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Description
The premier platform designed for the complete computer vision process allows you to evolve from image annotation to precise neural networks at speeds up to ten times quicker. Utilizing our exceptional data labeling tools, you can convert your images, videos, and 3D point clouds into top-notch training data. This enables you to train your models, monitor experiments, visualize results, and consistently enhance model predictions, all while constructing custom solutions within a unified environment. Our self-hosted option ensures data confidentiality, offers robust customization features, and facilitates seamless integration with your existing technology stack. This comprehensive solution for computer vision encompasses multi-format data annotation and management, large-scale quality control, and neural network training within an all-in-one platform. Crafted by data scientists for their peers, this powerful video labeling tool draws inspiration from professional video editing software and is tailored for machine learning applications and beyond. With our platform, you can streamline your workflow and significantly improve the efficiency of your computer vision projects.
Description
T-Rex Label is a sophisticated annotation tool that caters to intricate scenario labeling across diverse sectors. It stands out as the preferred choice for individuals looking to enhance their workflows and generate superior datasets with ease. By utilizing visual prompts, T-Rex enables the rapid prediction of multiple bounding boxes simultaneously, making it particularly suitable for annotating scenes that are complex and densely packed. With its remarkable zero-shot detection feature, T-Rex facilitates the annotation of intricate scenes across various industries without the need for fine-tuning, thereby supporting a wide range of applications from agriculture to logistics and more. This tool aids an increasing number of algorithm engineers and researchers in accelerating their annotation processes, fostering the development of high-quality datasets. Furthermore, T-Rex2 marks a notable advancement towards more versatile and adaptable object detection, harnessing the synergistic strengths of both language and visual inputs, thereby expanding its utility in the field. The evolution of T-Rex not only enhances productivity but also sets a new standard in the realm of data annotation technology.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Supervisely
Founded
2017
Country
United States
Website
supervise.ly/
Vendor Details
Company Name
T-Rex Label
Country
United States
Website
trexlabel.com
Product Features
Computer Vision
Blob Detection & Analysis
Building Tools
Image Processing
Multiple Image Type Support
Reporting / Analytics Integration
Smart Camera Integration
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
Product 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