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Description
The Synthetic Data Vault (SDV) is a comprehensive Python library crafted for generating synthetic tabular data with ease. It employs various machine learning techniques to capture and replicate the underlying patterns present in actual datasets, resulting in synthetic data that mirrors real-world scenarios. The SDV provides an array of models, including traditional statistical approaches like GaussianCopula and advanced deep learning techniques such as CTGAN. You can produce data for individual tables, interconnected tables, or even sequential datasets. Furthermore, it allows users to assess the synthetic data against real data using various metrics, facilitating a thorough comparison. The library includes diagnostic tools that generate quality reports to enhance understanding and identify potential issues. Users also have the flexibility to fine-tune data processing for better synthetic data quality, select from various anonymization techniques, and establish business rules through logical constraints. Synthetic data can be utilized as a substitute for real data to increase security, or as a complementary resource to augment existing datasets. Overall, the SDV serves as a holistic ecosystem for synthetic data models, evaluations, and metrics, making it an invaluable resource for data-driven projects. Additionally, its versatility ensures it meets a wide range of user needs in data generation and analysis.
Description
SuperSplat is the premier solution for editing and enhancing 3D Gaussian splats. Its user-friendly interface is equipped with robust selection tools that simplify the cleanup process of your splats. Developed on the advanced PlayCanvas engine runtime and utilizing the PCUI front-end framework, SuperSplat offers a lightweight and efficient visual editing environment that is entirely browser-based. There is no need for downloads or installations, making it incredibly accessible. Operating seamlessly with the widely-used PLY file format, SuperSplat is compatible with any engine of your choice. Thanks to the PlayCanvas engine's capabilities, it can effortlessly manage even the most complex 3D Gaussian splat scenes. Users can easily select splats for removal, as well as translate and rotate their scenes according to their needs. Additionally, you can save your work in PLY, compressed PLY, or SPLAT formats. 3D Gaussian splatting presents an innovative technique for generating photorealistic 3D scenes derived from photogrammetry, yet sometimes the captured splats require adjustments for optimal results. Therefore, SuperSplat emerges as an essential tool for artists and developers looking to refine their visual creations.
API Access
Has API
No
API Access
Has API
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
$15 per month
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
DataCebo
Website
sdv.dev/
Vendor Details
Company Name
PlayCanvas
Founded
2011
Country
United Kingdom
Website
playcanvas.com/products/supersplat
Product Features
Product Features
3D Modeling
2D Drawing
No
Animation
No
Annotations
No
Bill of Materials
No
Character Modeling
No
Collaboration Tools
No
Component Library
No
Data Import / Export
No
For 3D Printing
No
For Architects
No
For Manufacturers
No
Reference Management
No
Simulation
No
