Hi all, I’m running into an issue when trying to reconstruct a 3D model using PhotogrammetrySession on macOS from a set of images captured via the iOS Object Capture sample app, specifically in Area mode. When I attempt to create the model from these images (using the raw Images/ folder exported directly from the capture session), I get the following errors: ERROR cv3dapi.pg: Internal error codes (2): 4011 4012 WARN cv3dapi.pg: Internal warning codes (1): 4507 Output error with code = -15 requestError: CoreOC.PhotogrammetrySession.Error.processError I use the "Images" directory directly exported from Object Capture with my iphone 12 pro max (has lidar) set to "area mode" in the object capture app here is an example heic image metadata from the sequence. heif-info Images/00044.869568833.HEIC MIME type: image/heic main brand: heic compatible brands: mif1, MiHE, MiPr, miaf, MiHB, heic image: 3024x4032 (id=49), primary tiles: 6x8, tile size: 512x512 colorspace: YCbCr, 4:2:0 bit depth: 8 thumbnail: 240x320 color profile: nclx alpha channel: no depth channel: yes size: 192x256 bits per pixel: 8 z-near: 1.173828 z-far: 2.552734 d-min: undefined d-max: undefined representation: uniform Z metadata: Exif: 960 bytes uri /tag:apple.com,2023:ObjectCapture#CameraTrackingState: 4 bytes uri /tag:apple.com,2023:ObjectCapture#CameraCalibrationData: 1015 bytes uri /tag:apple.com,2023:ObjectCapture#ObjectTransform: 48 bytes uri /tag:apple.com,2023:ObjectCapture#ObjectBoundingBox: 48 bytes uri /tag:apple.com,2023:ObjectCapture#RawFeaturePoints: 832 bytes uri /tag:apple.com,2023:ObjectCapture#PointCloudData: 23984 bytes uri /tag:apple.com,2023:ObjectCapture#BundleVersion: 5 bytes uri /tag:apple.com,2023:ObjectCapture#SegmentID: 4 bytes uri /tag:apple.com,2024:ObjectCapture#SessionUUID: 36 bytes uri /tag:apple.com,2024:ObjectCapture#CaptureMode: 4 bytes uri /tag:apple.com,2023:ObjectCapture#Feedback: 4 bytes uri /tag:apple.com,2023:ObjectCapture#WideToDepthCameraTransform: 48 bytes uri /tag:apple.com,2023:ObjectCapture#TemporalDepthPointClouds: 864026 bytes transformations: angle (ccw): 270 region annotations: none properties: camera intrinsic matrix: focal length: 2813.695557; 2813.695557 principal point: 1522.338502; 2002.843018 skew: 0.000000 camera extrinsic matrix: rotation matrix: -0.695 0.344 -0.632 0.007 -0.875 -0.483 -0.719 -0.340 0.606 Questions: • What do internal error codes 4011 and 4012 refer to? • Is there something specific about Area mode captures that require preprocessing before they’re compatible with PhotogrammetrySession? • Has anyone successfully reconstructed a model from an Area mode session using the stock Apple tools? NOTE: I can provide the folder of images for debugging if that would help!

Hi Apple Team, We noticed the following exciting changelog in the latest macOS 26 beta: A new algorithm significantly improves PhotogrammetrySession reconstruction quality of low-texture objects not captured with the ObjectCaptureSession front end. It will be downloaded and cached once in the background when the PhotogrammetrySession is used at runtime. If network isn’t available at that time, the old low quality model will be used until the new one can be downloaded. There is no code change needed to get this improved model. (145220451) However after trying this on the latest beta and running some tests we do not see any differences on objects with low textures such as single coloured surfaces. Is there anything we are missing? the machine is definitely connected to the internet but we have no way of knowing from the logs if the new model is being used? thanks

I noticed in the latest macOS beta 3 that there was this update: A new algorithm significantly improves PhotogrammetrySession reconstruction quality of low-texture objects not captured with the ObjectCaptureSession front end. It will be downloaded and cached once in the background when the PhotogrammetrySession is used at runtime. If network isn’t available at that time, the old low quality model will be used until the new one can be downloaded. There is no code change needed to get this improved model. (145220451) I am not noticing any difference to before with the reconstructions I tested so I am assuming it's reverting to the old model but in the logs there is no way to see if it succeeds or fails to download that new model. do you have any more information on what was improved here with some examples and what we should be looking for? also how can confirm the download of that new model has not failed?

