Hello Apple AVFoundation team, Could you clarify the supported iPhone models and OS versions for standalone locked video frame duration using AVCaptureDeviceInput.activeLockedVideoFrameDuration? The API is documented as available from iOS 26.0, but I understand that OS availability alone does not mean every camera device/configuration supports it. I have read the API documentation and the DTS reply in iPhone 17 Pro's Genlock feature, but could not find a model compatibility list for the standalone locked-duration API. Scope: I am investigating actual capture timing for multi-iPhone motion capture. This question is about locking each camera's frame period using its internal timing, without an external genlock accessory. I am not asking about encoding a constant-frame-rate file, ordinary equal min/max frame durations, timecode metadata, or synchronizing the first exposure across phones. Physical-device test iPhone 16 Pro, iOS 26.2 (23C55). Built with Xcode 26.3 and the iOS 26.2 SDK. One AVCaptureSession, one physical rear .builtInWideAngleCamera input, and one AVCaptureVideoDataOutput. 8-bit SDR 420v formats, tested at 1920 x 1080 and 3840 x 2160, each at 30 and 60 fps. Auto video frame rate disabled; no spatial video capture or multicam session. Manual exposure approximately 2 ms, shorter than half a frame at both tested rates. The session is running and delivering frames. Two separate probe runs produced the same results, including capability readbacks after a settling period. For all four tested configurations: input.isLockedVideoFrameDurationSupported = false device.minSupportedLockedVideoFrameDuration = kCMTimeInvalid input.activeLockedVideoFrameDuration = kCMTimeInvalid device.isVideoFrameDurationLocked = falseOrdinary activeVideoMinFrameDuration and activeVideoMaxFrameDuration can both be set to the requested CMTime(value: 1, timescale: 30) or CMTime(value: 1, timescale: 60), and frames are delivered. This is only a configuration readback, not a claim of exact capture timing in the ordinary mode. The app directly queries the public support properties; it has no model whitelist. It does not attempt to set a valid locked duration when support is false, as the documented setter contract would reject that. These tests cover the selected formats, not every camera/format on this phone. Questions Which iPhone models support this standalone API? In particular, is false expected on iPhone 16 Pro? Is there an official compatibility list covering iPhone 13/14/15/16 and iPhone 17 models? Is the iPhone 16 Pro result a hardware capability restriction, an iOS 26.2 limitation/known issue, or a configuration requirement? Is there a released iOS version that enables this on iPhone 16 Pro, or is newer hardware required? What is the minimum supported capture configuration and correct time to query support? Are there restrictions involving the physical versus virtual camera input, pixel format, SDR/HDR, or exposure mode that could explain this result? If so, which configuration should be tested before concluding that the device does not support it? On supported hardware, can this standalone lock be enabled without an external accessory or a special entitlement, independently of follow(_:videoFrameDuration:delegate:)? Relevant documentation: activeLockedVideoFrameDuration isLockedVideoFrameDurationSupported minSupportedLockedVideoFrameDuration I can provide a focused reproducer if needed. Thank you for clarifying the device requirements and whether an OS upgrade can change the result.

Hi everyone, I'm developing an iOS camera app that aims to record 4224×3024 Open Gate video at 60fps in 10-bit HEVC with Apple Log 2. Native Apple ISP-processed Apple Log 2 capture works at 3840×2160/60fps. However, at 4224×3024/60fps, the tested capture configuration only provides Bayer RAW (btp2). I've successfully decoded ProRes RAW using Apple's decoder into linear Rec.2020 and applied the published Apple Gamut and Apple Log 2 transforms. However, the resulting chroma is only approximately 72–74% of the native ISP output in controlled color-chart comparisons. I've also confirmed that VTRAWProcessingSession and related RAW processing controls are not publicly available to iOS apps in the iPhoneOS 27.0 SDK. My questions are: Is there a public iOS API that applies the same color and tone rendering as Apple's native camera ISP to captured Bayer RAW or ProRes RAW? Is there a supported configuration for obtaining full-resolution 4224×3024/60fps ISP-processed Apple Log 2 output (x420 or x422), without preview proxies or upscaling? If neither is supported, what is Apple's recommended approach? Is this a hardware limitation or a public API limitation? The goal is to use Apple's official color processing pipeline without empirically fitted matrices, LUTs, or arbitrary color corrections. Any guidance would be greatly appreciated. Thank you!

