A fast and simple OCR library written in Swift, optimized for recognizing short alphanumeric codes like gift cards.
SwiftOCR is an open-source optical character recognition library written in Swift for iOS and macOS. It uses a neural network to recognize text in images, specifically optimized for short, one-line alphanumeric codes like gift card or serial numbers. It solves the problem of slow and inaccurate OCR for these specialized use cases by offering faster processing and higher accuracy than traditional tools.
iOS and macOS developers who need to integrate OCR functionality into their apps, particularly for recognizing short codes, serial numbers, or gift cards where speed and accuracy are critical.
Developers choose SwiftOCR because it is significantly faster and more accurate than Tesseract for alphanumeric code recognition, uses modern neural network techniques, and can be implemented with just a few lines of code, making it much simpler to integrate than complex legacy OCR solutions.
Fast and simple OCR library written in Swift
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Processes images in as little as 0.08 seconds, as benchmarked against Tesseract, making it ideal for real-time code scanning.
Achieves up to 97.7% accuracy on difficult alphanumeric images, outperforming Tesseract in specialized use cases.
Can be implemented with just 6 lines of code, reducing setup complexity compared to legacy OCR solutions.
Uses less CPU (~30%) and memory (45 MB) than alternatives, based on internal testing, for efficient mobile performance.
The project explicitly states it is no longer maintained, with no bug fixes or updates, and recommends Apple's Vision instead.
Only optimized for short, one-line alphanumeric codes; the README admits it's not suitable for normal text like poems or articles.
Relies on Swift-AI and GPUImage, which may have compatibility issues or lack modern support, as hinted by the TODO for GPUImage 2.
SwiftOCR is an open-source alternative to the following products: