Horizontal plane detection limitations? - ios

I'm trying to build an ARKit based app which requires detection of roads and placing virtual content 30 feet away from the camera. However horizontal plane detection is stopping to add anchors after about 10 feet. Is there a workaround for this problem?

public func session(_ session: ARSession, didUpdate frame: ARFrame) {
guard let usdzEntity = usdzEntity else { return }
let camera = frame.camera
let transform = camera.transform
if let rayCast = arView.scene.raycast(from: transform.translation, to: usdzEntity.transform.translation, query: .nearest, mask: .default, relativeTo: nil).first {
print(rayCast.distance)
}
}
look at this, hope this can give you some help

Related

Swift combine ML to better detect Images using ARKit

right now my App can detect images and place some Models. I am usnig ARKit and RealityKit. This is my setup:
import ARKit
import RealityKit
class ViewController: UIViewController, ARSessionDelegate {
func session(_ session: ARSession, didUpdate anchors: [ARAnchor]) {
guard let imageAnchor = anchors.first as? ARImageAnchor,
let _ = imageAnchor.referenceImage.name
else { return }
let anchor = AnchorEntity(anchor: imageAnchor)
// Add Model Entity to anchor
anchor.addChild(model)
arView.scene.anchors.append(anchor)
}
override func viewWillAppear(_ animated: Bool) {
super.viewWillAppear(animated)
arView.session.delegate = self
resetTrackingConfig()
}
func resetTrackingConfig() {
guard let refImg = ARReferenceImage.referenceImages(inGroupNamed: "Sub",
bundle: nil)
else { return }
let config = ARWorldTrackingConfiguration()
config.detectionImages = refImg
config.maximumNumberOfTrackedImages = 1
let options = [ARSession.RunOptions.removeExistingAnchors,
ARSession.RunOptions.resetTracking]
arView.session.run(config, options: ARSession.RunOptions(options))
}
}
Now the problem is that I am not completely satisfied how the image detection works. It has troubles detecting images if for example the light is slightly different.
This is my image:
But it should also be able to detect these images:
(2nd one has no white background)
And for that I thought I could use Machine Leaning. But how can I combine that with my ARKit setup? Right now it just takes the images from my assets-folder. I tried searching for that topic but couldn't find anything.. Is this kind of project even possible the way I described it? Any help is appreciated! Let me know if you need any more information.

ARKit does not recognize reference images

I'm trying to place a 3D model on top of a recognized image with ARKit and RealityKit - all programmatically. Before I start the ARView I'm downloading the model I want to show when the reference image is detected.
This is my current setup:
override func viewDidLoad() {
super.viewDidLoad()
arView.session.delegate = self
// Check if the device supports the AR experience
if (!ARConfiguration.isSupported) {
TLogger.shared.error_objc("Device does not support Augmented Reality")
return
}
guard let qrCodeReferenceImage = UIImage(named: "QRCode") else { return }
let detectionImages: Set<ARReferenceImage> = convertToReferenceImages([qrCodeReferenceImage])
let configuration = ARWorldTrackingConfiguration()
configuration.detectionImages = detectionImages
arView.session.run(configuration, options: [.resetTracking, .removeExistingAnchors])
}
I use the ARSessionDelegate to get notified when a new image anchor was added which means the reference image got detected:
func session(_ session: ARSession, didAdd anchors: [ARAnchor]) {
print("Hello")
for anchor in anchors {
guard let imageAnchor = anchor as? ARImageAnchor else { return }
let referenceImage = imageAnchor.referenceImage
addEntity(self.localModelPath!)
}
}
However, the delegate method never gets called while other delegate functions like func session(ARSession, didUpdate: ARFrame) are getting called so I assume that the session just doesn't detect the image. The image resolution is good and the printed image the big so it should definitely get recognized by the ARSession. I also checked that the image has been found before adding it to the configuration.
Can anyone lead me in the right direction here?
It looks like you have your configuration set up correctly. Your delegate-function should be called when the reference image is recognized. Make sure your configuration isn't overwritten at any point in your code.