I am working on a computational photography research project involving multi-exposure HDR reconstruction using Bayer RAW and Apple ProRAW captures. I would like to clarify the radiometric interpretation of Apple ProRAW and the availability of Bayer RAW capture through AVFoundation. My questions are: On current iPhone Pro devices, is it possible for third-party apps to capture and export true Bayer-pattern RAW DNG files through AVFoundation, rather than Apple ProRAW linear DNG files? If so, which availableRawPhotoPixelFormatTypes correspond to Bayer RAW, and what device or format restrictions apply? Apple ProRAW appears to be demosaiced and computationally processed, and may include multi-frame fusion. Is the decoded ProRAW image intended to be radiometrically linear and scene-referred? For a bracketed ProRAW sequence captured with fixed ISO, white balance, lens, and focus, but different exposure times, can one assume that the decoded linear pixel values Y_i(p) satisfy an exposure-proportional model in non-saturated regions, such as Y_i(p) ≈ t_i R(p), across brackets? This question is about radiometric consistency for algorithmic use, not about visual editing or tone mapping. Thank you for your help.

I am working on a computational photography research project involving multi-exposure HDR reconstruction using Bayer RAW and Apple ProRAW captures. I would like to clarify the radiometric interpretation of Apple ProRAW and the availability of Bayer RAW capture through AVFoundation. My questions are: 1.On current iPhone Pro devices, is it possible for third-party apps to capture and export true Bayer-pattern RAW DNG files through AVFoundation, rather than Apple ProRAW linear DNG files? If so, which availableRawPhotoPixelFormatTypes correspond to Bayer RAW, and what device or format restrictions apply? 2.Apple ProRAW appears to be demosaiced and computationally processed, and may include multi-frame fusion. Is the decoded ProRAW image intended to be radiometrically linear and scene-referred? 3.For a bracketed ProRAW sequence captured with fixed ISO, white balance, lens, and focus, but different exposure times, can one assume that the decoded linear pixel values Y_i(p) satisfy an exposure-proportional model in non-saturated regions, such as Y_i(p) ≈ t_i R(p), across brackets? This question is about radiometric consistency for algorithmic use, not about visual editing or tone mapping. Thank you for your help.

We build a medical scanning app. A practitioner walks a slow orbit (~1 m radius, two laps, 25–35 s) around a standing subject while an ARSession runs, and we capture ~50 high-resolution stills with captureHighResolutionFrame. The ARKit camera poses for those frames are later used to set the metric scale of a photogrammetry reconstruction. We need the resulting scale to be within about 2 % of true. What we observe, measured against a printed A4 sheet on the floor in every scan: Devices with LiDAR (iPhone 16 Pro Max, iPad Pro), using the sceneDepth frame semantic as a check: scale within ±0.8 % across 11 sessions. Devices without LiDAR (iPhone 13, iPad 9th and 11th gen, plus non-LiDAR runs on the Pro devices): the world-frame metre is on average 2–3 % short of true, and varies by a further ±2 % from one session to the next, across 24 sessions in four rooms. Within a session the scale is stable: lap-to-lap variation is under 0.4 %. The error appears to be set during initialisation and held. Nothing we record about capture correlates with the error: time spent before capture, distance walked, vertical camera movement, orbit radius, rotation speed, tracking state, or the residual of our pose fit. Questions: Is there any session setup, initialisation practice, or motion during the first seconds of tracking that is known to improve the metric scale estimate on devices without LiDAR? Does the choice of video format, resolution or frame rate affect scale estimation? Is there any signal, beyond ARCamera.trackingState, that indicates how well scale has been determined for a session, so we could flag sessions rather than accept them? Does anything in the configuration above, in particular locking exposure on the capture device or using the high-resolution video format, work against tracking quality or scale?

