Photos & Camera

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Explore technical aspects of capturing high-quality photos and videos, including exposure control, focus modes, and RAW capture options.

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Dockkit custom tracking does not work on iOS18.3
Hi all, I'm using Apple Sample Code below to create application using dockkit. "Controlling a DockKit accessory using your camera app" https://developer.apple.com/documentation/dockkit/controlling-a-dockkit-accessory-using-your-camera-app?changes=_8 I used vision hand recognition and put the observation data to dockAccessory.track, but Belkin or Insta360 devices never move on iPhone 16 Pro Max with iOS 18.3. If I use other functions like face search (system tracking) in the app, those work ok. I used Belkin and Insta360 Flow 2 Pro to reproduce the problem. My friend is also saying that the custom tracking feature was working fine on the OS 18 beta, but on recent iOS 18.3 that feature does not work. If I can get the iOS 18.0 beta then we can test that feature. But I cannot revert my iOS from 18.3 to the iOS 18.0 Beta. Regards, TO
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CIRAWFilter.outputImage first-time cost is huge (~3s), subsequent calls are ~3ms. Any official way to pre-initialize RAW pipeline (without taking a real photo)?
Hi Apple Developer Forums, I’m developing an iOS camera app that processes RAW captures using Core Image. I’m seeing a large “first use” performance penalty specifically when creating the CIImage from CIRAWFilter.outputImage. What’s slow (important detail) I’m measuring the time for: let rawFilter = CIRAWFilter(imageData: rawData, identifierHint: hint) let ciImage = rawFilter.outputImage This is not CIContext.render(...) / createCGImage(...). It’s just the time to access outputImage (i.e., building the Core Image graph / RAW pipeline setup). Observed behavior First time accessing CIRAWFilter.outputImage: ~3 seconds Second time (same app session, similar RAW): ~3 milliseconds So something heavy is happening only on first use (decoder initialization, pipeline setup, shader/library compilation, caching, etc.). Using Metal System Trace, I also noticed that during the slow first call there are many “Create MTLLibrary” events, while the second call doesn’t show this pattern. Warm-up attempts using bundled DNG I tried to “warm up” early (e.g., on camera screen entry) by loading a bundled DNG and then accessing CIRAWFilter.outputImage by taking a photo: Warm-up with a ~247 KB DNG → first real RAW outputImage cost drops to ~1.42s Warm-up with a ~25 MB DNG → first real RAW outputImage cost drops to ~843ms This helps, but it’s still far from the steady-state ~3ms. Warm-up by capturing a real RAW (works, but concerns) The only method that fully eliminates the delay is to trigger a real RAW capture programmatically before the user’s first photo, then use that captured rawData to warm up the CIRAWFilter.outputImage path. This brings the first user-facing capture close to the steady-state timing. However: In some regions, the camera shutter sound cannot be suppressed, so “hidden warm-up capture” is unacceptable UX. I’m also unsure whether triggering a real capture without an explicit user action could raise compliance/privacy concerns, even if the image is immediately discarded and never saved/uploaded. Questions Is the large first-time cost of CIRAWFilter.outputImage expected (RAW pipeline initialization / shader compilation)? Is there an Apple-recommended way to pre-initialize the Core Image RAW pipeline / Metal resources so the first outputImage is fast, without taking a real photo? Are there any best practices (e.g. CIContext creation timing, prepareRender(...), specific options) that reliably reduce this first-use overhead for CIRAWFilter? Attachments Figure 1: First RAW capture with no warm-up (~3s outputImage time) Figure 2: First RAW capture after warm-up with bundled DNG (improved but still hundreds of ms) Thanks for any guidance or experience sharing!
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Orientation does not work on iPhone 17 and above.
I'm receiving output from avcapturesession and capturing an image using Vision, but the image is output in landscape orientation instead of portrait. Even when I set the orientation to up in ciimage, cgimage, and uiimage, the image is still output in landscape orientation. On iPhones 16 and below, the image is output in portrait orientation. But on iPhones 17 and above, the image is output in landscape orientation. Please help.
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Background Upload Extension
Hello, We are trying to use the new Background Upload Extension to improve uploads of assets (Photos, Live Photos, Videos) in the background in our application. 1-The assets have finished uploading, but I'm unable to retrieve successful records using PHAssetResourceUploadJob.fetchJobs(action: .acknowledge, options: nil). When will the successful records be returned? 2-How to retrieve the system's pending tasks ? We want to cancel tasks handed over to the system when returning to the main app to avoid duplicate resource uploads. 3-When we set UploadJobExtensionEnabled = true, will tasks handed over to the system still execute after returning to the main app? Do we need to set UploadJobExtensionEnabled = false upon returning to the main app? If we set UploadJobExtensionEnabled = false, will previously submitted upload tasks be cleared?
