Before you post —Camera doesn't work on the Simulator— that's no longer true. I've made a solution that makes the Simulator believe there's an actual hardware device connected, allowing users to stream the macOS camera to the iOS Simulator (see for more info RocketSim's documentation: https://docs.rocketsim.app/features/hzQMSrSga7BGWvxdNVdwYs/simulator-camera-support/58tQ5jvevLNSnyUEA7VgAv) Now, it works for VNDocumentCameraViewController, but when I try opening DataScannerViewController, I directly run into: Failed to start scanning: The operation couldn’t be completed. (VisionKit.DataScannerViewController.ScanningUnavailable error 0.) My question: How does this view controller determine whether scanning is available? Is there a certain capability the available AVCaptureDevice's need to support maybe? Any direction would be helpful for me to make this work for developers, making them build apps faster!

Hello experts, I have implemented 3d guassian splating rendering through the CompositorServices framework, but I want to port it to the RealityKit framework. I am not sure whether RealityKit meets the requirements. In order to port the code, I need to render a large number of instanced planes (it is necessary to support instantiated Mesh), and completely custom vertex shader and fragment shader code, including using instance_id and discarding pixels (Call the discard_fragment method). Some Metal code snippets: vertex ColorInOut splatVertexShader(uint vertexID [[vertex_id]], uint instanceID [[instance_id]], ushort amp_id [[amplification_id]], constant Splat* splatArray [[ buffer(BufferIndexSplat) ]], constant UniformsArray & uniformsArray [[ buffer(BufferIndexUniforms) ]], constant int32_t* splatIndices [[ buffer(BufferIndexSplatIndex) ]]) { // ... （do some calculations） } fragment half4 splatFragmentShader(ColorInOut in [[stage_in]]) { // ... if (/* a certain condition */) { discard_fragment(); } } I have learned that CustomMaterial does not support vision, and Shader Graph does not support custom vertex/fragment shader code. I also noticed the LowLevelMesh interface, but I didn't find any sample code with custom shader code, so it's not clear whether it would be able to achieve what I need. Can these requirements be met using reality?

Hello, We have been encountering a persistent crash in our application, which is deployed exclusively on iPad devices. The crash occurs in the following code block: let requestHandler = ImageRequestHandler(paddedImage) var request = CoreMLRequest(model: model) request.cropAndScaleAction = .scaleToFit let results = try await requestHandler.perform(request) The client using this code is wrapped inside an actor, following Swift concurrency principles. The issue has been consistently reproduced across multiple iPadOS versions, including: iPad OS - 18.4.0 iPad OS - 18.4.1 iPad OS - 18.5.0 This is the crash log - Crashed: com.apple.VN.detectorSyncTasksQueue.VNCoreMLTransformer 0 libobjc.A.dylib 0x7b98 objc_retain + 16 1 libobjc.A.dylib 0x7b98 objc_retain_x0 + 16 2 libobjc.A.dylib 0xbf18 objc_getProperty + 100 3 Vision 0x326300 -[VNCoreMLModel predictWithCVPixelBuffer:options:error:] + 148 4 Vision 0x3273b0 -[VNCoreMLTransformer processRegionOfInterest:croppedPixelBuffer:options:qosClass:warningRecorder:error:progressHandler:] + 748 5 Vision 0x2ccdcc __119-[VNDetector internalProcessUsingQualityOfServiceClass:options:regionOfInterest:warningRecorder:error:progressHandler:]_block_invoke_5 + 132 6 Vision 0x14600 VNExecuteBlock + 80 7 Vision 0x14580 __76+[VNDetector runSuccessReportingBlockSynchronously:detector:qosClass:error:]_block_invoke + 56 8 libdispatch.dylib 0x6c98 _dispatch_block_sync_invoke + 240 9 libdispatch.dylib 0x1b584 _dispatch_client_callout + 16 10 libdispatch.dylib 0x11728 _dispatch_lane_barrier_sync_invoke_and_complete + 56 11 libdispatch.dylib 0x7fac _dispatch_sync_block_with_privdata + 452 12 Vision 0x14110 -[VNControlledCapacityTasksQueue dispatchSyncByPreservingQueueCapacity:] + 60 13 Vision 0x13ffc +[VNDetector runSuccessReportingBlockSynchronously:detector:qosClass:error:] + 324 14 Vision 0x2ccc80 __119-[VNDetector internalProcessUsingQualityOfServiceClass:options:regionOfInterest:warningRecorder:error:progressHandler:]_block_invoke_4 + 336 15 Vision 0x14600 VNExecuteBlock + 80 16 Vision 0x2cc98c __119-[VNDetector internalProcessUsingQualityOfServiceClass:options:regionOfInterest:warningRecorder:error:progressHandler:]_block_invoke_3 + 256 17 libdispatch.dylib 0x1b584 _dispatch_client_callout + 16 18 libdispatch.dylib 0x6ab0 _dispatch_block_invoke_direct + 284 19 Vision 0x2cc454 -[VNDetector internalProcessUsingQualityOfServiceClass:options:regionOfInterest:warningRecorder:error:progressHandler:] + 632 20 Vision 0x2cd14c __111-[VNDetector processUsingQualityOfServiceClass:options:regionOfInterest:warningRecorder:error:progressHandler:]_block_invoke + 124 21 Vision 0x14600 VNExecuteBlock + 80 22 Vision 0x2ccfbc -[VNDetector processUsingQualityOfServiceClass:options:regionOfInterest:warningRecorder:error:progressHandler:] + 340 23 Vision 0x125410 __swift_memcpy112_8 + 4852 24 libswift_Concurrency.dylib 0x5c134 swift::runJobInEstablishedExecutorContext(swift::Job*) + 292 25 libswift_Concurrency.dylib 0x5d5c8 swift_job_runImpl(swift::Job*, swift::SerialExecutorRef) + 156 26 libdispatch.dylib 0x13db0 _dispatch_root_queue_drain + 364 27 libdispatch.dylib 0x1454c _dispatch_worker_thread2 + 156 28 libsystem_pthread.dylib 0x9d0 _pthread_wqthread + 232 29 libsystem_pthread.dylib 0xaac start_wqthread + 8 We found an issue similar to us - https://developer.apple.com/forums/thread/770771. But the crash logs are quite different, we believe this warrants further investigation to better understand the root cause and potential mitigation strategies. Please let us know if any additional information would help diagnose this issue.

