago
  • Build a Stock Dashboard in less than 40 lines of Python code!🤓
    In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / almost 2 years ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / about 2 years ago
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What are some alternatives?

When comparing ARToolKit and Plotly, you can also consider the following products

Google ARCore - Google Augmented Reality SDK

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

Vuforia SDK - Vuforia is a vision-based augmented reality software platform.

RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...

AR SDK - Augmented Reality SDK

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.