How To Create Multiline Synthetic Images Using Synthtiger

Author(s): Eivind Kjosbakken

Originally published on Towards AI.

Making synthetic data is one of the quickest ways of acquiring a labeled dataset for supervised learning. Instead of labeling files yourself, you already have the ground truth as you are creating the images. This tutorial will show you how to leverage the power of synthetic image generation to create a dataset, which can then be used to fine-tune an OCR engine like EasyOCR or a document information extraction model like Donut.

Create Synthetic images by following this tutorial. OpenAI. (2024). ChatGPT [Large language model]. https://chat.openai.comMotivationCreating the environmentInstalling LibraqmCloning the Git repositoryCreate synthetic imagesCreate synthetic images with your own wordsUse cases for synthetic imagesCustomizing the image creation processUse cases for synthetic imagesConclusion

Training high-quality supervised AI models typically requires a large dataset for the model to train on. These datasets are expensive to create, as you have to label the dataset. For example, if you want a dataset to fine-tune an OCR engine, you would have to get a series of images, and then manually write out all the text in the images. This requires a lot of time if you are to do it yourself or money if you are to outsource the work.

The solution is then to create a synthetic… Read the full blog for free on Medium.

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Published via Towards AI