Milan Todorovic
Let your iOS app read texts
#1about 4 minutes
Introduction to the Vision framework for text recognition
The Vision framework simplifies incorporating optical character recognition (OCR) into iOS and macOS applications using Swift.
#2about 4 minutes
Understanding the core Vision request workflow
The fundamental process involves creating an image request handler, defining a request, and then performing the handler to get results.
#3about 2 minutes
Simplifying text recognition with VNRecognizedTextRequest
The modern API streamlines text recognition by using the VNRecognizedTextRequest class, which returns candidate strings directly.
#4about 3 minutes
Choosing between fast and accurate recognition modes
A comparison of the 'fast' mode, which uses character detection, and the 'accurate' mode, which uses a neural network for whole-word recognition.
#5about 4 minutes
Implementing the full workflow with advanced options
A complete code walkthrough shows how to set up the request, handle completion, and improve results with language correction and custom lexicons.
#6about 6 minutes
Live demo of scanning printed text from a book
A practical demonstration using a sample app to scan a page from a printed book, showing the high accuracy of the Vision framework.
#7about 3 minutes
Demonstrating business card and receipt scanning
The demo continues by scanning a business card and a multi-language receipt, highlighting both successes and potential challenges with complex layouts.
#8about 3 minutes
Recognizing handwritten text and a brief code overview
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.
#9about 5 minutes
Resources and other capabilities of the Vision framework
Learn where to find documentation and tutorials, and discover other Vision features like hand and body pose detection or image classification.
#10about 3 minutes
On-device processing and cross-platform considerations
The benefits of on-device processing for speed, security, and privacy are discussed, along with potential alternatives for Android and Flutter developers.
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Matching moments
01:54 MIN
Understanding the capabilities of Apple's Vision framework
Detect Hand Pose with Vision
02:20 MIN
Exploring Apple's core machine learning frameworks
Harnessing Apple Intelligence: Live Coding with Swift for iOS
23:25 MIN
Using the on-device model for text extraction
Harnessing Apple Intelligence: Live Coding with Swift for iOS
00:20 MIN
Defining computer vision and its real-world applications
Computer Vision from the Edge to the Cloud done easy
07:53 MIN
Understanding the capabilities of Apple Intelligence
Harnessing Apple Intelligence: Live Coding with Swift for iOS
27:25 MIN
Showcasing computer vision project examples
Computer Vision from the Edge to the Cloud done easy
07:12 MIN
Using Vision Camera and frame processors for real-time video
Building Better Apps with React Native
24:46 MIN
Exploring the Foundation Models documentation and opportunities
Harnessing Apple Intelligence: Live Coding with Swift for iOS
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