Hi, I'm investigating whether 18MP photo capture from the front camera on iPhone 17 Pro is available to third-party apps using AVFoundation. I first inspected all available AVCaptureDevice formats, but I could not find any format corresponding to ~18MP resolution (e.g., around 4896×3672). for format in device.formats { let desc = format.formatDescription let dims = CMVideoFormatDescriptionGetDimensions(desc) print("Format: (dims.width) x (dims.height)") } All reported formats appear to be limited to resolutions such as 4032×3024 (12MP) or below. Question: Is 18MP front camera capture actually available to third-party apps via AVFoundation on iPhone 17?

MPVolumeView's showsRouteButton was deprecated (https://developer.apple.com/documentation/mediaplayer/mpvolumeview/showsroutebutton?language=objc). It's not clear how can we now hide this button without deprecation warning. The documentation is lacking. Please advise. Thank you!

We have an application that capture audio and video. App captures audio PCM on internal or external microphone and displays audio level on the screen. App was working fine for many years but after iOS 26.4 upgrade, averagePowerLevel and peakHoldLevel are stuck to -120 values. Any suggestion?

Hello there, Our application has HLS VOD download option. Users can download VOD which has DRM protection and watch content when device is offline. We use aggregateAssetDownloadTask to download HLS VOD. We want to resume download after Wifi/LTE change but it does not resume. Download is starting from beginning. We use some token algorithms to start download. That's why, our playlist url and chunks urls may change. But playlist and chunk urls' content is unique. If user start to download via Wifi and changed to LTE. Download request responds 403 Forbidden because of some token algorithms after some time func urlSession(_ session: URLSession, task: URLSessionTask, didCompleteWithError error: Error?) AVAssetDownloadDelegate function triggered by system. If we resume it does not resume at this point. It is starting from beginning if we start new download process for same content. Is there any way to resume unfinished HLS Download processes? Thanks

I'm developing an audio player app that uses AVAudio​File to read PCM data from various formats. I'm experiencing severe performance issues when seeking in FLAC, while other compressed formats (M4A/AAC) work correctly. I don't intend to use them in my app, but I also tested mp3 files just by curiosity and they also have this issue. Environment: macOS 26 (Tahoe) Xcode 26.3 Apple Silicon (M1) The issue: After setting AVAudio​File​.frame​Position to a position mid-file, the subsequent call to AVAudio​File​.read(into​:frame​Count:) blocks for an unreasonable amount of time for FLAC and MP3 files. The delay scales linearly with the seek target, seeking near the beginning is fast, seeking toward the end is proportionally slower, which suggests the decoder is decoding linearly from the beginning of the file rather than using any seek index. (My app deals with “images” of Audio CDs ripped as a single long audio file.) The issue is particularly severe when reading files from an SMB network share (server on Ethernet, client on Wi-Fi with the access point ~2 meters away in line of sight). Quick Benchmark results: I tested with the same 75-minute audio content (16-bit/44.1 kHz stereo, 200,502,708 frames) encoded in five formats, seeking to the midpoint. Over SMB (Local Network, Server on Ethernet, Client on WiFi): Format | Seek + Read Time ----------|------------------ WAV | 0.007 s AIFF | 0.009 s Apple | 0.015 s Lossless | MP3 | 9.2 s FLAC | 30.2 s Locally (MacBook Air M1 SSD) : Format | Seek + Read Time ----------|------------------ WAV | 0.0005 s AIFF | 0.0004 s Apple | 0.0011 s Lossless | MP3 | 0.1958 s FLAC | 0.7528 s WAV, AIFF, and M4A all seek virtually instantly (< 15 ms). MP3 and FLAC exhibit linear-time behavior, with FLAC being the worst affected. Note that M4A (AAC) is also a compressed format that requires decoding after seeking, yet it completes in 15 ms. This rules out any inherent limitation of compressed formats, the MP4 container's packet index (stts/stco) is clearly being used for fast random access. Both MP3 (Xing/LAME TOC) and FLAC (SEEKTABLE metadata block) have their own seek mechanisms that should provide similar performance. Minimal CLI tool to reproduce: import Foundation guard CommandLine.arguments.count > 1 else { print("Usage: FLACSpeed <audio-file-path>") exit(1) } let path = CommandLine.arguments[1] let fileURL = URL(fileURLWithPath: path) do { let file = try AVAudioFile(forReading: fileURL) let format = file.processingFormat let buffer = AVAudioPCMBuffer(pcmFormat: format, frameCapacity: 8192)! let totalFrames = file.length let seekTarget = totalFrames / 2 print("File: \(fileURL.lastPathComponent)") print("Format: \(format)") print("Total frames: \(totalFrames)") print("Seeking to frame: \(seekTarget)") file.framePosition = seekTarget let start = CFAbsoluteTimeGetCurrent() try file.read(into: buffer, frameCount: 8192) let elapsed = CFAbsoluteTimeGetCurrent() - start print("Read after seek took \(elapsed) seconds") } catch { print("Error: \(error.localizedDescription)") exit(1) } Expected behavior: AVAudio​File​.read(into​:frame​Count:) after setting frame​Position should use the available seek mechanisms in FLAC and MP3 files for fast random access, as it already does for M4A (AAC). Even accounting for the fact that seek tables provide approximate (not sample-precise) positioning, the "jump to nearest index point + decode forward" approach should complete in milliseconds, not seconds. Workaround: For FLAC, I've worked around this by using libFLAC directly, which provides instant seeking via FLAC__stream​_decoder​_seek​_absolute(). libFLAC Performance: For comparison, libFLAC's FLAC__stream​_decoder​_seek​_absolute() performs the same seek + read on the same FLAC file in around 0.015, using the FLAC seek table to jump to the nearest preceding seek point, then decoding forward a small number of frames to the exact target sample.

