Grounded-SAM: Marrying Grounding-DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
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Apr 17, 2024 - Jupyter Notebook
Grounded-SAM: Marrying Grounding-DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
A powerful, feature-rich, random test data generator.
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.
Synthetic data generation for tabular data
Conditional GAN for generating synthetic tabular data.
List of useful data augmentation resources. You will find here some not common techniques, libraries, links to GitHub repos, papers, and others.
Deep Convolutional Neural Networks for Musical Source Separation
A library to model multivariate data using copulas.
The Declarative Data Generator
C++ Faker library for generating fake (but realistic) data.
Data generation and property-based testing for Elixir. 🔮
CAIRI Supervised, Semi- and Self-Supervised Visual Representation Learning Toolbox and Benchmark
Random dataframe and database table generator
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
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
MockNeat - the modern faker lib.
A novel approach for synthesizing tabular data using pretrained large language models
Generate strings that match a given regular expression
Genalog is an open source, cross-platform python package allowing generation of synthetic document images with custom degradations and text alignment capabilities.
GRATIS: GeneRAting TIme Series with diverse and controllable characteristics
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