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Qubole VS Computer Vision Annotation Tool (CVAT)

Compare Qubole VS Computer Vision Annotation Tool (CVAT) and see what are their differences

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Qubole logo Qubole

Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

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

Powerful and efficient Computer Vision Annotation Tool (CVAT) - opencv/cvat
  • Qubole Landing page
    Landing page //
    2023-06-22
  • Computer Vision Annotation Tool (CVAT) Landing page
    Landing page //
    2023-08-26

Qubole videos

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Fast and Cost Effective Machine Learning Deployment with S3, Qubole, and Spark

More videos:

  • Review - Migrating Big Data to the Cloud: WANdisco, GigaOM and Qubole
  • Review - Democratizing Data with Qubole

Computer Vision Annotation Tool (CVAT) videos

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Computer Vision Annotation Tool (CVAT): annotation mode

Category Popularity

0-100% (relative to Qubole and Computer Vision Annotation Tool (CVAT))

Qubole

Computer Vision Annotation Tool (CVAT)

Data Dashboard
100 100%
Data Dashboard
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Big Data
100 100%
Big Data
0% 0
AI
0 0%
AI
100% 100

User comments

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Social recommendations and mentions

Based on our record, Computer Vision Annotation Tool (CVAT) seems to be more popular. It has been mentiond 14 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.

Qubole mentions (0)

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

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: almost 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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What are some alternatives?

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

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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

MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming

Labelbox - Build computer vision products for the real world

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

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

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