OpenCV VS DataMelt
Compare OpenCV VS DataMelt and see what are their differences
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives.
featured
OpenCV
Scikit-learn
Pandas
NumPy
Dataiku
Exploratory
htm.java
Figure Eight
DataMelt
SciDaVis
LabPlot
RJS Graph
Aveloy Graph
IGOR Pro
DPlot
OriginPro
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
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DataMelt's answer:
students and data scientists
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.
DataMelt's answer:
Multiplatform. Supports multiple programming languages: Java, Python (Jython), Groovy, Ruby
DataMelt's answer:
Large database of examples and code snippets https://datamelt.org/code/
DataMelt's answer:
Students at universities and data scientists.
DataMelt's answer:
Java (JDK any new new release including JDK20)
I like this DataMelt analysis program since it has many 2D/3D visualisation and a massive number of practical examples
Based on our record, OpenCV seems to be more popular. It has been mentiond 51 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.
Open the camera feed — and use the OpenCV library for real-time computer vision processing. - Source: dev.to / 16 days ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 6 months ago
You might be able to achieve this with scripting tools like AutoHotkey or Python with libraries for GUI automation and image recognition (e.g., PyAutoGUI https://pyautogui.readthedocs.io/en/latest/, OpenCV https://opencv.org/). Source: 6 months ago
- [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 10 months ago
I came across a very interesting [project]( (4) Mckay Wrigley on Twitter: "My goal is to (hopefully!) add my house to the dataset over time so that I have an indoor assistant with knowledge of my surroundings. It’s basically just a slow process of building a good enough dataset. I hacked this together for 2 reasons: 1) It was fun, and I wanted to…" / X ) made by Mckay Wrigley and I was wondering what's the easiest... Source: 10 months ago
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
SciDaVis - SciDAVis is a free application for Scientific Data Analysis and Visualization.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
LabPlot - LabPlot is a KDE-application for interactive graphing and analysis of scientific data.
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.