I have an application which records video along with some custom metadata and a chapter track. The resultant video is stored in the Camera Roll. When sharing the video via the Share Sheet or AirDrop, the metadata track is stripped entirely (the chapter markers are preserved) Sharing via AirDrop with the "All Photos Data" option does include the metadata track, as does copying from the device with Image Capture but this is a bad user experience as the user must remember to explicitly select this option, and the filename is lost when sending this way. I have also tried various other approaches (such as encoding my metadata in a subtitle track, which I didn't expect to be stripped as it's an accessibility concern) but it's also removed. Essentially I am looking for a definitive list of things that are not stripped or if there's a way to encode a track in some way to indicate it should be preserved. The metadata is added via AVTimedMetadataGroup containing one AVMutableMetadataItem which has its value as a JSON string. I took a different approach with the Chapter Marker track (mainly because I did it first in a completely different way and didn't rework it when I added the other track). I post-process these after the video is recorded, and add them with addMutableTrack and then addTrackAssociation(to: chapterTrack, type: .chapterList) but I don't think that's the reason the chapter track persists where the custom metadata does not as other tests with video files from other sources containing subtitles etc also had their subtitle data stripped. tl;dr I record videos with metadata that I want to be able to share via Share Sheet and AirDrop, what am I doing wrong?

I’m implementing a custom playback pipeline using AVSampleBufferAudioRenderer together with AVSampleBufferRenderSynchronizer. hasSufficientMediaDataForReliablePlaybackStart appears to be the intended signal for determining when enough media has been queued to start playback. For local playback, this works well in practice — the property becomes true after a reasonable amount of media is enqueued. However, when the output route is AirPlay, using this property becomes difficult: AirPlay requires significantly more buffered media before the renderer reports sufficient data. The required preroll amount is much larger than for local playback. For short assets, it is possible to enqueue the entire audio track and still never observe hasSufficientMediaDataForReliablePlaybackStart == true. In that situation there is no more media data to enqueue, but the renderer still reports that playback is not ready. Given this behavior, what is the recommended way to determine playback readiness when using AVSampleBufferAudioRenderer with AirPlay?

