How we made our optical character recognition (OCR) code more accurate

Summary

What is optical character recognition?Optical Character Recognition (OCR) is a technology that recognizes printed or handwritten characters from digital images or scanned documents and converts them into machine-readable text. This technology has revolutionized document processing, enabling the extraction of information from paper-based documents and converting it into editable and searchable digital formats.OCR systems use advanced algorithms to analyze the shape, size, and location of characters in an image, matching them to a database of known characters. The result is the transformation of visual data into readable text.Advancements in OCR technology driven, by machine learning and AI, have significantly improved its accuracy. OCR is now widely used in applications such as document scanning, data entry automation, and text-to-speech technology for people with visual impairments.Optical character recognition at PiecesAt Pieces, we’ve worked on fine-tuning OCR technology specifically for code. We use Tesseract as the primary OCR engine, which performs layout analysis before using LSTM (Long Short-Term Memory) trained on text-image pairs to predict the characters. Tesseract is one of the best free OCR tools, supporting over 100 languages, some of our users used OCR+Pieces to build their own tool. However, its out-of-the-box capabilities are not ideal for code, which is why we enhanced it with specific pre- and post-processing steps.Standardized inputs through image pre-processingTo best support software engineers when they want to transcribe code from images, we fine-tuned our pre-processing pipeline to screenshots of code in IDEs, terminals, and online resources like YouTube videos and blog posts.Since programming environments can be in light or dark mode, both modes should yield good results.Additionally, we wanted to support images with gradients or noisy backgrounds, as might be found in YouTube programming tutorials or retro websites, as well as images with lo...