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What is Prodigy?

Groundbreaking machine teaching has arrived, featuring an incredibly effective annotation tool powered by active learning. Prodigy stands out as a customizable annotation platform so proficient that data scientists can take charge of the annotation process themselves, facilitating quick iterations. The progress seen in current transfer learning technologies enables the creation of high-quality models with minimal examples. By adopting Prodigy, you can fully harness modern machine learning strategies, engaging in a more adaptable approach to data collection. This capability not only speeds up your workflow but also grants you increased independence, resulting in a significant boost in project success rates. Prodigy combines state-of-the-art insights from both machine learning and user experience design, making it exceptionally versatile. Its continuous active learning framework ensures that you only annotate cases where the model exhibits uncertainty, optimizing your time and effort. The web application is not only robust and adaptable but also complies with the most up-to-date user experience standards. What makes Prodigy truly remarkable is its intuitive design: it allows you to focus on one decision at a time, keeping you actively involved—similar to a swipe-right method for data. Furthermore, this streamlined approach enhances the overall enjoyment and effectiveness of the annotation process, making it an invaluable tool for data scientists. As a result, users can expect not just efficiency but also a more satisfying experience while navigating through their annotation tasks.

What is ImgLab?

ImgLab is a free tool designed to simplify the image annotation process for machine learning and artificial intelligence projects. With its intuitive interface, users can annotate images using different types of metadata such as bounding boxes, points, lines, and polygons to emphasize specific features or objects within the images. It supports multiple annotation formats, including COCO, Pascal VOC, and YOLO, ensuring that it works seamlessly with various machine learning models and platforms. Furthermore, ImgLab is capable of managing large image datasets, making it especially useful for addressing complex challenges in machine learning. This range of functionalities makes ImgLab an essential asset for both researchers and developers working in the AI sector. As the demand for effective image annotation tools continues to grow, ImgLab stands out as a reliable choice for enhancing productivity in AI-related tasks.

Media

Media

Integrations Supported

ZenML

Integrations Supported

ZenML

API Availability

Has API

API Availability

Has API

Pricing Information

$490 one-time fee
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Explosion

Date Founded

2016

Company Location

Germany

Company Website

prodi.gy/

Company Facts

Organization Name

ImgLab

Company Website

imglab.in/

Categories and Features

Data Labeling

Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

Categories and Features

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