Hello, I’m building an iOS video player using AVPlayer and a custom playback queue. I implemented remote controls using MPRemoteCommandCenter and enabled: nextTrackCommand previousTrackCommand playCommand pauseCommand I disabled: skipForwardCommand skipBackwardCommand seekForwardCommand seekBackwardCommand I also set queue metadata in MPNowPlayingInfoCenter: MPNowPlayingInfoPropertyPlaybackQueueIndex MPNowPlayingInfoPropertyPlaybackQueueCount Even with these commands enabled and the queue count greater than 1, the iOS lock screen continues to display the 10-second skip buttons instead of the previous/next track buttons. The commands themselves work correctly when triggered externally (Control Center, headphones, etc.), but the UI still shows the skip controls. Is there a way to force the lock screen UI to display previous / next track buttons for a video playlist? Or is this behavior expected when using AVPlayer with video content? Thanks.

Hello, I've been very familiar with the UVC Support in iPadOS ever since it launched in iOS 17. There are a number of people that use the software I've developed built around UVC and there are often queries about 8-Bit vs. 10-Bit. My understanding is that the newest UVC Spec is 1.5 which was standardised in 2012 and almost every UVC Capture Card runs at 8-Bit. The only 10-Bit Capture Card that is on my radar is the AJA U-Tap SDI, however it looks like this is 10-Bit up until the UVC Part where the 10-Bit Input is downsampled to 8-Bit. Though I have read in certain places that it works as a 10-Bit Capture Card on macOS but not on iPadOS. I was just wondering if 10-Bit via UVC is even possible on iPadOS? If there was indeed a true 10-Bit Source being passed into an iPad, would iPadOS allow it or would it be downsampled by AVFoundation so it can show up as a valid external video input? All USB Capture Cards that I have encountered use one of the following formats: kCVPixelFormatType_420YpCbCr8BiPlanarVideoRange kCVPixelFormatType_420YpCbCr8BiPlanarFullRange kCVPixelFormatType_32BGRA So if a UVC Device delivered a 10-Bit Format, would that be accessible by iPadOS or would it fallback to these 8-Bit Formats by default? Thanks!

In Instruments, I'm seeing "Zero Time Stamp" events in the "Audio Server" lane. What does that mean?

Hi, I’m trying to better understand how AVAssetDownloadConfiguration selects video variants when downloading HLS content for offline playback. Suppose I have an HLS master playlist (.m3u8) that contains several video variants defined with #EXT-X-STREAM-INF. For example, the master playlist may contain multiple video streams like this: Same resolution, different BANDWIDTH Or different resolutions (for example 720p, 1080p, etc.) My question is: How many video variants are actually downloaded when using AVAssetDownloadConfiguration without specifying any variantQualifiers? In other words: If the master playlist contains multiple video variants, will the download task fetch only one variant, or multiple variants? Does the behavior differ depending on whether the variants differ only by BANDWIDTH or also by RESOLUTION? What I observed in testing In my tests, I always end up with only one video variant downloaded, specifically the one with the highest BANDWIDTH parameter. In the m3u8 files I tested, all video variants had identical parameters (resolution, codec, frame rate, etc.) and differed only by the BANDWIDTH attribute in the master playlist. However, when inspecting the downloaded .movpkg, I noticed something interesting in boot.xml. It lists two video streams: one with complete="true" (the one with highest bandwidth) another with complete="no" (the one with lowest bandwidth) I actually had 3 video streams listed in m3u8, but the one with middle bandwidth wasn't listed in boot.xml file at all. There are also additional streams for audio and subtitles in boot.xml file. This made me wonder whether the system initially attempts to download another video variant (possibly a lower bitrate one), but then switches to the highest-quality variant and only completes that one. Additional question about variantQualifiers If I provide a predicate such as: NSPredicate(format: "peakBitRate > 0") which should theoretically match all variants, will the download task attempt to download all matching video variants, or will it still select only one? Summary So the main questions are: Without variantQualifiers, does AVAssetDownloadConfiguration always download a single video variant, and if so, how is it chosen? Does the behavior differ if variants have different resolutions vs only different bitrates? When a predicate matches multiple variants, can multiple video variants actually be downloaded in a single .movpkg? Why might boot.xml list multiple video streams when only one appears to be fully downloaded? Any clarification on the intended behavior would be greatly appreciated. Thanks!

