Hi everyone,
I'm working on a SwiftUI app and need help building a view that integrates the device's camera and uses a pre-trained Core ML model for real-time object recognition. Here's what I want to achieve:
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Open the device's camera from a SwiftUI view.
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Capture frames from the camera feed and analyze them using a Create ML-trained Core ML model.
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If a specific figure/object is recognized, automatically close the camera view and navigate to another screen in my app.
I'm looking for guidance on:
- Setting up live camera capture in SwiftUI.
- Using Core ML and Vision frameworks for real-time object recognition in this context.
- Managing navigation between views when the recognition condition is met.
Any advice, code snippets, or examples would be greatly appreciated!
Thanks in advance!
Hello @VladimirBarev,
See AVCam for guidance on setting up live camera capture in SwiftUI.
See Recognizing Objects in Live Capture, which uses Core ML and Vision for real-time object recognition.
Managing navigation between views when the recognition condition is met.
In SwiftUI, navigation is state based. For example, see Manage navigation state for NavigationStack. When you get a successful recognition, you can update your navigation state accordingly.
-- Greg
