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VGG Image Annotator (VIA) VS Playment

Compare VGG Image Annotator (VIA) VS Playment and see what are their differences

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VGG Image Annotator (VIA) logo VGG Image Annotator (VIA)

VGG Image Annotator is a simple and standalone manual annotation software for image, audio and video. VIA runs in a web browser and does not require any installation or setup.

Playment logo Playment

Playment is a fully-managed solution offering training data for AI, transcription, data collection and enrichment services at scale.
  • VGG Image Annotator (VIA) Landing page
    Landing page //
    2022-09-08
  • Playment Landing page
    Landing page //
    2023-07-22

VGG Image Annotator (VIA)

Website
robots.ox.ac.uk
Pricing URL
-
Release Date
-
Edit details

Playment

Website
playment.io
Pricing URL
Official Playment Pricing
Release Date
2015 January
Startup details
Country
India
State
Karnataka
City
Bengaluru
Founder(s)
Ajinkya Malasane
Employees
10 - 19
Edit details

VGG Image Annotator (VIA) videos

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Playment videos

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EARN 💲20 PER DAY BY PLAYMENT APP |WITH PAYMENT PROOF|

More videos:

  • Review - Playment : Polygon Tool Training
  • Demo - Playment for User Generated Content(UGC) Moderation Demo

Category Popularity

0-100% (relative to VGG Image Annotator (VIA) and Playment)

VGG Image Annotator (VIA)

Playment

Image Annotation
17 17%
Image Annotation
83% 83
Data Labeling
8 8%
Data Labeling
92% 92
Data Science And Machine Learning
26 26%
Data Science And Machine Learning
74% 74
AI
16 16%
AI
84% 84

User comments

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What are some alternatives?

When comparing VGG Image Annotator (VIA) and Playment, you can also consider the following products

CrowdFlower - Enterprise crowdsourcing for micro-tasks

Labelbox - Build computer vision products for the real world

Universal Data Tool - Machine learning, data labeling tool, computer vision, annotate-images, classification, dataset

CloudFactory - Human-powered Data Processing for AI and Automation

Amazon Mechanical Turk - The online market place for work.

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

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