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Description
LabelMe aims to offer an online platform for annotating images, facilitating the creation of image databases for research in computer vision. By utilizing the annotation tool, users can actively contribute to the growing database. Images can be systematically organized into collections, with the flexibility to create nested collections akin to folders. When a user downloads their database, the organization of collections will reflect this folder structure. Users can also upload images to their collections and annotate them using the LabelMe tool. Furthermore, unlisted collections allow for viewing by anyone with access to the specific URL, although they won't be featured among public folders. Ultimately, LabelMe's objective is to ensure that both images and annotations are made accessible to the research community without any limitations, fostering collaboration and innovation. This commitment to open access highlights the importance of shared resources in advancing computer vision research.
Description
Segments.ai provides a robust solution for labeling multi-sensor data, combining 2D and 3D point cloud labeling into a unified interface. It offers powerful features like automated object tracking, smart cuboid propagation, and real-time interpolation, allowing users to label complex data more quickly and accurately. The platform is optimized for robotics, autonomous vehicle, and other sensor-heavy industries, enabling users to annotate data in a more streamlined way. By fusing 3D data with 2D images, Segments.ai enhances labeling efficiency and ensures high-quality data for model training.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Google Cloud Platform
Hugging Face
Microsoft Azure
PyTorch
Python
TensorFlow
Integrations
Amazon Web Services (AWS)
Google Cloud Platform
Hugging Face
Microsoft Azure
PyTorch
Python
TensorFlow
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
LabelMe
Website
labelme.csail.mit.edu/Release3.0/
Vendor Details
Company Name
Segments.ai
Founded
2020
Country
Belgium
Website
segments.ai
Product Features
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