Hello, I’m experiencing a severe performance degradation when running CoreML models on a live AVFoundation video feed compared to offline or synthetic inference. This happens across multiple models I've converted (including SCI, RTMPose, and RTMW) and affects multiple devices. The Environment OS: macOS 26.3, iOS 26.3, iPadOS 26.3 Hardware: Mac14,6 (M2 Max), iPad Pro 11 M1, iPhone 13 mini Compute Units: cpuAndNeuralEngine The Numbers When testing my SCI_output_image_int8.mlpackage model, the inference timings are drastically different: Synthetic/Offline Inference: ~1.34 ms Live Camera Inference: ~15.96 ms Preprocessing is completely ruled out as the bottleneck. My profiling shows total preprocessing (nearest-neighbor resize + feature provider creation) takes only ~0.4 ms in camera mode. Furthermore, no frames are being dropped. What I've Tried I am building a latency-critical app and have implemented almost every recommended optimization to try and fix this, but the camera-feed penalty remains: Matched the AVFoundation camera output format exactly to the model input (640x480 at 30/60fps). Used IOSurface-backed pixel buffers for everything (camera output, synthetic buffer, and resize buffer). Enabled outputBackings. Loaded the model once and reused it for all predictions. Configured MLModelConfiguration with reshapeFrequency = .frequent and specializationStrategy = .fastPrediction. Wrapped inference in ProcessInfo.processInfo.beginActivity(options: .latencyCritical, reason: "CoreML_Inference"). Set DispatchQueue to qos: .userInteractive. Disabled the idle timer and enabled iOS Game Mode. Exported models using coremltools 9.0 (deployment target iOS 26) with ImageType inputs/outputs and INT8 quantization. Reproduction To completely rule out UI or rendering overhead, I wrote a standalone Swift CLI script that isolates the AVFoundation and CoreML pipeline. The script clearly demonstrates the ~15ms latency on live camera frames versus the ~1ms latency on synthetic buffers. (I have attached camera_coreml_benchmark.swift and coreml model (very light low light enghancement model) to this repo on github https://github.com/pzoltowski/apple-coreml-camera-latency-repro). My Question: Is this massive overhead expected behavior for AVFoundation + Core ML on live feeds, or is this a framework/runtime bug? If expected, what is the Apple-recommended pattern to bypass this camera-only inference slowdown? One think found interesting when running in debug model was faster (not as fast as in performance benchmark but faster than 16ms. Also somehow if I did some dummy calculation on on different DispatchQueue also seems like model got slightly faster. So maybe its related to ANE Power State issues (Jitter/SoC Wake) and going to fast to sleep and taking a long time to wakeup? Doing dummy calculation in background thought is probably not a solution. Thanks in advance for any insights!

