Software Alternatives, Accelerators & Startups

SuperAnnotate VS Supervisely

Compare SuperAnnotate VS Supervisely and see what are their differences

SuperAnnotate logo SuperAnnotate

Empowering Enterprises with Custom LLM/GenAI/CV Models.

Supervisely logo Supervisely

Supervisely helps people with and without machine learning expertise to create state-of-the-art...
  • SuperAnnotate Landing page
    Landing page //
    2023-10-10

SuperAnnotate is the leading platform for building, fine-tuning, iterating, and managing your AI models faster with the highest-quality training data. With advanced annotation and QA tools, data curation, automation features, native integrations, and data governance, we enable enterprises to build datasets and successful ML pipelines. Partner with SuperAnnotate’s expert and professionally managed annotation workforce that can help you quickly deliver high-quality data for building top-performing models.

  • Supervisely Landing page
    Landing page //
    2023-08-06

SuperAnnotate features and specs

  • Activity dashboard
    yes
  • Configurable workflow
  • Data import/export
    yes
  • Performance metrics
    yes
  • Real time analytics
  • Third-party integrations
    yes
  • Collaboration tools
    yes
  • Data visualization
  • Drag and drop
    yes
  • Multiple data sources
  • Reporting/analytics
    yes
  • Task management
    yes
  • Visual analytics
  • Monitoring
  • Real-time monitoring
    yes
  • Secure data storage
    yes
  • Trend analysis
    yes
  • Visual discovery
    yes

Supervisely features and specs

  • Comprehensive Toolset
    Supervisely offers a wide range of tools for image annotation, data management, and deep learning model training, providing a one-stop solution for computer vision projects.
  • Collaborative Platform
    It supports team collaboration with features for sharing projects, annotating data, and reviewing work, making it easier for teams to work together.
  • High Customizability
    Supervisely allows users to create custom plugins and automation scripts, offering flexibility to tailor the platform according to specific project needs.
  • Extensive Dataset Support
    The platform supports a wide variety of data formats and types, including images, videos, and 3D data, making it versatile for different applications.
  • Integrated Machine Learning
    Supervisely integrates machine learning capabilities, enabling users to train models directly on the platform and test them using their own annotated data.

Possible disadvantages of Supervisely

  • Cost
    Supervisely can be expensive, particularly for small teams or individual users, as it primarily targets enterprise customers.
  • Complexity
    Due to the breadth of features and tools, there may be a steep learning curve for new users, making it more challenging to get started quickly without adequate training.
  • Performance Issues
    Some users may experience performance issues, particularly when handling very large datasets or running multiple simultaneous tasks.
  • Cloud Dependency
    While a cloud-based platform offers accessibility advantages, it also means that users are dependent on internet connectivity and may face latency or downtime problems.
  • Limited Offline Features
    Supervisely's offline functionality is limited, which can be a drawback for users who need to work in environments with restricted or unreliable internet access.

Analysis of Supervisely

Overall verdict

  • Overall, Supervisely is a good platform for computer vision projects due to its versatility and ease of use. It offers a complete ecosystem that caters to various stages of the machine learning pipeline, making it an efficient choice for both beginners and experienced practitioners.

Why this product is good

  • Supervisely is considered a robust platform for its comprehensive suite of tools designed for computer vision tasks. It provides capabilities for data labeling, neural network training, and deployment. Its user-friendly interface, collaborative features, and support for a wide range of formats and integrations make it appealing to both individual developers and enterprise teams.

Recommended for

  • Data scientists looking for a comprehensive tool for computer vision.
  • Companies needing a collaborative environment for AI projects.
  • Researchers who require a platform with extensive format support and integrations.
  • Developers wanting an easy-to-use interface for data annotation and model training.

SuperAnnotate videos

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

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Supervisely videos

🛠️Basic annotation overview - Supervisely

More videos:

  • Review - Cars annotation in Supervisely: Polygons vs. AI powered tool
  • Tutorial - Yolo v3 Tutorial #2 - Object Detection Training Part 1 - Create a Supervisely Cluster

Category Popularity

0-100% (relative to SuperAnnotate and Supervisely)
Data Labeling
44 44%
56% 56
Image Annotation
36 36%
64% 64
Data Science And Machine Learning
AI
31 31%
69% 69

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare SuperAnnotate and Supervisely

SuperAnnotate Reviews

Top Video Annotation Tools Compared 2022
In this blog, we’ll quickly explore annotation platforms and the features they offer to help improve the video annotation process. We’ll be looking closely at six big names in the video annotation market: Innotescus, Dataloop, Scale, V7, SuperAnnotate, and Labelbox.
Source: innotescus.io

Supervisely Reviews

We have no reviews of Supervisely yet.
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Social recommendations and mentions

Based on our record, Supervisely should be more popular than SuperAnnotate. It has been mentiond 6 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.

SuperAnnotate mentions (1)

  • data-labeling tools comparison
    Ok, so I tried comparing 4 of the better data annotation tools like dLabel.org, CVAT.com, SuperAnnotate.com and Labelbox.com . I tried them all as thoroughly as I could and I probably missed some things so apologies in advance for that! Let me know what I missed in the comment. Btw, I'm Amir and I've worked most of my data-labeling career at dLabel.org. Source: almost 4 years ago

Supervisely mentions (6)

  • Way to label yolov7 images fast
    Another annotation tool that integrates prediction and training within the application is supervisely supervisely.com., unfortunately it's pretty expensive unless you are satisfied with the community version. I saw that they have an integration for owl-vit, which might be helpful for annotation of animals. https://ecosystem.supervisely.com/apps/serve-owl-vit. Source: about 2 years ago
  • 65 Blog Posts to Learn Data Science
    Hello world. This tutorial is a gentle introduction to building modern text recognition system using deep learning in 15 minutes. It will teach you the main ideas of how to use Keras and Supervisely for this problem. This guide is for anyone who is interested in using Deep Learning for text recognition in images but has no idea where to start. - Source: dev.to / over 2 years ago
  • Bounding Box for Text Annotation
    If they were videos, I would have suggested trying supervise.ly as it has a very good tracking functionality. Source: almost 3 years ago
  • CVAT alternatives for video frame annotation
    Hi, I'm exactly in the same boat like you are. I looked around for a while and the better solutions I found was supervise.ly and CVAT for video annotation. The pricetag on supervisely is pretty high, so I analyzed CVAT for a couple days and was positively surprised. Source: almost 3 years ago
  • Accessing 2022 Machine Learning Imagery from WPI's Photo Album
    Under the WPI Photo Ambum section of the page for FRC field photos (https://www.firstinspires.org/robotics/frc/playing-field#WPIPhotos), they have a section of machine learning imagery. However, this link goes to supervise.ly, the website they use for machine learning. I created an account to attempt to download the images, however, whenever I try to 'clone' the project, it stalls at 0% and gives me an error... Source: almost 3 years ago
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What are some alternatives?

When comparing SuperAnnotate and Supervisely, you can also consider the following products

Labelbox - Build computer vision products for the real world

V7 - Pixel perfect image labeling for industrial, medical, and large scale dataset creation. Create ground truth 10 times faster.

CrowdFlower - Enterprise crowdsourcing for micro-tasks

CloudFactory - Human-powered Data Processing for AI and Automation

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

Hive - Seamless project management and collaboration for your team.