The Vision framework simplifies incorporating optical character recognition (OCR) into iOS and macOS applications using Swift.
The fundamental process involves creating an image request handler, defining a request, and then performing the handler to get results.
The modern API streamlines text recognition by using the VNRecognizedTextRequest class, which returns candidate strings directly.
A comparison of the 'fast' mode, which uses character detection, and the 'accurate' mode, which uses a neural network for whole-word recognition.
A complete code walkthrough shows how to set up the request, handle completion, and improve results with language correction and custom lexicons.
A practical demonstration using a sample app to scan a page from a printed book, showing the high accuracy of the Vision framework.
The demo continues by scanning a business card and a multi-language receipt, highlighting both successes and potential challenges with complex layouts.
The final demo shows the framework's capability to recognize handwritten text, followed by a quick look at the relevant Swift code in the sample project.
Learn where to find documentation and tutorials, and discover other Vision features like hand and body pose detection or image classification.
The benefits of on-device processing for speed, security, and privacy are discussed, along with potential alternatives for Android and Flutter developers.
28:51Milan Todorovic
28:54MIlan Todorović
28:48Mario Petricevic
34:34Daniel Madalitso Phiri
44:13Andrew Morgan
44:09Peter Steinberger
48:21Nermin Sehic
25:29Pawel Skiba
Jobs that call for the skills explored in this talk.
TechBiz Global GmbH
TechBiz Global GmbH
TechBiz Global GmbH
TechBiz Global GmbH
TechBiz Global GmbH