At the WWDC26 Camera and Photo Technologies Group Lab (session 8018, ~29:55 to 32:46), the panel explained why ProRAW can produce 48 MP output from Quad Bayer sensors while native Bayer RAW is limited to the binned resolution. ProRAW is already demosaiced and linearized, and may incorporate Photonic Engine multi-frame processing. The native RAW path exposes the binned Bayer result. A true full-resolution RAW output would be Quad Bayer, not conventional Bayer, and supporting it properly needs a decoding path around it. The panel suggested filing Feedback Assistant requests if developers need this, so I filed FB25352517. My use case is computational photography that wants minimally processed sensor-domain samples on purpose — its own multi-frame alignment, denoising, HDR fusion, motion rejection, and super-resolution. Adobe Project Indigo is a public example of that kind of pipeline. It captures RAW bursts and uses measured sub-pixel variation between frames to reconstruct detail. Processed 48 MP photos and ProRAW don't cover that. They've already been through Apple's reconstruction or demosaic. Is filing enhancement requests still the intended path for a supported full-resolution Quad Bayer RAW or mosaic capture path? If so, what would make these reports more useful — mosaic metadata, DNG representation, CIRAWFilter support, AVCaptureDevice.Format capability discovery, something else? WWDC26 session: https://developer.apple.com/videos/play/wwdc2026/8018/ Project Indigo technical overview: https://research.adobe.com/articles/indigo/indigo.html

Hi everyone, I've been reading about iPhone camera sensors recently, and there's something I've been wondering about. Apple has explained the benefits of Quad Bayer, especially pixel binning for low-light photography and high-resolution capture. But why not use a traditional Bayer sensor with Dual Pixel PDAF instead? As far as I understand, a native Bayer arrangement could potentially preserve more fine detail without requiring remosaicing. And if both sensors have the same size and pixel count, couldn't the Bayer sensor also produce a cleaner 12MP image by downsampling? I'm also curious about the microlens design. Some sensors use one microlens shared by four pixels for phase detection. Wouldn't individual microlenses potentially offer better spatial resolution? So my main question is: What hardware-level advantages make Quad Bayer worth choosing over traditional Bayer, despite the additional image reconstruction involved? Is it mainly about read noise, analog binning, power efficiency, autofocus, or something else? I'm not a camera engineer, just someone interested in understanding the technology behind iPhone cameras. I'd really appreciate any technical insight. Thanks!

I am encountering an issue where the Lock Screen Quick Action fails to visibly open my app. My app is a camera application that utilizes a CameraCaptureIntent to launch a standalone, lightweight camera view (accessible while the device is locked), distinct from the main application. Steps to Reproduce: Open the lightweight camera view using the Lock Screen Quick Action. From this view, launch the Main App. Lock the iPhone (put it to sleep). Attempt to launch the lightweight camera view via the Quick Action again. A slight animation occurs, but the camera view does not appear on screen. After multiple tests, it seems the view is actually launching but remains in an "invisible state." I suspect that the system hides the lightweight camera view when transitioning to the Main App, but fails to reset this hidden state when the Quick Action is triggered subsequently. I would appreciate any guidance on a potential workaround or confirmation if this is a known issue awaiting a system update.