ARKit - Capture textures for provided environment mesh using Lidar

I'm trying to create environment mesh with textures, the mesh has been built successfully but not sure how to the store captured textures to apply to the mesh later. According to this as we are creating a geometry for each anchor at the final state of scan, I suppose we need to store each frame texture for corresponding anchor with help of ARSession delegate.
The way textures are recording:
//Create a dictionary to store textures corresponding to each anchor
private var anchors = [UUID: UIImage]()
//Store every new anchor with the current frame image
func session(_ session: ARSession, didAdd anchors: [ARAnchor]) {
guard let cameraImage = captureCamera() else { return }
anchors.forEach { anchor in
self.anchors[anchor.identifier] = cameraImage
}
}
//In case of an anchor update, texture needs to be updated too(not sure it's necessary or not)
func session(_ session: ARSession, didUpdate anchors: [ARAnchor]) {
guard let cameraImage = captureCamera() else { return }
anchors.forEach { anchor in
self.anchors[anchor.identifier] = cameraImage
}
}
//Remove every removed anchor to free up the memory
func session(_ session: ARSession, didRemove anchors: [ARAnchor]) {
anchors.forEach { anchor in
self.anchors.removeValue(forKey: anchor.identifier)
}
}
//Capture current camera frame image
func captureCamera() -> UIImage? {
guard let frame = metalARSession.currentFrame else {return nil}
let pixelBuffer = frame.capturedImage
let image = CIImage(cvPixelBuffer: pixelBuffer)
let context = CIContext(options:nil)
guard let cameraImage = context.createCGImage(image, from: image.extent) else {return nil}
return UIImage(cgImage: cameraImage)
}
In rest of the code I have created a MDLAsset and export it as an OBJ file, also textures are saved on storage and texture coordinates are calculated too. Now how can I apply these textures to my OBJ file?

ARKit removes a node when Reference Image disappeared

I'm building AR Scanner application where users are able to scan different images and receive rewards for this.
When they point camera at some specific image - I place SCNNode on top of that image and after they remove camera from that image - SCNNode get's dismissed.
But when image disappears and camera stays at the same position SCNNode didn't get dismissed.
How can I make it disappear together with Reference image disappearance?
I have studied lot's of other answers here, on SO, but they didn't help me
Here's my code for adding and removing SCNNode's:
extension ARScannerScreenViewController: ARSCNViewDelegate {
func renderer(_ renderer: SCNSceneRenderer, didAdd node: SCNNode, for anchor: ARAnchor) {
DispatchQueue.main.async { self.instructionLabel.isHidden = true }
if let imageAnchor = anchor as? ARImageAnchor {
handleFoundImage(imageAnchor, node)
imageAncors.append(imageAnchor)
trackedImages.append(node)
} else if let objectAnchor = anchor as? ARObjectAnchor {
handleFoundObject(objectAnchor, node)
}
}
func renderer(_ renderer: SCNSceneRenderer, updateAtTime time: TimeInterval) {
guard let pointOfView = sceneView.pointOfView else { return }
for (index, item) in trackedImages.enumerated() {
if !(sceneView.isNode(item, insideFrustumOf: pointOfView)) {
self.sceneView.session.remove(anchor: imageAncors[index])
}
}
}
private func handleFoundImage(_ imageAnchor: ARImageAnchor, _ node: SCNNode) {
let name = imageAnchor.referenceImage.name!
print("you found a \(name) image")
let size = imageAnchor.referenceImage.physicalSize
if let imageNode = showImage(size: size) {
node.addChildNode(imageNode)
node.opacity = 1
}
}
private func showImage(size: CGSize) -> SCNNode? {
let image = UIImage(named: "InfoImage")
let imageMaterial = SCNMaterial()
imageMaterial.diffuse.contents = image
let imagePlane = SCNPlane(width: size.width, height: size.height)
imagePlane.materials = [imageMaterial]
let imageNode = SCNNode(geometry: imagePlane)
imageNode.eulerAngles.x = -.pi / 2
return imageNode
}
private func handleFoundObject(_ objectAnchor: ARObjectAnchor, _ node: SCNNode) {
let name = objectAnchor.referenceObject.name!
print("You found a \(name) object")
}
}
I also tried to make it work using ARSession, but I couldn't even get to prints:
func session(_ session: ARSession, didUpdate anchors: [ARAnchor]) {
for anchor in anchors {
for myAnchor in imageAncors {
if let imageAnchor = anchor as? ARImageAnchor, imageAnchor == myAnchor {
if !imageAnchor.isTracked {
print("Not tracked")
} else {
print("tracked")
}
}
}
}
}
You have to use ARWorldTrackingConfiguration instead of ARImageTrackingConfiguration. It's quite bad idea to use both configurations in app because each time you switch between them – tracking state is reset and you have to track from scratch.
Let's see what Apple documentation says about ARImageTrackingConfiguration:
With ARImageTrackingConfiguration, ARKit establishes a 3D space not by tracking the motion of the device relative to the world, but solely by detecting and tracking the motion of known 2D images in view of the camera.
The basic differences between these two configs are about how ARAnchors behave:
ARImageTrackingConfiguration allows you get ARImageAnchors only if your reference images is in a Camera View. So if you can't see a reference image – there's no ARImageAnchor, thus there's no a 3D model (it's resetting each time you cannot-see-it-and-then-see-it-again). You can simultaneously detect up to 100 images.
ARWorldTrackingConfiguration allows you track a surrounding environment in 6DoF and get ARImageAnchor, ARObjectAnchor, or AREnvironmentProbeAnchor. If you can't see a reference image – there's no ARImageAnchor, but when you see it again ARImageAnchor is still there. So there's no reset.
Conclusion:
ARWorldTrackingConfiguration's cost of computation is much higher. However this configuration allows you perform not only image tracking but also hit-testing and ray-casting for detected planes, object detection, and a restoration of world maps.
Use nodeForAnchor to load your nodes, so when the anchors disappear, the nodes will go as well.

