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Supervisely VS s3-lambda

Compare Supervisely VS s3-lambda and see what are their differences

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Supervisely logo Supervisely

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

s3-lambda logo s3-lambda

Lambda functions over S3 objects: each, map, reduce, filter
  • Supervisely Landing page
    Landing page //
    2023-08-06
  • s3-lambda Landing page
    Landing page //
    2022-11-04

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.

s3-lambda features and specs

  • Batch processing of S3 objects
    s3-lambda provides a straightforward way to perform batch operations on large numbers of S3 objects, enabling map, filter, and reduce-style processing over entire S3 buckets or prefixes without writing boilerplate code.
  • Familiar functional API
    The library uses a functional programming paradigm with operations like map, filter, and reduce, making it intuitive for JavaScript developers to process S3 objects using patterns they already know.
  • Built-in concurrency control
    s3-lambda handles parallel processing of S3 objects with configurable concurrency, allowing users to control how many operations run simultaneously and avoid overwhelming AWS resources or hitting rate limits.
  • Context-aware operations
    The library provides a context object within each operation that includes useful metadata about the current object being processed, simplifying access to S3 object properties during transformations.
  • Easy integration with Lambda
    Designed to work seamlessly within AWS Lambda functions, making it straightforward to set up event-driven, serverless pipelines for processing large volumes of S3 data without managing infrastructure.

Possible disadvantages of s3-lambda

  • Unmaintained project
    The repository appears to be no longer actively maintained, with limited recent commits and unresolved issues, which raises concerns about long-term reliability, security patches, and compatibility with newer AWS SDK versions.
  • Limited documentation
    The project's documentation is relatively sparse, lacking comprehensive examples, edge case handling guidance, and detailed API references, which can make it challenging for new users to adopt effectively.
  • AWS SDK version dependency
    The library depends on an older version of the AWS SDK for JavaScript, which may conflict with projects using the newer AWS SDK v3 and could miss out on performance improvements and features in updated SDKs.
  • Limited error handling flexibility
    The built-in error handling mechanisms are relatively basic, and handling partial failures or implementing sophisticated retry logic for individual object operations requires additional custom code from the developer.
  • Narrow scope of functionality
    The library is tightly focused on S3 object processing and does not integrate with other AWS services or provide utilities beyond basic map/filter/reduce operations, limiting its usefulness in more complex data pipeline scenarios.

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.

Analysis of s3-lambda

Overall verdict

  • s3-lambda is a useful Node.js library for performing operations like map, reduce, and filter directly on S3 objects using Lambda, making it good for developers who need efficient, serverless-based batch processing of S3 data without managing infrastructure. It is well suited for smaller to medium projects but may not be actively maintained for enterprise-scale needs.

Why this product is good

  • Simplifies common S3 batch operations (map, filter, reduce) with a clean, functional API
  • Leverages AWS Lambda for scalable, serverless parallel processing of S3 objects
  • Reduces boilerplate code for iterating over and transforming large numbers of S3 objects
  • Open-source and free to use, allowing customization for specific workflows
  • Integrates well with existing AWS infrastructure and Node.js applications

Recommended for

  • Developers building serverless data pipelines on AWS
  • Teams needing to process or transform large sets of S3 objects without provisioning servers
  • Node.js developers looking for a functional programming approach to S3 operations
  • Projects with batch processing needs that fit within Lambda's execution limits
  • Prototyping or small-to-medium scale ETL tasks involving S3 data

Supervisely videos

+ Add

🛠️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

s3-lambda videos

No s3-lambda videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Supervisely and s3-lambda)

Supervisely

s3-lambda

Image Annotation
100 100%
Image Annotation
0% 0
Relational Databases
0 0%
Relational Databases
100% 100
Data Labeling
100 100%
Data Labeling
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100

User comments

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Social recommendations and mentions

Based on our record, Supervisely seems to be more popular. 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.

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: over 3 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 / almost 4 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: about 4 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: about 4 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: about 4 years ago
View more

s3-lambda mentions (0)

We have not tracked any mentions of s3-lambda yet. Tracking of s3-lambda recommendations started around Mar 2021.

What are some alternatives?

When comparing Supervisely and s3-lambda, you can also consider the following products

Labelbox - Build computer vision products for the real world

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

CrowdFlower - Enterprise crowdsourcing for micro-tasks

Amazon Mechanical Turk - The online market place for work.

Playment - Playment is a fully-managed solution offering training data for AI, transcription, data collection and enrichment services at scale.

Labeling AI - Labeling AI is a deep learning-based auto labeling solution that develops and auto-labels custom AI by learning minimal manual labeling data.

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