Software Alternatives, Accelerators & Startups
Register | Login

Eva Design System VS OpenCV

Compare Eva Design System VS OpenCV and see what are their differences

ScreenshotMAX
The all-in-one Screenshot API for developers: capture websites, generate PDFs, record videos, and automate it all with powerful, scalable infrastructure. No browser setup, no hassle. Just clean results, fast. featured
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Eva Design System logo Eva Design System

A free customizable design system

OpenCV logo OpenCV

OpenCV is the world's biggest computer vision library
  • Eva Design System Landing page
    Landing page //
    2022-07-16
  • OpenCV Landing page
    Landing page //
    2023-07-29

Eva Design System features and specs

  • Customization Flexibility
    Eva Design System offers a high degree of customization, allowing developers and designers to easily adjust themes and components to match specific brand guidelines.
  • Comprehensive Component Library
    The system provides a wide range of pre-designed components, making it easier and faster to build applications with consistent design.
  • Open Source
    Being open-source, Eva Design System allows for community contributions and ensures that it can be freely used and shared, fostering a collaborative environment for improvement.
  • Styled with Theme Variables
    Eva uses theme variables extensively, which facilitates skinning and theming applications, ensuring a unified look and feel across different components and screens.
  • Built-in Dark Mode
    Eva Design System comes with built-in support for dark mode, making it easier for developers to implement this feature without additional complexity.

Possible disadvantages of Eva Design System

  • Learning Curve
    Due to its comprehensive nature and customization options, there may be a steep learning curve for new users who are unfamiliar with the system.
  • Documentation Gaps
    While it is generally well-documented, there can be occasional gaps in the documentation that may hinder smooth implementation or require users to seek additional help.
  • Dependency Management
    Managing dependencies can become complex, especially when integrating Eva Design System with other libraries or frameworks, potentially leading to conflicts or additional overhead.
  • Performance Overhead
    The extensive customization and theming options, while beneficial, may also introduce some performance overhead, particularly in large-scale applications.
  • Community Size
    Compared to more popular design systems, Eva's community is relatively smaller, which may result in fewer third-party integrations, plugins, or community-driven solutions.

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 Eva Design System

Overall verdict

  • Eva Design System is a highly recommended choice for teams looking for a modern and cohesive design language that can accelerate development and ensure design consistency across projects.

Why this product is good

  • Eva Design System is considered good because it offers a comprehensive and consistent framework for building user interfaces that are visually pleasing and user-friendly. It provides a customizable design language, a collection of reusable UI components, and detailed documentation that can help streamline the design and development process. Additionally, it is open-source, which allows for community contributions and makes it adaptable to various project needs.

Recommended for

    Eva Design System is ideal for UI/UX designers, front-end developers, and product teams who want a flexible and robust system for creating applications with a consistent look and feel. It is especially useful for those working on cross-platform projects, as it provides components and guidelines that work well across different environments.

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

Eva Design System videos

No Eva Design System videos yet. You could help us improve this page by suggesting one.

Add video

OpenCV videos

+ Add

AI Courses by OpenCV.org

More videos:

  • Review - Practical Python and OpenCV

Category Popularity

0-100% (relative to Eva Design System and OpenCV)

Eva Design System

OpenCV

Design Tools
100 100%
Design Tools
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Prototyping
100 100%
Prototyping
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Eva Design System and OpenCV. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare Eva Design System and OpenCV

Eva Design System Reviews

We have no reviews of Eva Design System yet.
Be the first one to post

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 seems to be a lot more popular than Eva Design System. While we know about 60 links to OpenCV, we've tracked only 1 mention of Eva Design System. 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.

Eva Design System mentions (1)

  • Dark Mode for Developers
    Based on the EVA Design System, the Nebular library is one of the best UI libraries for Angular. Nebular provides inbuilt, customizable themes like the default theme, cosmic theme, dark theme, etc. The mobile version of Nebular, called UI Kitten, also supports the dark theme. - Source: dev.to / over 3 years ago

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 Eva Design System and OpenCV, you can also consider the following products

Ant Design System for Figma - A large library of 2100+ handcrafted UI components

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

Design Systems Repo - A collection of design system examples and resources

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

Fabrx.co - Create the UI Kits, Bootstrap 5 or HTML Dashboards that you need in minutes. Have some design sense to spare? Fabrx will help you tackle even the trickiest of projects.

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

Loading...