Synthetic-data Libraries

5 Components & Libraries

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Synthetic-data Libraries

Mimesis is a powerful Python library that empowers developers to generate massive amounts of synthetic data efficiently.

To install mimesis, simply use pip: It is divided into several sections: You can improve it by sending pull requests to this repository.

A procedural Blender pipeline for photorealistic training image generation

A procedural Blender pipeline for photorealistic rendering. The simplest way to install blenderproc is via pip: Alternatively, if you need to make changes to blenderproc or you want to make use of th…

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

Genalog has various capabilities: The aim of this project is to provide a complete solution for generating synthetic images from any text data rich in natural language and to imitate most of OCR nois…

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

More installation instructions can be found in the docs: This release of zpy is under the GPLv3 license, a free copyleft license used by Blender. TLDR: Its free, use it!

medigan - A Python Library of Pretrained Generative Models for Medical Image Synthesis

See below how medigan can be run from the command line to generate synthetic medical images. Model information can be found in: To install the current release, simply run: Or, alternatively via conda…

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