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What is Zastra?

We are set to enhance the platform by adding annotation capabilities specifically designed for segmentation tasks. The Zastra repository will feature cutting-edge algorithms that streamline segmentation processes, thereby improving active learning across various datasets. To support this, we will implement complete end-to-end machine learning operations, which will include dataset and experiment version control, as well as templated pipelines that facilitate model deployment in standard cloud environments and on edge devices. By embedding advancements in Bayesian deep learning within the active learning framework, we aspire to significantly enhance overall performance. Additionally, we will improve the precision of annotations by utilizing specialized architectures like Bayesian CNNs, which will ensure superior outcomes. Our dedicated team has committed considerable time and resources to create this innovative solution tailored to your requirements. While we are consistently adding new features and improvements to the platform, we invite you to participate in a trial run soon! Zastra offers a variety of essential functionalities, such as active learning for object classification, detection, localization, and segmentation across multiple formats, including images, videos, audio, text, and point cloud data. This versatility not only makes Zastra a powerful tool for addressing a wide range of data challenges, but it also positions us well to adapt to future needs in data processing and machine learning advancements.

What is Labelbox?

An efficient platform for AI teams focused on training data is essential for developing effective machine learning models. Labelbox serves as a comprehensive solution that enables the creation and management of high-quality training data all in one location. Furthermore, it enhances your production workflow through robust APIs. The platform features an advanced image labeling tool designed for tasks such as segmentation, object detection, and image classification. Accurate and user-friendly image segmentation tools are crucial when every detail matters, and these tools can be tailored to fit specific requirements, including custom attributes. Additionally, Labelbox includes a high-performance video labeling editor tailored for advanced computer vision applications, allowing users to label video content at 30 frames per second with frame-level precision. It also offers per-frame analytics, which can accelerate model development significantly. Moreover, creating training data for natural language processing has never been simpler, as you can swiftly and effectively label text strings, conversations, paragraphs, or documents with customizable classification options. This streamlined approach enhances productivity and ensures that the training data is both comprehensive and relevant.

Media

Media

Integrations Supported

Integrations Supported

Cogito
Databricks
Diffgram Data Labeling
Innovatiana
Lightly
People For AI
Unremot
Visual Layer
Voxel51

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars

Training Options

Not specified

Company Facts

Organization Name

RoundSqr

Date Founded

2018

Company Location

India

Company Website

www.roundsqr.com/zastra/

Company Facts

Organization Name

Labelbox

Date Founded

2018

Company Location

United States

Company Website

labelbox.com/product/platform

Categories and Features

Data Annotation

Not specified

Data Labeling

Not specified

Image Annotation

Not specified

Video Annotation

Not specified

Categories and Features

AI Fine-Tuning

Not specified

Data Annotation

Not specified

Data Labeling

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

Image Annotation

Not specified

Machine Learning

Not specified

RLHF

Not specified

Video Annotation

Not specified

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