Issue: In iOS 26 (tested on Developer Beta), AVCaptureMetadataOutputObjectsDelegate no longer receives callbacks when using .face detection. metadataOutput.metadataObjectTypes = [.face]

Hi, I'm developing an application for macos and ios that has to run DetectHumanBodyPose3DRequest model in real time for retrieving the 3d skeleton from the camera. I'm experiencing a memory leak every time the model is used (when i comment that line, the memory stays constant). After a minute it uses about 1GB of ram running with mac catalyst. I attached a minimal project that has this problem Code Camera View import SwiftUI import Combine import Vision struct CameraView: View { @StateObject private var viewModel = CameraViewModel() var body: some View { HStack { ZStack { GeometryReader { geometry in if let image = viewModel.currentFrame { Image(decorative: image, scale: 1) .resizable() .scaledToFill() .frame(width: geometry.size.width, height: geometry.size.height) .clipped() } else { ProgressView() } } } } } } class CameraViewModel: ObservableObject { @Published var currentFrame: CGImage? @Published var frameRate: Double = 0 @Published var currentVisionBodyPose: HumanBodyPose3DObservation? // Store current body pose @Published var currentImageSize: CGSize? // Store current image size private var cameraManager: CameraManager? private var humanBodyPose = HumanBodyPose3DDetector() private var lastClassificationTime = Date() private var frameCount = 0 private var lastFrameTime = Date() private let classificationThrottleInterval: TimeInterval = 1.0 private var lastPoseSendTime: Date = .distantPast init() { cameraManager = CameraManager() startPreview() startClassification() } private func startPreview() { Task { guard let previewStream = cameraManager?.previewStream else { return } for await frame in previewStream { let size = CGSize(width: frame.width, height: frame.height) Task { @MainActor in self.currentFrame = frame self.currentImageSize = size self.updateFrameRate() } } } } private func startClassification() { Task { guard let classificationStream = cameraManager?.classificationStream else { return } for await pixelBuffer in classificationStream { self.classifyFrame(pixelBuffer: pixelBuffer) } } } private func classifyFrame(pixelBuffer: CVPixelBuffer) { humanBodyPose.runHumanBodyPose3DRequestOnImage(pixelBuffer: pixelBuffer) { [weak self] observation in guard let self = self else { return } DispatchQueue.main.async { if let observation = observation { self.currentVisionBodyPose = observation print(observation) } else { self.currentVisionBodyPose = nil } } } } private func updateFrameRate() { frameCount += 1 let now = Date() let elapsed = now.timeIntervalSince(lastFrameTime) if elapsed >= 1.0 { frameRate = Double(frameCount) / elapsed frameCount = 0 lastFrameTime = now } } } HumanBodyPose3DDetector import Foundation import Vision class HumanBodyPose3DDetector: NSObject, ObservableObject { @Published var humanObservation: HumanBodyPose3DObservation? = nil private let queue = DispatchQueue(label: "humanbodypose.queue") private let request = DetectHumanBodyPose3DRequest() private struct SendablePixelBuffer: @unchecked Sendable { let buffer: CVPixelBuffer } public func runHumanBodyPose3DRequestOnImage(pixelBuffer: CVPixelBuffer, completion: @escaping (HumanBodyPose3DObservation?) -> Void) { let sendableBuffer = SendablePixelBuffer(buffer: pixelBuffer) queue.async { [weak self] in Task { [weak self, sendableBuffer] in do { guard let self = self else { return } let result = try await self.request.perform(on: sendableBuffer.buffer) //process result DispatchQueue.main.async { if result.isEmpty { completion(nil) } else { completion(result[0]) } } } catch { DispatchQueue.main.async { completion(nil) } } } } } }