Hi Apple Team, I’m working on a human portrait scanning application using PhotogrammetrySession, and I’ve been very impressed by the results. Thank you for building such a powerful and accessible photogrammetry solution into macOS! I do, however, have a question regarding mesh detail limitations on different Mac hardware configurations. When using PhotogrammetrySession.Request.Detail.custom and trying to set maximumPolygonCount = 1000000, I see the following log message: Clamped max poly count: 1000000 to device limit. 250000 is used. This is on an M1 Max with 32 GB RAM. I’m aware that PhotogrammetrySession.limits can report values like maximumInputImageDimension and maximumNumberOfInputImages, but I haven’t found documentation on how the maximumPolygonCount is determined, and what hardware specs influence it. Is it tied more to: • GPU performance (e.g. neural/graphics cores)? • CPU architecture? • Memory size or bandwidth? • Or is it fixed per SoC generation? I’d love to understand what kind of hardware upgrades (e.g. moving to M4 Pro or increasing RAM) could allow me to increase mesh complexity and generate more detailed models. Any insights would be greatly appreciated—and if this is covered in upcoming WWDC sessions or documentation, I’d be happy to tune in. Thanks in advance! KitCheng

Hi Apple Team and Developers, First of all, I’d like to express my appreciation for the incredible results achieved using PhotogrammetrySession. I’ve been developing a portrait scanning app using Object Capture, and in many tests—especially with human models—I’ve found the reconstructed body surfaces are remarkably smooth and clean, often outperforming tools like Metashape and RealityCapture in terms of aesthetic results. However, I’ve encountered some challenges when working with complex areas like long hair overlapping the face. For instance, with female models where strands of hair partially occlude the face, the resulting mesh tends to merge the hair and facial geometry. This leads to distorted or “melted” facial features, likely due to ambiguity in the geometry estimation phase. Feature Suggestion: Would it be possible to allow developers to supply two versions of the input images: • One version (original) for texture generation • A pre-processed version (e.g., contrast-enhanced or CLAHE filtered) to guide mesh reconstruction only This would give us the flexibility to enhance edge features or shadow detail without affecting the final texture appearance. In other photogrammetry pipelines, applying image enhancement selectively before dense reconstruction improves geometry quality in low-contrast areas. Question: Is there any plan to support this kind of two-path workflow in future versions of PhotogrammetrySession? Or perhaps expose more intermediate stages or tunable parameters to developers? Also, any hints on what we can expect from WWDC 2025 regarding improvements to Object Capture or related vision/3D technologies? Thanks again for this powerful API. Looking forward to hearing insights from the team and other developers. Warm regards, KitCheng

I'm simply trying to use a proxy to route a http request in Swift. I've tried using a URLSession Delegate but that results in the same issue with the iOS menu. proxy format: host:port:username:password When I run the code below I am prompted with a menu to add credentials for the proxy. I closed this menu inside my app and tried the function below again and it worked without giving me the menu a second time. However even though the function works without throwing any errors, it does NOT use the proxies to route the request. I've spent days on this and the only solution I found was using a NWConnection but this is super low level and now I need a shared session to manage cookies. If you want to see the NWConnection solution I made its here func averageProxyGroupSpeed(proxies: [String], completion: @escaping (Int, String) -> Void) { let numProxies = proxies.count if numProxies == 0 { completion(0, "No proxies") return } var totalTime: Int64 = 0 var successCount = 0 let group = DispatchGroup() let queue = DispatchQueue(label: "proxyQueue", attributes: .concurrent) let lock = NSLock() let shuffledProxies = proxies.shuffled() let selectedProxies = Array(shuffledProxies.prefix(25)) for proxy in selectedProxies { group.enter() queue.async { let proxyDetails = proxy.split(separator: ":").map(String.init) guard proxyDetails.count == 4, let port = Int(proxyDetails[1]), let url = URL(string: "http://httpbin.org/get") else { completion(0, "Invalid proxy format") group.leave() return } var request = URLRequest(url: url) request.timeoutInterval = 15 let configuration = URLSessionConfiguration.default configuration.connectionProxyDictionary = [ AnyHashable("HTTPEnable"): true, AnyHashable("HTTPProxy"): proxyDetails[0], AnyHashable("HTTPPort"): port, AnyHashable("HTTPSEnable"): false, AnyHashable("HTTPUser"): proxyDetails[2], AnyHashable("HTTPPassword"): proxyDetails[3] ] let session = URLSession(configuration: configuration) let start = Date() let task = session.dataTask(with: request) { _, _, error in defer { group.leave() } if let error = error { print("Error: \(error.localizedDescription)") } else { let duration = Date().timeIntervalSince(start) * 1000 lock.lock() totalTime += Int64(duration) successCount += 1 lock.unlock() } } task.resume() } } group.notify(queue: DispatchQueue.main) { if successCount == 0 { completion(0, "Proxies Failed") } else { let averageTime = Int(Double(totalTime) / Double(successCount)) completion(averageTime, "") } } } Delegate example class ProxySessionDelegate: NSObject, URLSessionDelegate { let username: String let password: String init(username: String, password: String) { self.username = username self.password = password } func urlSession(_ session: URLSession, task: URLSessionTask, didReceive challenge: URLAuthenticationChallenge, completionHandler: @escaping (URLSession.AuthChallengeDisposition, URLCredential?) -> Void) { if challenge.protectionSpace.authenticationMethod == NSURLAuthenticationMethodHTTPBasic { let credential = URLCredential(user: self.username, password: self.password, persistence: .forSession) completionHandler(.useCredential, credential) } else { completionHandler(.performDefaultHandling, nil) } } }

I am new here and would appreciate help in coding or an explanation what to use in swift for an app which will be able to capture LiDAR scanning and RGB data from taken pictures, generate a 3D mesh, and create .OBJ, .MTL, and .JPEG file set for further manipulation of 3D model. I am able to create from LiDAR scanning 3D mesh and .OBJ file but can not generate .MTL and .JPEG for a texture of 3D model.

