Software Alternatives & Reviews

Computer Vision Annotation Tool (CVAT) VS Scikit-learn

Compare Computer Vision Annotation Tool (CVAT) VS Scikit-learn and see what are their differences

Computer Vision Annotation Tool (CVAT) logo Computer Vision Annotation Tool (CVAT)

Powerful and efficient Computer Vision Annotation Tool (CVAT) - opencv/cvat

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Computer Vision Annotation Tool (CVAT) Landing page
    Landing page //
    2023-08-26
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Computer Vision Annotation Tool (CVAT) videos

Computer Vision Annotation Tool (CVAT): annotation mode

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Category Popularity

0-100% (relative to Computer Vision Annotation Tool (CVAT) and Scikit-learn)
Data Science And Machine Learning
AI
100 100%
0% 0
Data Science Tools
0 0%
100% 100
Data Labeling
100 100%
0% 0

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Reviews

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Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...

Social recommendations and mentions

Based on our record, Scikit-learn should be more popular than Computer Vision Annotation Tool (CVAT). It has been mentiond 28 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.

Computer Vision Annotation Tool (CVAT) mentions (14)

  • Exploring Open-Source Alternatives to Landing AI for Robust MLOps
    Another powerful resource is CVAT, the Computer Vision Annotation Tool which supports both image and video annotations with advanced capabilities such as interpolation of shapes between frames, making it highly suitable for computer vision. - Source: dev.to / 5 months ago
  • Need help identifying a good open source data annotation tool
    CVAT has an open source repo under MIT license: https://github.com/opencv/cvat I've not worked with it directly but it might be a good place to start. Source: 5 months ago
  • Way to label yolov7 images fast
    An open source annotation tool that integrates object detectors is CVAT https://github.com/opencv/cvat however, using your own detector might require some coding. There is an integration for yolov5, but without modification it only loads the pretrained models. Source: about 1 year ago
  • Segment Anything Model is now available in the open-source CVAT
    This integration is currently available in the open-source version of Computer Vision Annotation Tool (http://github.com/opencv/cvat)! Please use it for your computer vision projects to segment images faster. - Source: Hacker News / about 1 year ago
  • How to build computer vision dataset labeling team in-house
    You can download the CVAT docker from a github (Link) and install it yourself, keeping all data local. And here are two options - locally on your personal computer (or company server) or in your own cloud (there are instructions on how to do this with AWS). - Source: dev.to / about 1 year ago
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Scikit-learn mentions (28)

  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 2 months ago
  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 11 months ago
  • WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point
    The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 12 months ago
  • PSA: You don't need fancy stuff to do good work.
    Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago
  • Help on using R for Machine Learning?
    Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
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What are some alternatives?

When comparing Computer Vision Annotation Tool (CVAT) and Scikit-learn, you can also consider the following products

AWS SageMaker Ground Truth - Build highly accurate training datasets using machine learning and reduce data labeling costs by up to 70%.

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

Labelbox - Build computer vision products for the real world

OpenCV - OpenCV is the world's biggest computer vision library

Supervisely - Supervisely helps people with and without machine learning expertise to create state-of-the-art...

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