I am a private individual working on a personal panorama viewing and reprojection project. I have been investigating the geometry of panoramas produced by the iPhone Camera app, with extensive analytical and research assistance from OpenAI's ChatGPT. My goal is to determine the physical viewing direction (longitude and latitude, or equivalently a 3-D viewing ray) corresponding to each pixel in a finished iPhone panorama. I have been able to recover much of this geometry from information contained in the panorama itself. Controlled tests on several iPhone models indicate that I can accurately determine the effective focal length of the perspective source camera, camera rotation during capture, endpoint geometry, horizontal field of view, and gravity-relative camera orientation. The remaining problem is the absolute vertical/latitude mapping in the finished panorama. The gravity/orientation information allows me to determine where a known physical latitude—for example, the true horizontal plane (0° latitude)—falls in the individual source-camera frames. However, I have not found a documented way to determine exactly where those source-frame viewing rays are placed vertically in the final panorama bitmap. My investigation suggests that the Camera app performs additional geometric processing during panorama assembly, including geometric/perspective correction and the selection, cropping and/or rotation of image slices before they are blended into the panorama. What I have not been able to determine is whether the information needed to reconstruct that source-ray-to-finished-pixel mapping is retained anywhere in the finished panorama or is available through a supported Apple API. My primary question is therefore: Is there a documented or supported way to determine the physical viewing ray corresponding to each pixel in a panorama produced by the iPhone Camera app, including its absolute vertical/latitude mapping? More specifically: Is the projection used for the finished Camera panorama documented? Is the gravity-relative orientation or vertical reference of that projection available through supported metadata or an API? Is sufficient information retained in the panorama to reconstruct the geometric correction and placement applied to source images/slices during panorama assembly? If that information is not retained in the finished image, is there another supported framework or API that provides it during or after panorama capture? I am not trying to reproduce Apple's image blending or other proprietary image-processing algorithms. I simply want to interpret the geometry of the finished image accurately enough to reproject it—for example, to cylindrical or equirectangular coordinates—and assign physical longitude and latitude to its pixels. I have controlled test panoramas from multiple iPhone generations and considerably more technical detail about the investigation. I would be happy to provide example files, measurements, or additional information if that would be helpful. Even confirmation that the required vertical-placement information is not retained or exposed would be very useful.

As a reminder, the recommended approach to monitor camera rotations, including on upcoming hardware, is to use the AVCaptureDevice.RotationCoordinator / AVCaptureDeviceRotationCoordinator API. In many common scenarios on iPhone Duo, proper use of the rotation coordinator is the only way to ensure that your camera previews and captures use the orientation expected by the user. AVCaptureVideoOrientation has been deprecated as of iOS 17.0 and iPadOS 17.0. When switching cameras in your app, make sure to create a rotation coordinator for that device. To ensure that your app has implemented the rotation coordinator API correctly, you should test different orientations and sizes of your app on an iPad with Stage Manager enabled. Additional information: Sample Code: Supporting device rotation in your camera app Tech Talk: Build a great camera experience for iPhone Duo WWDC23 session: Support external cameras in your iPadOS app

We're building a simple iPhone app that shows a live view from the rear camera in Picture in Picture while the user is in other apps. The camera feed is only displayed. It's never recorded, stored or transmitted, and the app has no network access. In testing on an iPhone 15 Pro (iOS 26.6.2) with Xcode 26.6, the camera keeps running behind PiP only when the app declares the voip background mode. Without it, as documented, isMultitaskingCameraAccessSupported is false and the capture session is interrupted with videoDeviceNotAvailableWithMultipleForegroundApps as soon as PiP starts. Our app isn't a calling app, so we don't want to rely on voip. Two questions: Is the com.apple.developer.avfoundation.multitasking-camera-access entitlement available to non-calling apps with a use case like this? If so, how should we request it? If not, is there any supported way for a non-calling app to keep a live camera preview running in PiP on iPhone? I'm happy to share a short screen recording of the prototype.

How can I tell which DNG opcode belongs to which OpcodeList for a RAW image captured by AVPhotoOutput? I couldn't find any of the OpcodeList1, OpcodeList2 or OpcodeList3 tags in the DNG metadata inside AVCapturePhoto.metadata, but when exporting the photo into a DNG file to disk and extracting that DNG file's metadata using exiftool on a computer, I could see the opcodes in their respective opcode lists. Can I get the opcode lists without exporting into DNG data representation and then parsing the DNG file?

Since upgrading to macOS 27 Golden Gate, my Mac Studio (M4) recognises my Logitech MX Brio 4K webcam, but no video feed is displayed. The camera appears to be detected by the system, but the video signal does not show up in: FaceTime Photo Booth Logitech Options+ I've spent quite a bit of time troubleshooting the issue, including following diagnostic steps suggested by Siri and Copilot, but everything points to a potential macOS-related problem rather than a hardware or configuration issue. Has anyone else experienced this with the MX Brio or other webcams on macOS 27 Golden Gate? I reported the issue to Apple through the Feedback app when Beta 1 was released, but so far I haven't received a response or found a workaround. Any insights or suggestions would be greatly appreciated. Thanks!

