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Which is more popular?
Based on our record, OpenCV
should be more popular than Vim.
It has been mentioned 63 times since March 2021.
social mentions
10 vs 63
Text Editors popularity
100% vs 0%
alternatives listed
240+ vs 206
Base details
Website, pricing, platforms and company facts side by side.
Efficiency Once learned, Vim can significantly speed up text editing with its modal editing, keyboard shortcuts, and commands that allow for quick navigation and manipulation of text.
Lightweight Vim is a very lightweight editor, consuming minimal system resources, making it highly performant even on systems with lower specifications.
Customizability Vim is highly configurable and extensible through plugins and user-defined settings, allowing users to tailor the editor to their specific needs.
Ubiquity Vim is available on almost every Unix-like system and even on Windows, making it a ubiquitous tool that you can rely on being available in most environments.
Support for Multiple Programming Languages Vim supports a wide range of programming languages out of the box and offers syntax highlighting, which can be enhanced through plugins.
Powerful Search and Replace Vim offers robust searching and replacing functionalities, including support for regular expressions, which can be a powerful tool for developers.
Possible disadvantages
Steep Learning Curve Vim's modal editing and extensive set of commands can be daunting for new users, requiring significant time and effort to master.
Minimal Default Config The default configuration of Vim is quite minimalistic, which may necessitate additional setup and customization to meet modern development needs.
Limited GUI Vim primarily operates in a terminal, and while there are graphical variants like GVim, they are not as feature-rich or user-friendly as modern GUI editors.
Plugin Management While Vim is highly extensible, managing and configuring plugins can be cumbersome compared to more modern editors that offer integrated plugin management.
Inconsistent Behavior Across Platforms There may be inconsistencies in behavior or available features of Vim across different operating systems, which can complicate its use in certain environments.
Lack of Integrated Modern Features Vim lacks some modern IDE features like integrated debugging, advanced code introspection, and refined autocompletion, which often require third-party plugins to achieve.
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
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
An editorial look at what each product does well and who it suits.
VimOpenCV
Overall verdict
Yes, Vim is a good text editor, especially for users who invest the time to learn its powerful commands and features. Its steep learning curve may be challenging initially, but once mastered, it significantly enhances productivity.
Why this product is good
Vim is considered a powerful text editor because of its efficiency and versatility. It offers extensive features, such as syntax highlighting, a robust plugin system, and support for numerous programming languages. Vim is highly configurable, enabling users to customize its environment to fit their needs. It is particularly appreciated for its speed and the ability to perform complex text manipulations using simple commands.
Recommended for
Vim is recommended for programmers, developers, and system administrators who require a highly efficient and customizable text editing experience. It is especially useful for those who work extensively in terminal environments or need a quick, resource-light text editor for remote systems.
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
Vim offers a variety of features like split windows, macros, and extensive customization options. It has a steep learning curve, but once you master it, you’ll be amazed at the speed and productivity it brings to your...
It’s tough to say which developers would enjoy Vim as a text editor. It’s an old system with an outdated interface. Yet, it still has the charm and powerful feature-set that the average developer needs. I would...
The entire installation process is perfectly documented on their Sourceforge page, which you must definitely pay a visit. There is another standalone Vim software, known as the gVim that brings a GUI-based interface...
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...
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....
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...
Recommendations tracked on public social media and blogs since March 2021.
Vim10 mentionsOpenCV63 mentions
regular Vim has lua?!
Lua is quite small, encouraging distros to include it. The ubuntu gvim has, and the gvim AppImage linked from vim.org does. The default Makefile from github is set up to not include it, but you can uncomment one line there to get it.
Source:
over 3 years ago
is there a way to make highlighted text persistent after quit when using something like [match Search /\%'.line('.').'l/] ?
I've not used vimwiki locally (tho I'm old enough to remember the Vim wiki on vim.org :), but I think what you are wanting to do is extend vimwiki's syntax file. I presume it installs one at $VIMRUNTIM/syntax or or ~/.vim/syntax. If...
Source:
almost 4 years ago
Vim.org has 242k total visitors, tailwindcss.com has 4.4m, planetscale.com has 412k, jpl.nasa.gov has 2.6m, all built with Tailwind, all several years younger than Vim's website. Unnecessary comparison, unnecessary defence. It's a...
Source:
about 4 years ago
Every promising candidate gets checked against the query frame with plain old computer vision in OpenCV:.
- Source: dev.to
/
27 days ago
Computer vision for code: What PVS-Studio saw in OpenCV
OpenCV is the world's largest open-source computer vision library, supported by the non-profit organization, Open Source Computer Vision Foundation. It offers a wide range of algorithms that cover a variety of tasks, from basic image...
- Source: dev.to
/
11 months ago
Google's Gemini and other multimodal models also fit here, especially for mixed-input apps. James Allsopp, Founder of Ask Zyro, suggests, "For anything involving images or mixed inputs, tools like Claude 3 Opus (great for handling long...
- Source: dev.to
/
about 1 year ago
Sublime Text is a sophisticated text editor for code, html and prose - any kind of text file. You'll love the slick user interface and extraordinary features. Fully customizable with macros, and syntax highlighting for most major languages.
Sublime Text
VS Code
Notepad++
GNU Emacs
Microsoft Visual Studio
Netbeans
IntelliJ IDEA
Pandas
Scikit-learn
NumPy
Dataiku
Exploratory
htm.java
Figure Eight
