Software Alternatives, Accelerators & Startups

Lichess VS OpenCV

Compare Lichess VS OpenCV and see what are their differences

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Lichess logo Lichess

The complete chess experience, play and compete in tournaments with friends others around the world.

OpenCV logo OpenCV

OpenCV is the world's biggest computer vision library
  • Lichess Landing page
    Landing page //
    2023-01-04
  • OpenCV Landing page
    Landing page //
    2023-07-29

Lichess features and specs

  • Free to Use
    Lichess is completely free to use, with no hidden fees or subscription models required to access its features.
  • Open Source
    The platform is open-source, allowing anyone to contribute to its development or customize it according to their needs.
  • Ad-Free
    Lichess does not run advertisements, providing a cleaner and more enjoyable user experience.
  • Variants
    Offers a wide range of chess variants like Crazyhouse, Chess960, and Atomic, catering to diverse player interests.
  • Community Features
    Features strong community elements such as forums, tournaments, and team play, enhancing social interaction.
  • Analysis Tools
    Provides powerful game analysis tools, including Stockfish integration, to help players improve their skills.
  • Accessibility
    The platform has a clean and intuitive interface that is accessible to both beginners and experienced players.
  • Mobile Apps
    Lichess offers mobile applications for both iOS and Android, allowing users to play and learn chess on the go.

Possible disadvantages of Lichess

  • No Official Recognition
    Lichess is not officially recognized by the major chess organizations, which might be a limitation for professional players.
  • Lesser User Base Compared to Competitors
    Although it has a strong community, its user base is smaller when compared to competitors like Chess.com.
  • Limited Social Features
    Lacks some of the advanced social features found on other platforms, such as comprehensive user profiles and social media integration.
  • Server Issues
    Occasionally faces server reliability issues during peak times, which can disrupt gameplay.
  • Learning Resources
    Although there are learning resources available, they are not as extensive or structured as those found on some other platforms.

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 Lichess

Overall verdict

  • Lichess.org is an excellent platform for playing, learning, and improving in chess. It provides a high-quality, ad-free experience that is accessible to everyone, making it a favorite among many chess players worldwide.

Why this product is good

  • Lichess.org is considered good because it offers a wide range of features for chess enthusiasts of all levels, including online play, puzzles, tournaments, studies, and more. It is completely free, open source, and does not contain ads. The platform supports various time controls and chess variants, which makes it versatile for different preferences. It also has a strong community and active development, ensuring continuous improvements and new features.

Recommended for

  • Beginners looking to learn and improve their chess skills
  • Casual players interested in playing games at their convenience
  • Advanced players seeking competitive matches and analysis tools
  • Chess enthusiasts who enjoy exploring different variants of chess
  • Coaches and teachers who want resources for instructing students

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

Lichess videos

Review of LiChess, Chess.com, ChessClub, ICC, Playchess, chesscube Reviewed!

More videos:

  • Review - Learning from your mistakes - Lichess has best online chess features and it is free!
  • Review - Introduction to Game Analysis on Lichess

OpenCV videos

AI Courses by OpenCV.org

More videos:

  • Review - Practical Python and OpenCV

Category Popularity

0-100% (relative to Lichess and OpenCV)
Chess
100 100%
0% 0
Data Science And Machine Learning
Games
100 100%
0% 0
Data Science Tools
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 Lichess and OpenCV

Lichess Reviews

Chess.com vs Lichess.org
Chess.com and Lichess.org - just “Lichess” from here on; pronounced as lee-chess - are the two most popular chess servers on the internet.

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.
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.

Social recommendations and mentions

Based on our record, Lichess seems to be a lot more popular than OpenCV. While we know about 912 links to Lichess, we've tracked only 60 mentions of OpenCV. 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.

Lichess mentions (912)

  • Ask HN: What are you working on? (May 2025)
    I'm a big chess buff, and will say that the hard part is not making an engine (which is hard!), but making an engine that plays poorly, well. What I mean is: engines are very smart and better than the best human. When you make a "dumb" engine, you are telling a chess god to intentionally make mistakes. The mistakes they make, however, are not the same mistakes a beginner chess player would make. Today, beginners... - Source: Hacker News / 5 days ago
  • PlayQuoridor: A Free, Open-Source Real-Time Quoridor Server
    Read about it more here: https://lichess.org/@/Neodimi/blog/playquoridor-a-free-open-source-real-time-quoridor-server/qHDnpxlq. - Source: Hacker News / 3 months ago
  • Implementing zen mode in React
    Zen mode is a popular UX pattern that creates a distraction-free experience for application users. It's a simple approach where part of application interface is hidden on user's demand. I have encountered this mode in applications where the main functions are based on focus and tranquility. One of them is Lichess, the second chess platform in the World. I am a chess enthusiast and I am trying (with poor results)... - Source: dev.to / 4 months ago
  • Mastering the Isolated Queen Pawn (IQP)
    Https://lichess.org is an excellent open source chess server with plenty of learning resources for pure beginners. As you progress learning resources sadly get more and more expensive indeed. Not to mention the cost of tournaments (travel and accomodation expenses add up very quickly). - Source: Hacker News / 5 months ago
  • Analyzing the World Chess Championship 2024: Empirical Synthesized Approach
    You don't have a good grasp of data analysis then. You used the data to tell yourself a story "the experts are biased!, not to gain a real deeper understanding". This story should already be suspect because the experts, when commentating, had access to the data you looked at. The eval bar was always there. But they interpreted it. Your assumption seems to be that by calculating some trivial statistics and not... - Source: Hacker News / 5 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 / 17 days 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 / 5 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 Lichess and OpenCV, you can also consider the following products

Chess.com - Play chess on Chess.com

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

Chessvia.ai - Chessvia AI offers a revolutionary chess experience with Chessy, your personal AI chess coach that speaks, listens, and adapts to your style.

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

Chessmaster - Chessmaster is a chess playing computer game series which is now owned and developed by Ubisoft.

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