Hi everyone, I recently updated my MacBook Pro (14-inch, M1 Pro) to macOS 27, and I've noticed a significant drop in the built-in FaceTime HD camera quality. The video feed looks incredibly grainy and noisy, almost like it's struggling with digital artifacts, even in well-lit rooms where it used to look perfectly crisp. Here is what I've tried so far to fix it: • Restarted the Mac multiple times. • Cleaned the physical camera lens with a microfiber cloth. • Tested across multiple apps (FaceTime, Zoom, Google Meet, and Photo Booth) - the graininess happens everywhere, so it isn't isolated to just one app. The camera worked beautifully on previous macOS versions (26.x), so this definitely feels like a software processing bug or an issue with how macOS 27 handles the camera. Is anyone else experiencing this on their M1 Pro machine after the update? Are there any known workarounds, or do we just have to wait for Apple to push a supplemental software patch? Thanks in advance for any insights!

Hi Apple team, I’m developing Awaira, an iPhone app that runs real-time, on-device camera detection during a user-initiated support session. Its purpose is to help users notice hand-to-hair behavior. The user explicitly starts and stops the session; the camera indicator remains visible; camera frames are processed on-device; and the app does not record or transmit video. A common user request is to continue the session while using another app. On Android, this can be implemented with visible foreground-service behavior. On iOS, the capture session stops when Awaira is no longer foreground. I found AVCaptureSession.isMultitaskingCameraAccessSupported and isMultitaskingCameraAccessEnabled. The documentation says iOS 18 apps using UIBackgroundModes = voip may support multitasking camera access, and Apple’s PiP documentation discusses video-call apps. We do not provide a genuine person-to-person VoIP or video-calling service, and we do not want to misuse the VoIP background mode or create a fake call solely to keep camera detection active. Could Apple clarify: Is there any App-Review-approved API or entitlement for this kind of explicit, visible, user-initiated on-device camera session to continue while another app is foreground? Is declaring voip and using the multitasking-camera API permitted only for genuine VoIP/video-call apps? If no current approved path exists, is there a recommended design pattern for this accessibility/health-oriented use case? We will only ship an implementation that complies with the intended purpose of Apple’s APIs and App Review Guidelines. https://developer.apple.com/documentation/avfoundation/avcapturesession/ismultitaskingcameraaccesssupported Thank you.

“When the device opens or closes and the camera automatically changes, how does the systems decide which camera provides the best experience”???

I build Lumecast, a live-streaming app (custom AVCapture pipeline feeding WebRTC). Three questions:   1. Does iPhone Duo support AVCaptureMultiCamSession — specifically front + rear simultaneously? Our co-casting feature would let a solo host fill two panes with their face and what they're looking at. How should a continuous capture session (live broadcast, can't pause) respond to camera direction changes as the device opens and closes? Is there a recommended pattern for swapping to the Virtual Front Camera mid-session without a visible gap for viewers?  3. Which cameras are available to third-party apps in each posture (folded / half-open / fully open), and does availability change at a specific hinge state? Goal: a host folds or unfolds mid-broadcast and their audience never sees a dropped frame.

is AVCaptureMultiCamSession supported on iPhone Duo — specifically streaming two cameras that face opposite directions simultaneously (e.g. .builtInInnerUltraWideCamera + .builtInOuterUltraWideCamera, or the Virtual Front Camera plus a backward-facing camera)? I noticed the article recommends single-input reconfiguration over multi-cam; is that a performance recommendation, or is opposite-direction multi-cam unavailable on this device? Our use case is a live co-cast where one host fills two video panes: their face and what they're looking at.

