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PlantUML VS OpenCV

Compare PlantUML VS OpenCV 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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Contents:
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PlantUML logo PlantUML

PlantUML is an open-source tool that uses simple textual descriptions to draw UML diagrams.

OpenCV logo OpenCV

OpenCV is the world's biggest computer vision library
  • PlantUML Landing page
    Landing page //
    2023-10-22
  • OpenCV Landing page
    Landing page //
    2023-07-29

PlantUML features and specs

  • Simple Syntax
    PlantUML uses a plain text language that is easy to learn, making it accessible for both technical and non-technical users.
  • Quick Diagram Creation
    Due to its straightforward text-based syntax, diagrams can be created and modified quickly without the need for a graphical interface.
  • Version Control Friendly
    Diagrams are stored as text files, making them easy to manage with version control systems like Git.
  • Integrations
    PlantUML integrates well with many other tools and platforms including IDEs (e.g., IntelliJ, VSCode), documentation generators (e.g., Doxygen, Sphinx), and project management tools.
  • Wide Range of Diagrams
    PlantUML supports a variety of UML and non-UML diagrams, including sequence diagrams, use case diagrams, class diagrams, and more.
  • Open Source
    PlantUML is an open-source tool, which makes it free to use and allows for community contributions and extensions.

Possible disadvantages of PlantUML

  • Learning Curve
    While the syntax is simple, users unfamiliar with text-based diagramming may need time to become proficient.
  • No GUI
    PlantUML lacks a graphical user interface (GUI), which might be a disadvantage for users who prefer drag-and-drop diagram creation.
  • Complex Diagrams
    For very complex diagrams, the text-based syntax can become cumbersome and hard to manage.
  • Rendering Limitations
    The style and formatting options are less flexible compared to some dedicated graphical diagramming tools.
  • Performance
    For large diagrams, the text-to-diagram rendering process can be slow.
  • Security Concerns
    Using PlantUML with remote server options might raise security issues, particularly when dealing with sensitive information.

OpenCV features and specs

  • Comprehensive Library
    OpenCV offers a wide range of tools for various aspects of computer vision, including image processing, machine learning, and video analysis.
  • Cross-Platform Compatibility
    OpenCV is designed to run on multiple platforms, including Windows, Linux, macOS, Android, and iOS, which makes it versatile for development across different environments.
  • Open Source
    Being open-source, OpenCV is freely available for use and allows developers to inspect, modify, and enhance the code according to their needs.
  • Large Community Support
    A large community of developers and researchers actively contributes to OpenCV, providing extensive support, tutorials, forums, and continuously updated documentation.
  • Real-Time Performance
    OpenCV is highly optimized for real-time applications, making it suitable for performance-critical tasks in various industries such as robotics and interactive installations.
  • Extensive Integration
    OpenCV can easily be integrated with other libraries and frameworks such as TensorFlow, PyTorch, and OpenCL, enhancing its capabilities in deep learning and GPU acceleration.
  • Rich Collection of examples
    OpenCV provides a large number of example codes and sample applications, which can significantly reduce the learning curve for beginners.

Possible disadvantages of OpenCV

  • Steep Learning Curve
    Due to the vast array of functionalities and the complexity of some of its advanced features, beginners may find it challenging to learn and use effectively.
  • Documentation Gaps
    While the documentation is extensive, it can sometimes be incomplete or outdated, requiring users to rely on community forums or external sources for solutions.
  • Resource Intensive
    Some functions and algorithms in OpenCV can be quite resource-intensive, requiring significant processing power and memory, which can be a limitation for low-end devices.
  • Limited High-Level Abstractions
    OpenCV provides a wealth of low-level functions, but it may lack higher-level abstractions and frameworks, necessitating more hands-on coding and algorithm development.
  • Dependency Management
    Setting up and managing dependencies can be cumbersome, especially when integrating OpenCV with other libraries or on certain operating systems.
  • Backward Compatibility Issues
    With frequent updates and new versions, backward compatibility can sometimes be problematic, potentially breaking existing code when updating.

Analysis of PlantUML

Overall verdict

  • Yes, PlantUML is a good tool for developers and teams who need a straightforward and efficient way to create and manage diagrams within their projects. Its text-based approach allows for easy updates and maintenance, which is beneficial in agile and fast-paced development settings.

