再構築されたシーンの視覚化と操作

arView.automaticallyConfigureSession = false
let configuration = ARWorldTrackingConfiguration()
configuration.sceneReconstruction = .meshWithClassification

arView.debugOptions.insert(.showSceneUnderstanding)

arView.session.run(configuration)

@IBAction func togglePlaneDetectionButtonPressed(_ button: UIButton) {
    guard let configuration = arView.session.configuration as? ARWorldTrackingConfiguration else {
        return
    }
    if configuration.planeDetection == [] {
        configuration.planeDetection = [.horizontal, .vertical]
        button.setTitle("Stop Plane Detection", for: [])
    } else {
        configuration.planeDetection = []
        button.setTitle("Start Plane Detection", for: [])
    }
    arView.session.run(configuration)
}

let tapLocation = sender.location(in: arView)
if let result = arView.raycast(from: tapLocation, allowing: .estimatedPlane, alignment: .any).first {
    // ...

let resultAnchor = AnchorEntity(world: result.worldTransform)
resultAnchor.addChild(sphere(radius: 0.01, color: .lightGray))
arView.scene.addAnchor(resultAnchor, removeAfter: 3)

arView.automaticallyConfigureSession = false
let configuration = ARWorldTrackingConfiguration()
configuration.sceneReconstruction = .meshWithClassification

nearbyFaceWithClassification(to: result.worldTransform.position) { (centerOfFace, classification) in
    // ...

DispatchQueue.global().async {
    for anchor in meshAnchors {
        for index in 0..<anchor.geometry.faces.count {
            // Get the center of the face so that we can compare it to the given location.
            let geometricCenterOfFace = anchor.geometry.centerOf(faceWithIndex: index)
            
            // Convert the face's center to world coordinates.
            var centerLocalTransform = matrix_identity_float4x4
            centerLocalTransform.columns.3 = SIMD4<Float>(geometricCenterOfFace.0, geometricCenterOfFace.1, geometricCenterOfFace.2, 1)
            let centerWorldPosition = (anchor.transform * centerLocalTransform).position
             
            // We're interested in a classification that is sufficiently close to the given location––within 5 cm.
            let distanceToFace = distance(centerWorldPosition, location)
            if distanceToFace <= 0.05 {
                // Get the semantic classification of the face and finish the search.
                let classification: ARMeshClassification = anchor.geometry.classificationOf(faceWithIndex: index)
                completionBlock(centerWorldPosition, classification)
                return
            }
        }
    }

let textEntity = self.model(for: classification)

let rayDirection = normalize(result.worldTransform.position - self.arView.cameraTransform.translation)
let textPositionInWorldCoordinates = result.worldTransform.position - (rayDirection * 0.1)

let raycastDistance = distance(result.worldTransform.position, self.arView.cameraTransform.translation)
textEntity.scale = .one * raycastDistance

var resultWithCameraOrientation = self.arView.cameraTransform
resultWithCameraOrientation.translation = textPositionInWorldCoordinates
let textAnchor = AnchorEntity(world: resultWithCameraOrientation.matrix)
textAnchor.addChild(textEntity)
self.arView.scene.addAnchor(textAnchor, removeAfter: 3)

if let centerOfFace = centerOfFace {
    let faceAnchor = AnchorEntity(world: centerOfFace)
    faceAnchor.addChild(self.sphere(radius: 0.01, color: classification.color))
    self.arView.scene.addAnchor(faceAnchor, removeAfter: 3)
}

arView.environment.sceneUnderstanding.options.insert(.occlusion)

arView.environment.sceneUnderstanding.options.insert(.physics)

if model.collision == nil {
    model.generateCollisionShapes(recursive: true)
    model.physicsBody = .init()
}

Timer.scheduledTimer(withTimeInterval: seconds, repeats: false) { (timer) in
    model.physicsBody?.mode = .dynamic
}