Apple Vision Pro support issue. The app contains the following UIRequiredDeviceCapabilities values, which aren’t supported in visionOS: [arkit]. When I try and distribute a build to the AppStore in Xcode, it comes up with this message, I have not selected Vision Pro as part of my build, can anyone please help? Thanks!

Hi, I'm trying to use the new RecognizeDocumentsRequest from the Vision Framework to read a receipt. It looks very promising by being able to read paragraphs, lines and detect data. So far it unfortunately seems to read every line on the receipt as a paragraph and when there is more space on one line it creates two paragraphs. Is there perhaps an Apple Engineer who knows if this is expected behaviour or if I should file a Feedback for this? Code setup: let request = RecognizeDocumentsRequest() let observations = try await request.perform(on: image) guard let document = observations.first?.document else { return } for paragraph in document.paragraphs { print(paragraph.transcript) for data in paragraph.detectedData { switch data.match.details { case .phoneNumber(let data): print("Phone: \(data)") case .postalAddress(let data): print("Postal: \(data)") case .calendarEvent(let data): print("Calendar: \(data)") case .moneyAmount(let data): print("Money: \(data)") case .measurement(let data): print("Measurement: \(data)") default: continue } } } See attached image as an example of a receipt I'd like to parse. The top 3 lines are the name, street, and postal code + city. These are all separate paragraphs. Checking on detectedData does see the street (2nd line) as PostalAddress, but not the complete address. Might that be a location thing since it's a Dutch address. And lower on the receipt it sees the block with "Pomp 1 95 Ongelood" and the things below also as separate paragraphs. First picking up the left side and after that the right side. So it's something like this: * Pomp 1 Volume Prijs € TOTAAL * BTW Netto 21.00 % 95 Ongelood 41,90 l 1.949/ 1 81.66 € 14.17 67.49

How do I test the new RecognizeDocumentRequest API. Reference: https://www.youtube.com/watch?v=H-GCNsXdKzM I am running Xcode Beta, however I only have one primary device that I cannot install beta software on. Please provide a strategy for testing. Will simulator work? The new capability is critical to my application, just what I need for structuring document scans and extraction. Thank you.

Following WWDC24 video "Discover Swift enhancements in the Vision framework" recommendations (cfr video at 10'41"), I used the following code to perform multiple new iOS 18 `RecognizedTextRequest' in parallel. Problem: if more than 2 request are run in parallel, the request will hang, leaving the app in a state where no more requests can be started. -> deadlock I tried other ways to run the requests, but no matter the method employed, or what device I use: no more than 2 requests can ever be run in parallel. func triggerDeadlock() {} try await withThrowingTaskGroup(of: Void.self) { group in // See: WWDC 2024 Discover Siwft enhancements in the Vision framework at 10:41 // ############## THIS IS KEY let maxOCRTasks = 5 // On a real-device, if more than 2 RecognizeTextRequest are launched in parallel using tasks, the request hangs // ############## THIS IS KEY for idx in 0..<maxOCRTasks { let url = ... // URL to some image group.addTask { // Perform OCR let _ = await performOCRRequest(on: url: url) } } var nextIndex = maxOCRTasks for try await _ in group { // Wait for the result of the next child task that finished if nextIndex < pageCount { group.addTask { let url = ... // URL to some image // Perform OCR let _ = await performOCRRequest(on: url: url) } nextIndex += 1 } } } } // MARK: - ASYNC/AWAIT version with iOS 18 @available(iOS 18, *) func performOCRRequest(on url: URL) async throws -> [RecognizedText] { // Create request var request = RecognizeTextRequest() // Single request: no need for ImageRequestHandler // Configure request request.recognitionLevel = .accurate request.automaticallyDetectsLanguage = true request.usesLanguageCorrection = true request.minimumTextHeightFraction = 0.016 // Perform request let textObservations: [RecognizedTextObservation] = try await request.perform(on: url) // Convert [RecognizedTextObservation] to [RecognizedText] return textObservations.compactMap { observation in observation.topCandidates(1).first } } I also found this Swift forums post mentioning something very similar. I also opened a feedback: FB17240843

