This sample app runs an ARKit world-tracking session with content displayed in a SpriteKit view. The app uses the Vision framework to pass camera images to a Core ML classifier model, displaying a label in the corner of the screen to indicate whether the classifier recognizes anything in view of the camera. After the classifier produces a label for the image, the user can tap the screen to place that text in AR world space.
Implement the Vision/Core ML Image Classifier
The sample code’s classificationRequest property, classifyCurrentImage() method, and processClassifications(for:error:) method manage:
A Core ML image-classifier model, loaded from an mlmodel file bundled with the app using the Swift API that Core ML generates for the model
The sample ViewController class manages the AR session and displays AR overlay content in a SpriteKit view. ARKit captures video frames from the camera and provides them to the view controller in the session(_:didUpdate:) method, which then calls the classifyCurrentImage() method to run the Vision image classifier.
Serialize Image Processing for Real-Time Performance
The classifyCurrentImage() method uses the view controller’s currentBuffer property to track whether Vision is currently processing an image before starting another Vision task.
In addition, the sample app enables the usesCPUOnly setting for its Vision request, freeing the GPU for use in rendering.
Visualize Results in AR
The processClassifications(for:error:) method stores the best-match result label produced by the image classifier and displays it in the corner of the screen. The user can then tap in the AR scene to place that label at a real-world position. Placing a label requires two main steps.
First, a tap gesture recognizer fires the placeLabelAtLocation(sender:) action. This method uses the ARKit hitTest(_:types:) method to estimate the 3D real-world position corresponding to the tap, and adds an anchor to the AR session at that position.
Next, after ARKit automatically creates a SpriteKit node for the newly added anchor, the view(_:didAdd:for:) delegate method provides content for that node. In this case, the sample TemplateLabelNode class creates a styled text label using the string provided by the image classifier.
Use sound effects and environmental sound layers to create an engaging AR experience.
This documentation contains preliminary information about an API or technology in development. This information is subject to change, and software implemented according to this documentation should be tested with final operating system software.