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OpenCV VS DataMelt

Compare OpenCV VS DataMelt and see what are their differences

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OpenCV logo OpenCV

OpenCV is the world's biggest computer vision library

DataMelt logo DataMelt

DataMelt (DMelt), a free mathematics and data-analysis software for scientists, engineers and students.
  • OpenCV Landing page
    Landing page //
    2023-07-29
  • DataMelt Landing page
    Landing page //
    2019-07-18

DataMelt is a Java program for statistics, general data analysis and data visualization. The program is often termed "computational platform" since it can be used with different programming languages (Java, Python, Groovy..). DataMelt is not limited to a single programming language. The program is used for numeric computation, statistics, analysis of large data volumes ("big data") and scientific visualization. Full description: https://handwiki.org/wiki/Software:DataMelt

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.

DataMelt features and specs

  • Versatility
    DataMelt supports a wide range of programming languages including Java, Jython, Groovy, and JRuby, making it versatile for users familiar with different coding environments.
  • Rich Libraries
    It offers a comprehensive set of scientific libraries for numerical computation, data analysis, and visualization, which can be beneficial for complex scientific research and data processing tasks.
  • Cross-Platform
    DataMelt is platform-independent, running on any operating system that supports Java, such as Windows, macOS, and Linux. This makes it accessible to a wide audience.
  • Integrated Development Environment
    DataMelt provides a powerful IDE that integrates coding, plotting, and visualization tools, streamlining the workflow for developers and researchers.
  • Free and Open Source
    The core functionality of DataMelt is available for free, which can be appealing to individuals and organizations looking for budget-friendly computational tools.

OpenCV videos

+ Add

AI Courses by OpenCV.org

More videos:

  • Review - Practical Python and OpenCV

DataMelt videos

No DataMelt videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to OpenCV and DataMelt)

OpenCV

DataMelt

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Technical Computing
0 0%
Technical Computing
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Numerical Computation
0 0%
Numerical Computation
100% 100

Questions and Answers

As answered by people managing OpenCV and DataMelt.

How would you describe your primary audience?

DataMelt's answer:

students and data scientists

What's the story behind your product?

DataMelt's answer:

DataMelt has its roots in particle physics where data mining is a primary task. It was created as Software:jHepWork project in 2005 and it was initially written for data analysis for particle physics.

What makes your product unique?

DataMelt's answer:

Multiplatform. Supports multiple programming languages: Java, Python (Jython), Groovy, Ruby

Why should a person choose your product over its competitors?

DataMelt's answer:

Large database of examples and code snippets https://datamelt.org/code/

Who are some of the biggest customers of your product?

DataMelt's answer:

Students at universities and data scientists.

Which are the primary technologies used for building your product?

DataMelt's answer:

Java (JDK any new new release including JDK20)

User comments

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

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

DataMelt Reviews

  1. J.Mayear
    Great 3D graphics

    I like this DataMelt analysis program since it has many 2D/3D visualisation and a massive number of practical examples

Social recommendations and mentions

Based on our record, OpenCV seems to be more popular. It has been mentiond 59 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.

OpenCV mentions (59)

  • Top Programming Languages for AI Development in 2025
    Ideal For: Computer vision, NLP, deep learning, and machine learning. - Source: dev.to / 12 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 / 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 / 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

DataMelt mentions (0)

We have not tracked any mentions of DataMelt yet. Tracking of DataMelt recommendations started around Mar 2021.

What are some alternatives?

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

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

LabPlot - LabPlot is a KDE-application for interactive graphing and analysis of scientific data.

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

SciDaVis - SciDAVis is a free application for Scientific Data Analysis and Visualization.

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

RJS Graph - RJS Graph is an artificial intelligence-based data management platform that allows users or developers to organize the data by manipulating the binaries, scientific, mathematical, and other insights with accurate results.

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