Hi everyone, I'm trying to use VNDetectTextRectanglesRequest to detect text rectangles in an image. Here's my current code: guard let cgImage = image.cgImage(forProposedRect: nil, context: nil, hints: nil) else { return } let textDetectionRequest = VNDetectTextRectanglesRequest { request, error in if let error = error { print("Text detection error: \(error)") return } guard let observations = request.results as? [VNTextObservation] else { print("No text rectangles detected.") return } print("Detected \(observations.count) text rectangles.") for observation in observations { print(observation.boundingBox) } } textDetectionRequest.revision = VNDetectTextRectanglesRequestRevision1 textDetectionRequest.reportCharacterBoxes = true let handler = VNImageRequestHandler(cgImage: cgImage, orientation: .up, options: [:]) do { try handler.perform([textDetectionRequest]) } catch { print("Vision request error: \(error)") } The request completes without error, but no text rectangles are detected — the observations array is empty (count = 0). Here's a sample image I'm testing with: I expected VNTextObservation results, but I'm not getting any. Is there something I'm missing in how this API works? Or could it be a limitation of this request or revision? Thanks for any help!

HI, I've been modifying the Camera sample app found here: https://developer.apple.com/tutorials/sample-apps/capturingphotos-camerapreview ... in the processpreview images, I am calling in to the Vision APis to either detect a person or object, then I'm using the segmentation mask to extract the person and composite them onto a different background with some other filters. I am using coreimage to filter the CIImages, and converting and displaying as a SwiftUI Image. When running on my IPhone, it works fine. When running on my Iphone with the debugger, it crashes within a few seconds... Attached is a screenshot. At the top is an EXC_BAD_ACCESS in libRPAC.dylib`std::__1::__hash_table<std::__1::__hash_value_type<long, qos_info_t>, std::__1::__unordered_map_hasher<long, std::__1::__hash_value_type<long, qos_info_t>, std::__1::hash, std::__1::equal_to, true>, std::__1::__unordered_map_equal<long, std::__1::__hash_value_type<long, qos_info_t>, std::__1::equal_to, std::__1::hash, true>, std::__1::allocator<std::__1::__hash_value_type<long, qos_info_t>>>::__emplace_unique_key_args<long, std::__1::piecewise_construct_t const&, std::__1::tuple<long const&>, std::__1::tuple<>>: This was working fine a couple of days ago.. Not sure why it's popping up now. Am I correct in interpreting this as an LLDB issue? How do I fix it?

Hi, I am modifying the sample camera app that is here: https://developer.apple.com/tutorials/sample-apps/capturingphotos-camerapreview ... In the processPreviewImages, I am using the Vision APIs to generate a segmentation mask for a person/object, then compositing that person onto a different background (with some other filtering). The filtering and compositing is done via CoreImage. At the end, I convert the CIImage to a CGImage then to a SwiftUI Image. When I run it on my iPhone, it works fine, and has not crashed. When I run it on the iPhone with the debugger, it crashes within a few seconds with: EXC_BAD_ACCESS in libRPAC.dylib`std::__1::__hash_table<std::__1::__hash_value_type<long, qos_info_t>, std::__1::__unordered_map_hasher<long, std::__1::__hash_value_type<long, qos_info_t>, std::__1::hash, std::__1::equal_to, true>, std::__1::__unordered_map_equal<long, std::__1::__hash_value_type<long, qos_info_t>, std::__1::equal_to, std::__1::hash, true>, std::__1::allocator<std::__1::__hash_value_type<long, qos_info_t>>>::__emplace_unique_key_args<long, std::__1::piecewise_construct_t const&, std::__1::tuple<long const&>, std::__1::tuple<>>: It had previously been working fine with the debugger, so I'm not sure what has changed. Is there a difference in how the Vision APIs are executed if the debugger is attached vs. not?