Why this product is good

  • PlantUML is appreciated for its simplicity and versatility in creating UML diagrams. It allows users to write diagrams using a concise text-based language, which can be easily integrated into code repositories for version control. This approach facilitates collaboration and documentation among developers. Moreover, it supports various diagram types beyond UML, such as sequence diagrams, class diagrams, and state diagrams, and can be integrated with other tools and editors, enhancing its utility across different environments.

Recommended for

  • Software developers
  • Technical architects
  • Project managers
  • Teams using agile methodologies
  • Educators teaching software design

Analysis of OpenCV

Overall verdict

  • Yes, OpenCV is considered a good and reliable choice for computer vision tasks, particularly due to its extensive functionality, active community, and flexibility.

Why this product is good

  • OpenCV (Open Source Computer Vision Library) is widely regarded as a robust and versatile library for computer vision applications. It offers a comprehensive collection of functions and algorithms for image processing, video capture, machine learning, and more. Its open-source nature encourages community involvement, making it highly adaptable and continuously improving. OpenCV's cross-platform support and ease of integration with other libraries and languages further enhance its appeal.

Recommended for

  • Developers and researchers working on computer vision projects
  • People looking to implement real-time video analysis
  • Individuals exploring machine learning applications related to image and video processing
  • Anyone interested in experimenting with or learning computer vision concepts

PlantUML videos

+ Add

PlantUML - beautiful quick diagrams to explain your models

More videos:

  • Review - Folge16 - PlantUML und IntelliJ
  • Tutorial - PlantUML Gizmo Tutorial: Google Docs Add-on
  • Review - Mermaid vs PlantUML vs HackerDraw: Which One Is Best For You?
  • Review - Using PlantUML For Diagrams In A GitLab Wiki

OpenCV videos

+ Add

AI Courses by OpenCV.org

More videos:

  • Review - Practical Python and OpenCV

Category Popularity

0-100% (relative to PlantUML and OpenCV)

PlantUML

OpenCV

Diagrams
100 100%
Diagrams
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Flowcharts
100 100%
Flowcharts
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using PlantUML and OpenCV. 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 PlantUML and OpenCV

PlantUML Reviews

Top 7 diagrams as code tools for software architecture
PlantUML is a tool that allows you to write diagrams such as sequence, object, component, usecase, class diagrams and more.
Source: icepanel.medium.com
5 great diagramming tools for enterprise and software architects
PlantUML is an open source tool and syntax that allows you to make sequence, use case, class, object, and other diagrams from code. It also supports non-UML diagrams like JSON and YAML. In addition, it enjoys support from ArchiMate, ERD, Business Process Modeling Notation (BPMN), and other common notation styles. Its simple, plain-text definitions make creating, sharing, and...
Source: www.redhat.com
Software Diagrams - Plant UML vs Mermaid
For C4 Models, Mermaid support is still experimental. This shows as you have little control over the way the diagram is rendered, and some parts are unreadable (i.e., arrows over nodes). PlantUML works as you would expect and has support for more advanced setup like sprites. Not even close on this one. Winner: PlantUML
Source: www.dandoescode.com
9 Best UML Software For Mac & PC
PlantUML is another free open source sequence diagram software that uses text input to build UML charts. PlantUML requires using a specific PlantUML Language to construct sequence charts but once learned it’s very flexible.
Source: machow2.com
40 Open Source, Free and Top Unified Modeling Language (UML) Tools
PlantUML is a component that allows users to quickly write sequence diagrams, usecase diagrams, class diagrams, activity diagrams, component diagrams, state diagrams, deployment diagrams, object diagrams and wireframe graphical interfaces. Diagrams are defined using a simple and intuitive language. Images can be generated in PNG, SVG or LaTeX format and it is also possible...
Source: www.predictiveanalyticstoday.com

