There are 5 repositories under synthetic topic.
A synthetic data generator for text recognition
A procedural Blender pipeline for photorealistic training image generation
A Kubernetes operator for running synthetic checks as pods. Works great with Prometheus!
Official Implementation of SynthTIGER (Synthetic Text Image Generator), ICDAR 2021
Project Page of 'Synthesizing Coupled 3D Face Modalities by Trunk-Branch Generative Adversarial Networks'
Evaluate real and synthetic datasets against each other
Discord RAT: A versatile bot-based C2 tool that can manage multiple clients at once.
KITTI-CARLA: Python scripts to generate the KITTI-CARLA dataset
Synthetic Blender Dataset Production
Synthetic Role-Play Conversation Dataset Generation
PyGrinder: a Python toolkit for grinding data beans into the incomplete for real-world data simulation by introducing missing values with different missingness patterns, including MCAR (complete at random), MAR (at random), MNAR (not at random), sub sequence missing, and block missing
Synthetic population pipeline code for eqasim
Codebase to generate simulated data for OpenSDP project
Generate power grid dynamic simulation data automatically for machine learning applications using Python and Modelica models.
Open Synthea patient data for machine learning and team training.
A generator for unit disk graphs conditioned on concave hull cover.
This repository provides the face analysis by getting 68 Keypoints from the synthetic dataset published by Microsoft
The highly versatile synthetic data generator
Dart builder that reads several input files and writes the merged output to one file.
Mock database activity and run scalable simulations of database load with as little code as necessary
Linear and nonlinear mapping of sea surface waves imaged by synthetic aperture radar
CLI Tool for Synthetic Monitoring to Manage Synthetic Test and Locations Easily
Synthetic controls with disease time series
IFTG (ImageFromTextGenerator) is a Python package that simplifies creating robust datasets for OCR models. Generate images from text, apply over 10 built-in noise effects, and customize fonts and layouts. IFTG supports all languages and offers endless noise combinations, including custom noise creation.