WordCanvas
The core functionality of this project is the "Text-to-Image Generation Tool", named WordCanvas.
📄️ Introduction
In the current field of Optical Character Recognition (OCR), the accuracy of models is contingent upon the quality and diversity of datasets.
📄️ Installation
Currently, there is no package available on PyPI, and there are no plans to provide one in the near future. To use this project, you must clone it directly from Github and then install the required dependencies.
📄️ QuickStart
Getting started is often the hardest part, so let's keep it simple.
📄️ Advanced
Beyond basic usage, WordCanvas offers several advanced settings that allow you to flexibly control the output of text images. Here we introduce randomness settings, which are primarily used for training models.
📄️ Augmentation
We have not included image augmentation functionality directly within WordCanvas because we believe it is a highly "customizable" requirement. Different application scenarios may require different augmentation methods. However, we provide some simple examples to illustrate how to implement image augmentation.
📄️ MRZGenerator
This feature was added in version 0.5.0.
📄️ BarcodeGenerator
This feature was added in version 0.5.0.
📄️ Resources
Text synthesis tools are primarily used for automatically generating image datasets, especially in scenarios where large amounts of annotated data are required to train deep learning models. These tools enhance model adaptability to different environments, fonts, colors, and backgrounds by embedding synthetic text in images to simulate real-world occurrences of text.