TextRecognitionDataGenerator

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TextRecognitionDataGenerator is an open-source data & analytics tool that generates synthetic text image samples for training OCR software. It supports various languages and customization options for fonts, backgrounds, and text modifications.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is TextRecognitionDataGenerator?

TextRecognitionDataGenerator is an open-source synthetic data generator designed to create text image samples for training Optical Character Recognition (OCR) software. It allows users to generate custom datasets with various parameters, including different fonts, backgrounds, and text modifications like skewing, blurring, and distortion. The tool supports multiple languages, including non-latin scripts like Chinese and Japanese, and can generate images with handwritten text (experimental). Users can run it via CLI or as a Python module, offering flexibility for integration into training pipelines. It also provides a Docker image for easier deployment, eliminating the need for local installations.

Best used for

Ideal for developers and data scientists who need to create diverse synthetic text image datasets, train OCR software, and test text recognition algorithms. Especially valuable for generating data for languages with limited real-world datasets or for specific visual conditions like handwritten text or distorted images.

Common actions

generate synthetic data

train OCR models

create text datasets

customize image generation

automated workflowlow-code/no-codeopen-sourcedeepfakecollaborationworkflowsgithub copilot"AI Agents"face swapping

Capabilities

Key features

Generate synthetic text images
Support multiple languages
Customize fonts and backgrounds
Apply text skewing
Add text blurring
Distort text images
Output character-level mask

Target Audience

developerdata scientist

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What types of text modifications can be applied to generated images?

TextRecognitionDataGenerator allows for various modifications including skewing, blurring (Gaussian blur), and distortion. Users can also control character spacing, text color ranges, and add a stroke with adjustable width and fill color to the text, enhancing the diversity of the synthetic data.

How can I add support for a new non-latin language?

To add a new non-latin language, you need to create a new folder with its two-letter code, add a .ttf font file, edit `run.py` to include an if statement in `load_fonts()`, and add a text file in `dicts` with the same two-letter code. The tool currently only supports .ttf fonts.

Can I use my own dictionary for text generation?

Yes, you can specify a custom dictionary using the `--dict` argument when running the tool. This allows you to control the specific words and phrases that are randomly chosen and used to generate the text images, tailoring the dataset to your specific needs.

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AI Agents & Automation › AI Frameworks & Infra Coding & Development › Open Source & Models

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