CLSGAN

Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

The Declarative Data Generator

Conditional GAN for generating synthetic tabular data.

A library to model multivariate data using copulas.

Generate relevant synthetic data quickly for your projects. The Databricks Labs synthetic data generator (aka `dbldatagen`) may be used to generate large simulated / synthetic data sets for test, POCs, and other uses in Databricks environments including in Delta Live Tables pipelines

Genalog is an open source, cross-platform python package allowing generation of synthetic document images with custom degradations and text alignment capabilities.

Random dataframe and database table generator

A novel approach for synthesizing tabular data using pretrained large language models

A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.

The DataHelix generator allows you to quickly create data, based on a JSON profile that defines fields and the relationships between them, for the purpose of testing and validation