Show bounding box while detecting object using ARKit 2

I have scanned and trained multiple real world objects. I do have the ARReferenceObject and the app detects them fine.
The issue that I'm facing is when an object doest not have distinct, vibrant features it takes few seconds to return a detection result, which I can understand. Now, I want the app to show a bounding box and an activity indicator on top the object while it is trying to detect it.
I do not see any information regarding this. Also, if there is any way to get the time when detection starts or the confidence percentage of the object being detected.
Any help is appreciated.
It is possible to show a boundingBox in regard to the ARReferenceObject prior to it being detected; although I am not sure why you would want to do that (in advance anyway).
For example, assuming your referenceObject was on a horizontal surface you would first need to place your estimated bounding box on the plane (or use some other method to place it in advance), and in the time it took to detect the ARPlaneAnchor and place the boundingBox it is most likely that your model would already have been detected.
Possible Approach:
As you are no doubt aware an ARReferenceObject has a center, extent and scale property as well as a set of rawFeaturePoints associated with the object.
As such we can create our own boundingBox node based on some of the sample code from Apple in Scanning & Detecting 3D Objects and create our own SCNNode which will display a bounding box of the approximate size of the ARReferenceObject which is stored locally prior to it being detected.
Note you will need to locate the 'wireframe_shader' from the Apple Sample Code for the boundingBox to render transparent:
import Foundation
import ARKit
import SceneKit
class BlackMirrorzBoundingBox: SCNNode {
//-----------------------
// MARK: - Initialization
//-----------------------
/// Creates A WireFrame Bounding Box From The Data Retrieved From The ARReferenceObject
///
/// - Parameters:
/// - points: [float3]
/// - scale: CGFloat
/// - color: UIColor
init(points: [float3], scale: CGFloat, color: UIColor = .cyan) {
super.init()
var localMin = float3(Float.greatestFiniteMagnitude)
var localMax = float3(-Float.greatestFiniteMagnitude)
for point in points {
localMin = min(localMin, point)
localMax = max(localMax, point)
}
self.simdPosition += (localMax + localMin) / 2
let extent = localMax - localMin
let wireFrame = SCNNode()
let box = SCNBox(width: CGFloat(extent.x), height: CGFloat(extent.y), length: CGFloat(extent.z), chamferRadius: 0)
box.firstMaterial?.diffuse.contents = color
box.firstMaterial?.isDoubleSided = true
wireFrame.geometry = box
setupShaderOnGeometry(box)
self.addChildNode(wireFrame)
}
required init?(coder aDecoder: NSCoder) { fatalError("init(coder:) Has Not Been Implemented") }
//----------------
// MARK: - Shaders
//----------------
/// Sets A Shader To Render The Cube As A Wireframe
///
/// - Parameter geometry: SCNBox
func setupShaderOnGeometry(_ geometry: SCNBox) {
guard let path = Bundle.main.path(forResource: "wireframe_shader", ofType: "metal", inDirectory: "art.scnassets"),
let shader = try? String(contentsOfFile: path, encoding: .utf8) else {
return
}
geometry.firstMaterial?.shaderModifiers = [.surface: shader]
}
}
To display the bounding box you you would then do something like the following, noting that in my example I have the following variables:
#IBOutlet var augmentedRealityView: ARSCNView!
let configuration = ARWorldTrackingConfiguration()
let augmentedRealitySession = ARSession()
To display the boundingBox prior to detection of the actual object itself, you would call the func loadBoundigBox in viewDidLoad e.g:
/// Creates A Bounding Box From The Data Available From The ARObject In The Local Bundle
func loadBoundingBox(){
//1. Run Our Session
augmentedRealityView.session = augmentedRealitySession