I would appreciate help in coding or an explanation what to use in swift for an app which will be able to capture LiDAR scanning and RGB data from taken pictures, generate a 3D mesh, and create .OBJ, .MTL, and .JPEG file set for further manipulation of 3D model.

Hi, I created an app using iOS Object Capture API which works only on Lidar enabled phones. It's a limitation of the Api provided by apple itself. I Submitted an app for Review , but It is getting rejected (Twice) saying it doesnt work on non pro models. Even though I explained that capturing Needs Lidar and supported only in PRO models, It still gets rejected after testing in Non Pro models. is there a way out?

I would like to integrate the object capture API with a ML model for analysis. So, i will need to get the current frame into CG images for further process. Thanks in advance !

I am using RealityKit's ObjectCaptureSession API to capture objects, presenting the process with ObjectCaptureView. During the object capture session, there is default background audio that plays automatically. I noticed this same audio behavior in Apple's official Composer app, which seems to use the same API. I'd like to disable this audio in my app, but I have not been able to find any API or configuration option to do so. However, the audio persists, and I cannot find a way to turn it off. Is there an official method or workaround to disable this default audio in the ObjectCaptureSession API? Any guidance would be appreciated. Thank you!

Hi! I'm having issues retrieving the intrinsics matrix of camera poses for photogrammetry sessions. The camera object always seems to be nil, no matter what dataset I use. From the documentation, I can't see any indication of this issue, is there something I need to do on the code side? Or it's something related to the photo dataset? I'm on MacOS 15.2

I’m currently using the RealityKit/ObjectCaptureSession API to develop my app, and I’ve noticed that Apple’s official Reality Composer app also uses the same API. However, both my app and the Reality Composer app crash if the device doesn’t have enough storage space (approximately 4 GB free). Here is the debug log I’m seeing: Insufficient storage: required 4000000000 Switch to error state. Got error = insufficientStorage(requiredBytes: 4000000000) fromState == toState so punting transition! from=disabled toState=disabled Punting transition since states match: disabled Got error starting session! insufficientStorage(requiredBytes: 4000000000) I would like to request: A fix for the crash in the official Reality Composer app. Guidance on how to properly handle this crash or error when using the ObjectCaptureSession API in my own app. Thank you!

We are currently using ObjectCapture from ARKit, and we would like to fix exposure time, white balance parameter and ISO. How can we do this ? Additionally, we'd like to obtain the following information from the ARKit : white balance parameters (in case we cannot fix them) and color correction matrices ?

I am developing with Apple Vision Pro to implement object tracking functionality, but each model needs to go into Create ML for training, and the training time is very long. Are there other ways to shorten training time while obtaining reference files in the same format? Additionally, can the delay in object tracking be further optimized? Although the refresh rate has been optimized, there is still a noticeable delay.

Hello, I'm creating an app that use PhotogrammetrySession Class to build 3D objects from photographs (https://developer.apple.com/documentation/realitykit/creating-3d-objects-from-photographs). I'm wondering why this class is working only on Pro iphone (12 Pro, 13 Pro, 14 Pro, 15 Pro and 16 Pro) and none non-Pro iPhone. My app does not use Lidar so it's not the problem. I thought it could be power-related but a18 soc from iPhone 16 is more powerful than a14 bionic from iPhone 12 Pro (i could also mention iPhone 13 Pro and iPhone 14 that both have a15 bionic whereas only the first one is compatible). Did I miss something that could explain these restrictions ? Is there any plan to make this class usable by every iPhone enough powerful to run it ? Thanks in advance for answering me

We are currently using Apple's Object capture module and wonder if it would be possible to collect the following data : Device information Current translation / rotation Focal length embedded to the image headers GPS localisation information. Information about the exposure time White balances and the color correction matrices We also have 2 additional questions : Is there an option to block close up accomodation of the camera ? Is there a way for the object capture module to take a video instead of a series of picture ?

I'm really excited about the Object Capture APIs being moved to iOS, and the complex UI shown in the WWDC session. I have a few unanswered questions: Where is the sample code available from? Are the new Object Capture APIs on iOS limited to certain devices? Can we capture images from the front facing cameras?