Synthetic Python Packages

pygrinder

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

table-evaluator

Evaluate real and synthetic datasets against each other

blenderproc

A procedural Blender pipeline for photorealistic training image generation

datasety

CLI tool for dataset preparation: resize, align, caption, shuffle, synthetic, and mask generation.

trdg

A synthetic data generator for text recognition

misata

Python synthetic data generator for realistic multi-table test data, database seeding, and scenario simulation

zpy-zumo

Synthetic data for computer vision. An open source toolkit using Blender and Python.

jabberjay

🦜 Synthetic Voice Detection

synctl

CLI Tool for Synthetic Monitoring to Manage Synthetic Test and Locations Easily

synthtiger

Official Implementation of SynthTIGER (Synthetic Text Image Generator), ICDAR 2021

synpp

Synthetic population pipeline package for eqasim

synthetic-data-kit

Tool for generating high quality Synthetic datasets

blendersynth

Synthetic Blender Dataset Production

synthetic-face-masks

A Python library for generating synthetic face mask datasets by mixing facial regions

nhssynth

Package to accompany P41

bhepop2

Synthetic population enrichment from aggregated data

synloc

A Python package to create synthetic data from locally estimated distributions

iftg

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.

nrel-shift

Python package for developing power distribution model using opensource data.

pycorruptor

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

datahub-core

DataHub - Synthetic data library

wordcanvas-docsaid

Generating text with custom fonts and styles.

datahub-core-grovesy

Synthetic data generation tools for financial markets

db-load-generator

Mock database activity and run scalable simulations of database load with as little code as necessary