Hi everyone, I'm using the Vision framework’s ImageAestheticsScoresObservation class (https://developer.apple.com/documentation/vision/imageaestheticsscoresobservation). I noticed that the overallScore returned sometimes gives negative values. Could someone confirm whether the expected range of the score is from -1.0 to 1.0? The documentation doesn’t explicitly state the possible score range, so I’d appreciate any clarification or insights. Thanks in advance!

I encountered some issues while developing a Vision Pro program using Unity. After binding an ARAnchor to a game object, I overlapped the virtual game object with a real-world cup. However, when I moved around with the Vision Pro on, the virtual game object shifted, causing the real-world cup and the virtual object to no longer coincide. Is there a way to solve this?

Hello, I am experimenting with Unity to develop a mixed reality (MR) application for visionOS. I would like to understand the best approach for structuring my project: Should I build the entire experience in Unity (both Windows and Volumes)? Or is it better to create only certain elements (e.g., Volumes) in Unity while managing Windows separately in Xcode? Also, how well do interactions (e.g pinch, grab…) created in Unity integrate with Xcode? If I use the PolySpatial plugin, does that allow me to manage all interactions entirely within Unity, or would I still need to handle/integrate part of it in Xcode? What's worked best for you? Please let me know if you have any recommendations, Thanks!

as in the environments we have real tiem reflections of movies on a screen or reflections of the surrounding hood in the background... could i get a metallic surface getting accurate reflections of a box on top ? i don't mean getting a rpobe or hdr cubemap, i mean the same accurate reflections as the water of the mt hood with movie i'm wacthing in other app

Hi! I attempted to run a sample project for detecting human pose in photos, which can be found here: https://developer.apple.com/documentation/vision/detecting-human-body-poses-in-3d-with-vision The project works perfectly when run on my Macbook Pro M1, but it fails on Apple Vision Pro. After selecting the photo an endless loading screen is presented and the following output is produced in the console: Failed to initialize 2D Detection Algorithm. Failed to initialize 2D Pose Estimation Algorithm. Failed to initialize algorithm modules Network path is nil: (null) Failed to initialize 2D Detection Algorithm. Failed to initialize 2D Pose Estimation Algorithm. Failed to initialize algorithm modules Unable to perform the request: Error Domain=com.apple.Vision Code=9 "Async status object reported as failed but without an error" UserInfo={NSLocalizedDescription=Async status object reported as failed but without an error}. de-activating session 70138 after timeout It seems that VNDetectHumanBodyPose3DRequest is failing on Vision Pro for some reason. Are there any additional requirements for running Vision framework on VisionOS, that I might be missing?

Hi! I attempted running a sample project for detecting human pose in 3D with vision framework, that can be found here: https://developer.apple.com/documentation/vision/detecting-human-body-poses-in-3d-with-vision. It works perfectly on my Macbook Pro M1, but fails on Apple Vision Pro. After selecting a photo, an endless loading screen is displayed and the following message is produced in the console: Failed to initialize 2D Detection Algorithm. Failed to initialize 2D Pose Estimation Algorithm. Failed to initialize algorithm modules Network path is nil: (null) Failed to initialize 2D Detection Algorithm. Failed to initialize 2D Pose Estimation Algorithm. Failed to initialize algorithm modules Unable to perform the request: Error Domain=com.apple.Vision Code=9 "Async status object reported as failed but without an error" UserInfo={NSLocalizedDescription=Async status object reported as failed but without an error}. de-activating session 70138 after timeout Is human pose detection expected to work on VisionOS? Is there any special configuration required, that I might be missing?

Hi, One can configure the languages of a (VN)RecognizeTextRequest with either: .automatic: language to be detected a specific language, say Spanish If the request is configured with .automatic and successfully detects Spanish, will the results be exactly equivalent compared to a request made with Spanish set as language? I could not find any information about this, and this is very important for the core architecture of my app. Thanks!

The goal is to achieve precise joint tracking for clinical assessment. The Doctor is wearing the AVP and observing the Patients movement. Do you have any recommended best practices for integrating real-time joint tracking and displaying them on the patient within visionOS? We attempted to use VNHumanBodyPose3DObservation, which theoretically should work, but we are unable to display the detected joints in an Immersive Space for real-time validation. This makes it difficult for the doctor to ensure accurate tracking and if possible a photo or video of the Range of Motion assessment would be needed for the patient record. Are there alternative methods to achieve precise real-time joint tracking without requiring main camera access (com.apple.developer.arkit.main-camera-access.allow)?