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What is Hive Data?

Create training datasets for computer vision models through our all-encompassing management solution, as we recognize that the effectiveness of data labeling is vital for developing successful deep learning applications. Our goal is to position ourselves as the leading data labeling platform within the industry, allowing enterprises to harness the full capabilities of AI technology. To facilitate better organization, categorize your media assets into clear segments. Use one or several bounding boxes to highlight specific areas of interest, thereby improving detection precision. Apply bounding boxes with greater accuracy for more thorough annotations and provide exact measurements of width, depth, and height for a variety of objects. Ensure that every pixel in an image is classified for detailed analysis, and identify individual points to capture particular details within the visuals. Annotate straight lines to aid in geometric evaluations and assess critical characteristics such as yaw, pitch, and roll for relevant items. Monitor timestamps in both video and audio materials for effective synchronization. Furthermore, include annotations of freeform lines in images to represent intricate shapes and designs, thus enriching the quality of your data labeling initiatives. By prioritizing these strategies, you'll enhance the overall effectiveness and usability of your annotated datasets.

What is Florence-2?

Florence-2-large is an advanced vision foundation model developed by Microsoft, aimed at addressing a wide variety of vision and vision-language tasks such as generating captions, recognizing objects, segmenting images, and performing optical character recognition (OCR). It employs a sequence-to-sequence architecture and utilizes the extensive FLD-5B dataset, which contains more than 5 billion annotations along with 126 million images, allowing it to excel in multi-task learning. This model showcases impressive abilities in both zero-shot and fine-tuning contexts, producing outstanding results with minimal training effort. Beyond detailed captioning and object detection, it excels in dense region captioning and can analyze images in conjunction with text prompts to generate relevant responses. Its adaptability enables it to handle a broad spectrum of vision-related challenges through prompt-driven techniques, establishing it as a powerful tool in the domain of AI-powered visual applications. Additionally, users can find this model on Hugging Face, where they can access pre-trained weights that facilitate quick onboarding into image processing tasks. This user-friendly access ensures that both beginners and seasoned professionals can effectively leverage its potential to enhance their projects. As a result, the model not only streamlines the workflow for vision tasks but also encourages innovation within the field by enabling diverse applications.

Media

Media

Integrations Supported

Apache Atlas
Hive AutoML
Quickwork
Style Intelligence
Taxi for Email
Toad Intelligence Central
Wyn Enterprise
bipp

Integrations Supported

API Availability

Has API

API Availability

Pricing Information

$25 per 1,000 annotations

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Hive

Date Founded

2013

Company Location

United States

Company Website

thehive.ai/data-labeling

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

huggingface.co/microsoft/Florence-2-large

Categories and Features

AI Vision Models

Not specified

Computer Vision

Blob Detection & Analysis
Building Tools
Image Processing
Multiple Image Type Support
Reporting / Analytics Integration
Smart Camera Integration

Data Annotation

Not specified

Data Labeling

Labeling Automation
Labeling Quality
SDK
Supports Audio Files
Team Collaboration

Image Annotation

Not specified

Image Recognition

Not specified

Video Annotation

Not specified

Categories and Features

AI Vision Models

Not specified

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