According to Apple's press release (https://www.apple.com/pt/newsroom/2026/09/apple-debuts-iphone-18-pro-and-iphone-18-pro-max/): Variable aperture also provides more control for creative pros by giving them the ability to manually adjust any of the four aperture settings in the Camera app, and an API is available to developers for even more control across the aperture range in their apps. Can a DTS engineer specify the quoted API please? I can't see it anywhere in the documentation yet. What does it mean "even more control across the aperture range"? Will it be possible to set the aperture in a 0.0-1.0 range?

Group Labs are a unique opportunity for the community to submit questions directly to a panel of Apple engineers and designers. Here are the highlights from the iPhone Duo Group Labs: How should apps preserve navigation and UI state when switching between the inner and outer displays? Treat display transitions as size-class and trait changes, not a scene disconnect or app termination; your process stays alive. For more information, see Prepare your app for iPhone Duo. For state that must survive a scene disconnect/reconnect, implement stateRestorationActivity(for:) to save an NSUserActivity Restoring your app's state. Do multiple instances of the same app on iPhone Duo share UserDefaults/@AppStorage state? Multiple instances of your app's UI on iPhone Duo behave similarly to multi-window support on iPadOS. To learn more, see Leverage multiple displays and scenes on iPhone Duo. Both UserDefaults and AppStorage are app-wide, not per-window, stores. If a full-screen app on the inner display is closed, does it move to the outer display or get backgrounded? iPhone Duo honors UIRequiresFullScreen and apps adapt in place as the device opens and closes rather than backgrounding. To learn more, watch Prepare your app for iPhone Duo. How should apps preserve state — text input, scroll position, video playback, camera sessions — during hinge angle transitions? For example, when a LazyVGrid's column count changes because the device folds, does SwiftUI preserve scroll position automatically, or should you use scrollPosition(id:)? The system generally preserves text input and scroll position automatically since hinge angle changes are represented as size-class and trait updates, not a scene disconnect or app termination. This applies even to cases like a LazyVGrid column-count change triggered by opening or closing the device — apps typically don't need to manually manage scroll position with scrollPosition(id:anchor:) for this transition. For more info, see Prepare your app for iPhone Duo. How can apps preserve what someone is doing when switching displays or folding/unfolding? Treat this as a resize/trait-change event, not app teardown — your process keeps running as size classes change. See Prepare your app for iPhone Duo to learn more. For scenes that actually disconnect and reconnect, implement stateRestorationActivity(for:) to save an NSUserActivity Restoring your app's state. How does actively playing video behave through the hinge angle animation? The system generally preserves video playback and player position automatically since hinge angle changes are represented as size-class and trait updates, not a scene disconnect or app termination. AVKit will scale and resize the video automatically. If a user folds or unfolds the device mid-checkout, what does the system preserve automatically, and what should the app manage itself to avoid lost input or duplicate requests? When someone opens or closes an iPhone Duo, the system represents this as a size-class and trait collection change, not a scene disconnect or app teardown, so in-memory state like input fields typically persists automatically since the app’s process keeps running. For more info, see Prepare your app for iPhone Duo. How should apps handle the keyboard and text input when the device folds or unfolds while typing? As iPhone Duo folds or unfolds, the available screen geometry and framing change. Ensure your app adopts standard layout controls, containers, and size classes to handle resizability gracefully across all poses. When a text field becomes first responder, the system automatically shows the keyboard and binds its input to the text field. Because the appearance of the keyboard has the potential to obscure portions of your user interface, you should update your interface as needed to ensure that the text field being edited remains visible. Use keyboard notifications such as keyboardWillShowNotification, keyboardWillHideNotification, and keyboardWillChangeFrameNotification to detect the appearance and disappearance of the keyboard and to make necessary changes to your interface layout. To learn more, see UITextField. If someone is typing and closes iPhone Duo, does the keyboard/editing session survive the hinge transition, or does it get a new scene? When a user types and closes iPhone Duo, the active editing session and keyboard do not get a completely new scene. Instead, the app undergoes a dynamic resizing and transitions from the inner display to the compact outer display, maintaining the existing scene and application state. For more info, watch Prepare your app for iPhone Duo.