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Background Upload Extension For iOS 26.1
Hello, We are trying to use the new Background Upload Extension to improve uploads of assets (Photos, Live Photos, Videos) in the background in our application. 1-The assets have finished uploading, but I'm unable to retrieve successful records using PHAssetResourceUploadJob.fetchJobs(action: .acknowledge, options: nil). When will the successful records be returned? 2-How to retrieve the system's pending tasks? We want to cancel tasks handed over to the system when returning to the main app to avoid duplicate resource uploads. 3-When we set UploadJobExtensionEnabled = true, will tasks handed over to the system still execute after returning to the main app? Do we need to set UploadJobExtensionEnabled = false upon returning to the main app? If we set UploadJobExtensionEnabled = false, will previously submitted upload tasks be cleared?
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AVExternalStorageDeviceDiscoverySession.isSupported returns true only on iPhone Pro models
I am developing an iOS camera app that can record video directly to external storage connected to an iPhone. To detect whether an external USB storage device is connected and to obtain its URL, I am considering using AVExternalStorageDeviceDiscoverySession. However, when checking support using AVExternalStorageDeviceDiscoverySession.isSupported, I observe that it returns true only on Pro model iPhones, and false on non-Pro models in my environment. I have reviewed Apple’s official documentation, but I could not find any clear description of the supported devices or requirements (for example, whether this API is limited to Pro models or requires specific hardware capabilities). I would appreciate any information regarding the following points: ●The actual requirements for AVExternalStorageDeviceDiscoverySession to be supported Device limitations (Pro vs non-Pro models) Hardware requirements (USB controller, external recording capability, etc.) iOS version dependencies ●Whether support for non-Pro models is planned in the future Tested environments iPhone 16 Pro (iOS 18.7.1) → isSupported == true iPhone 16e (iOS 26.2) → isSupported == false iPhone 17 (iOS 26.2) → isSupported == false iPhone Air (iOS 26.2) → isSupported == false If anyone has observed similar behavior or has official information from Apple regarding this API, I would greatly appreciate your insights.
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AVExternalStorageDeviceDiscoverySession.isSupported returns true only on iPhone Pro models
I am developing an iOS camera app that can record video directly to external storage connected to an iPhone. To detect whether an external USB storage device is connected and to obtain its URL, I am considering using AVExternalStorageDeviceDiscoverySession. However, when checking support using AVExternalStorageDeviceDiscoverySession.isSupported, I observe that it returns true only on Pro model iPhones, and false on non-Pro models in my environment. I have reviewed Apple’s official documentation, but I could not find any clear description of the supported devices or requirements (for example, whether this API is limited to Pro models or requires specific hardware capabilities). I would appreciate any information regarding the following points: ①The actual requirements for AVExternalStorageDeviceDiscoverySession to be supported Device limitations (Pro vs non-Pro models) Hardware requirements (USB controller, external recording capability, etc.) iOS version dependencies ②Whether support for non-Pro models is planned in the future Tested environments iPhone 16 Pro (iOS 18.7.1) → isSupported == true iPhone 16e (iOS 26.2) → isSupported == false iPhone 17 (iOS 26.2) → isSupported == false iPhone Air (iOS 26.2) → isSupported == false If anyone has observed similar behavior or has official information from Apple regarding this API, I would greatly appreciate your insights.
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Recurring FigXPCUtilities / FigCaptureSourceRemote err=-17281 logs when using AVCaptureVideoDataOutput on iOS 26.x
Hi everyone, I’m seeing recurring internal AVFoundation camera logs on iOS 26.2 and I’m trying to understand whether this is expected behavior or a regression in the capture pipeline. These logs appear shortly after starting an AVCaptureSession, while video frames are being delivered, and also when the camera is stopped or the capture session is torn down. <<<< FigXPCUtilities >>>> signalled err=-17281 at <>:302 <<<< FigCaptureSourceRemote >>>> Fig assert: "err == 0 " at bail (FigCaptureSourceRemote.m:569) - (err=-17281) Even in this clean, minimal setup, the same logs appear on iOS 26.2 The exact same logic did not produce these logs on iOS 18.x. To rule out issues caused by my own code, GPT created a minimal SwiftUI example from scratch. My primary interest is to perform real-time processing on the video frames delivered by the camera (via AVCaptureVideoDataOutput), for tasks such as analysis, computer vision, or custom frame handling, while simultaneously displaying the live preview. Thanks in advance for any insight. Example Code
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