OpenCV Reviews

7 Best Computer Vision Development Libraries in 2024
From the widespread adoption of OpenCV with its extensive algorithmic support to TensorFlow's role in machine learning-driven applications, these libraries play a vital role in real-world applications such as object detection, facial recognition, and image segmentation.
Source: www.labellerr.com
10 Python Libraries for Computer Vision
OpenCV is the go-to library for computer vision tasks. It boasts a vast collection of algorithms and functions that facilitate tasks such as image and video processing, feature extraction, object detection, and more. Its simple interface, extensive documentation, and compatibility with various platforms make it a preferred choice for both beginners and experts in the field.
Source: clouddevs.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
OpenCV is an open-source computer vision and machine learning software library that was first released in 2000. It was initially developed by Intel, and now it is maintained by the OpenCV Foundation. OpenCV provides a set of tools and software development kits (SDKs) that help developers create computer vision applications. It is written in C++, but it supports several...
Source: www.uubyte.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
These are some of the most basic operations that can be performed with the OpenCV on an image. Apart from this, OpenCV can perform operations such as Image Segmentation, Face Detection, Object Detection, 3-D reconstruction, feature extraction as well.
Source: neptune.ai
5 Ultimate Python Libraries for Image Processing
Pillow is an image processing library for Python derived from the PIL or the Python Imaging Library. Although it is not as powerful and fast as openCV it can be used for simple image manipulation works like cropping, resizing, rotating and greyscaling the image. Another benefit is that it can be used without NumPy and Matplotlib.
Source: towardsdatascience.com

Social recommendations and mentions

Based on our record, OpenCV should be more popular than PlantUML. It has been mentiond 60 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.

PlantUML mentions (12)

  • Owning my own data, part 1: Integrating a self-hosted calendar solution
    That particular diagram seems to have been generated by https://plantuml.com according to the image's metadata. - Source: Hacker News / 2 months ago
  • Common Mistakes in Architecture Diagrams (2020)
    I have to confess I am guilty of this — I used to just draw some unstructured circles and arrows on a whiteboard and call it enough. Lately I've been trying to work my way through lots of different diagram types from https://plantuml.com/, and it does help to wrap my mind around the existing options. - Source: Hacker News / 4 months ago
  • LLM + Mermaid: How Modern Teams Create UML Diagrams Without Lucidchart
    Today, tools like Mermaid and PlantUML have taken center stage, thanks to their ability to generate diagrams with text-based commands. Even better, AI-powered assistants like Claude, ChatGPT, and GitHub Copilot have made generating diagrams even easier. These tools work directly within a developer's environment, creating diagrams that are version-controlled and integrated seamlessly into workflows. - Source: dev.to / 7 months ago
  • Blockdiag – simple diagram images generator – blockdiag 1.0 documentation
    While inactive blockdiag was small and nice for automatically annotating documentation. As you can see it hasn't been maintained for a few years. https://github.com/blockdiag/blockdiag With complex diagrams, I find good old PlantUML diagrams more useful if not as initially pretty as mermaid. Plus it will output archimate without having to touch that UI https://plantuml.com/ But really it is horses for courses.... - Source: Hacker News / 10 months ago
  • Introduction to Haskell Diagrams
    Use a high-level language like Plant UML, D2, Graphviz which are good for the purpose they are designed for, but not for generic purpose diagramming. - Source: dev.to / 10 months ago
View more

OpenCV mentions (60)

  • Grasping Computer Vision Fundamentals Using Python
    To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isn’t just a tool, it’s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that don’t just interpret visuals, but... - Source: dev.to / about 1 month ago
  • Top Programming Languages for AI Development in 2025
    Ideal For: Computer vision, NLP, deep learning, and machine learning. - Source: dev.to / about 1 month ago
  • Why 2024 Was the Best Year for Visual AI (So Far)
    Almost everyone has heard of libraries like OpenCV, Pytorch, and Torchvision. But there have been incredible leaps and bounds in other libraries to help support new tasks that have helped push research even further. It would be impossible to thank each and every project and the thousands of contributors who have helped make the entire community better. MedSAM2 has been helping bring the awesomeness of SAM2 to the... - Source: dev.to / 6 months ago
  • 20 Open Source Tools I Recommend to Build, Share, and Run AI Projects
    OpenCV is an open-source computer vision and machine learning software library that allows users to perform various ML tasks, from processing images and videos to identifying objects, faces, or handwriting. Besides object detection, this platform can also be used for complex computer vision tasks like Geometry-based monocular or stereo computer vision. - Source: dev.to / 7 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library is used for image and video processing, offering functions for tasks like object detection, filtering, and transformations in computer vision. - Source: dev.to / 8 months ago
View more

What are some alternatives?

When comparing PlantUML and OpenCV, you can also consider the following products

draw.io - Online diagramming application

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

yEd - yEd is a free desktop application to quickly create, import, edit, and automatically arrange diagrams. It runs on Windows, Mac OS X, and Unix/Linux.

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

LucidChart - LucidChart is the missing link in online productivity suites. LucidChart allows users to create, collaborate on, and publish attractive flowcharts and other diagrams from a web browser.

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

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