augmentedRealityView.delegate = self
//2. Load A Single ARReferenceObject From The Main Bundle
if let objectURL = Bundle.main.url(forResource: "fox", withExtension: ".arobject"){
do{
var referenceObjects = [ARReferenceObject]()
let object = try ARReferenceObject(archiveURL: objectURL)
//3. Log it's Properties
print("""
Object Center = \(object.center)
Object Extent = \(object.extent)
Object Scale = \(object.scale)
""")
//4. Get It's Scale
let scale = CGFloat(object.scale.x)
//5. Create A Bounding Box
let boundingBoxNode = BlackMirrorzBoundingBox(points: object.rawFeaturePoints.points, scale: scale)
//6. Add It To The ARSCNView
self.augmentedRealityView.scene.rootNode.addChildNode(boundingBoxNode)
//7. Position It 0.5m Away From The Camera
boundingBoxNode.position = SCNVector3(0, -0.5, -0.5)
//8. Add It To The Configuration
referenceObjects.append(object)
configuration.detectionObjects = Set(referenceObjects)
}catch{
print(error)
}
}
//9. Run The Session
augmentedRealitySession.run(configuration, options: [.resetTracking, .removeExistingAnchors])
augmentedRealityView.automaticallyUpdatesLighting = true
}
The above example simple creates a boundingBox from the non-detected ARReferenceObject and places it 0.5m down from and 0.5meter away from the Camera which yields something like this:
You would of course need to handle the position of the boundBox initially, as well as hoe to handle the removal of the boundingBox 'indicator'.
The method below simply shows a boundBox when the actual object is detected e.g:
//--------------------------
// MARK: - ARSCNViewDelegate
//--------------------------
extension ViewController: ARSCNViewDelegate{
func renderer(_ renderer: SCNSceneRenderer, didAdd node: SCNNode, for anchor: ARAnchor) {
//1. Check We Have A Valid ARObject Anchor
guard let objectAnchor = anchor as? ARObjectAnchor else { return }
//2. Create A Bounding Box Around Our Object
let scale = CGFloat(objectAnchor.referenceObject.scale.x)
let boundingBoxNode = BlackMirrorzBoundingBox(points: objectAnchor.referenceObject.rawFeaturePoints.points, scale: scale)
node.addChildNode(boundingBoxNode)
}
}
Which yields something like this:
In regard to the detection timer, there is an example in the Apple Sample Code, which displays how long it takes to detect the model.
In its crudest form (not accounting for milliseconds) you can do something like so:
Firstly create A Timer and a var to store the detection time e.g:
var detectionTimer = Timer()
var detectionTime: Int = 0
Then when you run your ARSessionConfiguration initialise the timer e.g:
/// Starts The Detection Timer
func startDetectionTimer(){
detectionTimer = Timer.scheduledTimer(timeInterval: 1.0, target: self, selector: #selector(logDetectionTime), userInfo: nil, repeats: true)
}
/// Increments The Total Detection Time Before The ARReference Object Is Detected
#objc func logDetectionTime(){
detectionTime += 1
}
Then when an ARReferenceObject has been detected invalidate the timer and log the time e.g:
//--------------------------
// MARK: - ARSCNViewDelegate
//--------------------------
extension ViewController: ARSCNViewDelegate{
func renderer(_ renderer: SCNSceneRenderer, didAdd node: SCNNode, for anchor: ARAnchor) {
//1. Check We Have A Valid ARObject Anchor
guard let _ = anchor as? ARObjectAnchor else { return }
//2. Stop The Timer
detectionTimer.invalidate()
//3. Log The Detection Time
print("Total Detection Time = \(detectionTime) Seconds")
//4. Reset The Detection Time
detectionTime = 0
}
}
This should be more than enough to get your started...
And please note, that this example doesn't provide a boundingBox when scanning an object (look at the Apple Sample Code for that), it provides one based on an existing ARReferenceObject which is implied in your question (assuming I interpreted it correctly).

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