Software Alternatives, Accelerators & Startups
Register | Login

Chart.js VS OpenCV

Compare Chart.js VS OpenCV and see what are their differences

Electe
Discover Electe, our data analytics platform dedicated to SMEs. Don't let your data go unused, take your business into the future! 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

Chart.js logo Chart.js

Easy, object oriented client side graphs for designers and developers.

OpenCV logo OpenCV

OpenCV is the world's biggest computer vision library
  • Chart.js Landing page
    Landing page //
    2023-03-13
  • OpenCV Landing page
    Landing page //
    2023-07-29

Chart.js features and specs

  • Open Source
    Chart.js is open source and free to use, which makes it accessible for both personal and commercial projects without any licensing costs.
  • Ease of Use
    Chart.js is known for its simple and easy-to-use API. Developers can quickly create charts by just including the library and writing minimal JavaScript.
  • Lightweight
    The library is relatively lightweight compared to other charting libraries, which helps in maintaining the performance of web applications.
  • Responsive Design
    Charts created with Chart.js are responsive by default, ensuring that they look good on all devices, including desktops, tablets, and mobile phones.
  • Variety of Chart Types
    Chart.js supports a variety of chart types including line, bar, radar, pie, doughnut, and polar area charts, providing flexibility for different data visualization needs.
  • Customization
    Developers can customize the appearance of charts extensively through Chart.js options such as colors, labels, and tooltips.
  • Active Community
    Chart.js has an active community and a strong support base, which means that developers can easily find help, tutorials, and plugins to enhance functionality.

Possible disadvantages of Chart.js

  • Limited Advanced Features
    While Chart.js is good for basic and intermediate charting needs, it may lack some advanced features and customizations offered by more complex charting libraries like D3.js.
  • Performance Issues with Large Datasets
    Chart.js can struggle with performance when dealing with very large datasets or complex visualizations, which can result in slower rendering times.
  • Learning Curve for Customization
    Although the basic usage is straightforward, achieving deeper customizations can involve a steeper learning curve as it requires understanding the underlying JavaScript and options.
  • Limited Interactivity
    Interactivity options with Chart.js are somewhat limited compared to other libraries that offer more advanced interactive features.
  • Dependency on Canvas
    Charts are rendered using the HTML5 canvas element, which may not be as flexible as SVG-based rendering used by some other libraries.

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.

Chart.js videos

+ Add

1.3: Graphing with Chart.js - Working With Data & APIs in JavaScript

More videos:

  • Tutorial - How to Build Ionic 4 Apps with Chart.js

OpenCV videos

+ Add

AI Courses by OpenCV.org

More videos:

  • Review - Practical Python and OpenCV

Category Popularity

0-100% (relative to Chart.js and OpenCV)

Chart.js

OpenCV

Charting Libraries
100 100%
Charting Libraries
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Data Visualization
100 100%
Data Visualization
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Chart.js 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 Chart.js and OpenCV

Chart.js Reviews

6 JavaScript Charting Libraries for Powerful Data Visualizations in 2023
Of the free libraries on this list, ECharts has the widest range of chart types available, second only to D3. Unlike D3, ECharts also ranks highly on the user-friendliness scale, although some users find ApexCharts and Chart.js even easier to use. You can check out some examples of basic charts on ECharts.
Source: embeddable.com
5 top picks for JavaScript chart libraries
Chart.js is a chart library that is available as a client-side JavaScript package. There are also derivatives for other frontend frameworks, like React, Vue, and Angular. It displays the chart on an HTML canvas element.
Source: blog.logrocket.com
Top 10 JavaScript Charting Libraries for Every Data Visualization Need
Chart.js is a simple yet quite flexible JavaScript library for data viz, popular among web designers and developers. It’s a great basic solution for those who don’t need lots of chart types and customization features but want their charts to look neat, clear and informative at a glance.
Source: hackernoon.com
A Complete Overview of the Best Data Visualization Tools
Chart.js uses HTML5 Canvas for output, so it renders charts well across all modern browsers. Charts created are also responsive, so it’s great for creating visualizations that are mobile-friendly.
Source: www.toptal.com
The Best Data Visualization Tools - Top 30 BI Software
Chart.js is better for smaller chart projects. It’s open source and small in size, supporting six different types of charts: bar, line, pie, radar, doughnut, and polar. You can also add or remove any of these 6 types to reduce your footprint. Chart.js uses HTML5 Canvas and ships with polyfills for IE6/7 support. Chart.js offers the ability to create simple charts quickly.
Source: improvado.io

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 Chart.js. While we know about 59 links to OpenCV, we've tracked only 1 mention of Chart.js. 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.

Chart.js mentions (1)

  • Chart library for Svelte?
    Https://chartjs.org works well, but you have to call the update function yourself if you want to do some reactive updates. Source: almost 4 years ago

OpenCV mentions (59)

  • Top Programming Languages for AI Development in 2025
    Ideal For: Computer vision, NLP, deep learning, and machine learning. - Source: dev.to / 11 days 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 / 4 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 / 6 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 / 7 months ago
  • Built in Days, Acquired for $20K: The NuloApp Story
    First of all, OpenCV, an open-source computer vision library, was used as the main editing tool. This is how NuloApp is able to get the correct aspect ratio for smartphone content, and do other cool things like centering the video on the speaker so that they aren't out of frame when the aspect ratio is changed. - Source: dev.to / 8 months ago
View more

What are some alternatives?

When comparing Chart.js and OpenCV, you can also consider the following products

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.

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

Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application

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

Google Charts - Interactive charts for browsers and mobile devices.

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

Loading...