My code that streams buffers into AVAudioPlayerNode is stuttering when the buffer is finished and before the next one is played. while engine.isRunning { let framesToCopy = min(buffer.frameLength - framePosition, Self.BufferSize) let srcRaw = UnsafeRawPointer(srcPtr) let playbackBuffer = AVAudioPCMBuffer(pcmFormat: buffer.format, frameCapacity: Self.BufferSize)! let playbackPtr = playbackBuffer.floatChannelData![0] let destRaw = UnsafeMutableRawPointer(mutating: playbackPtr) memcpy(destRaw, srcRaw, Int(framesToCopy) * MemoryLayout<Float>.stride) srcPtr = srcPtr.advanced(by: Int(framesToCopy)) playbackBuffer.frameLength = framesToCopy await player.scheduleBuffer(playbackBuffer, at: nil, options: [], completionCallbackType: .dataRendered) } I've tried to schedule multiple buffers at once using a combination of both the synchronous and async versions of scheduleBuffer because I thought the delay might be but it still stutters and the data copied into the playbackBuffer matches the source buffer. I've tried all combinations of options and completionCallbackType but no luck. I've tried increasing the buffer size but that just spaces out the stutters because the buffer is larger. What am I missing about this API?

Hi everyone, We’re encountering an issue where AudioQueueNewOutput blocks indefinitely and never returns, and we’re hoping to get some insight or confirmation if this is a known behavior/regression on newer iOS versions. Issue Description When triggering audio playback, we create an output AudioQueue using AudioQueueNewOutput. On some devices, the call hangs inside AudioQueueNewOutput and never returns, with no OSStatus error and no subsequent logs. This behavior is reproducible mainly on iOS 18.3. Earlier iOS versions do not show this issue under the same code path. if (audioDes) { mAudioDes.mSampleRate = audioDes->mSampleRate; mAudioDes.mBitsPerChannel = audioDes->mBitsPerChannel; mAudioDes.mChannelsPerFrame = audioDes->mChannelsPerFrame; mAudioDes.mFormatID = audioDes->mFormatID; mAudioDes.mFormatFlags = audioDes->mFormatFlags; mAudioDes.mFramesPerPacket = audioDes->mFramesPerPacket; mAudioDes.mBytesPerFrame = audioDes->mBytesPerFrame; mAudioDes.mBytesPerPacket = audioDes->mBytesPerFrame; mAudioDes.mReserved = 0; } // Create AudioQueue for output OSStatus status = AudioQueueNewOutput( &mAudioDes, AQOutputCallback, this, NULL, NULL, 0, &audioQueue ); code-block The thread blocks inside AudioQueueNewOutput, and execution never reaches the next line. Additional Notes / Observations ASBD is confirmed to be valid Standard PCM output Sample rate, channels, bytes per frame/packet all consistent Same ASBD works correctly on earlier iOS versions AudioQueue is created on a background thread Not on the main thread Not inside the AudioQueue callback On first creation, AVAudioSession may not yet be active setCategory and setActive:YES may be called shortly before creating the AudioQueue There may be a timing window where the session is still activating Issue is reported mainly on iOS 18.3 Multiple user reports point to iOS 18.3 devices Same code path works on iOS 17.x and earlier No OSStatus error is returned — the call simply never returns. Questions Is it expected that AudioQueueNewOutput can block indefinitely while waiting for AVAudioSession / audio route / HAL readiness? Have there been any behavior changes in iOS 18.3 regarding AudioQueue creation or AudioSession synchronization? Is it unsafe to call AudioQueueNewOutput before AVAudioSession is fully active on recent iOS versions? Are there recommended patterns (or delays / callbacks) to ensure AudioQueue creation does not hang? Any insight or confirmation would be greatly appreciated. Thanks in advance!

I read somewhere that the frames are returned in decode order instead of presentation order when using AVAssetReader. The documentation seems sparse on the subject. I have so far failed to find a video file where the frames are not returned in presentation order. Can anyone confirm the frames are actually returned in decode order?

Hello, I am currently developing a live streaming application using AVPlayer to play LL-HLS (Low-Latency HLS) content. During our testing phase, we consistently encountered the following error in the logs: CoreMediaErrorDomain Code=-15517 The challenge we are facing is that the error description is quite vague. It only provides cryptic messages such as "Key not found" or "No value information," which makes it extremely difficult to identify the root cause or perform a deep-dive analysis. I have searched through the official Apple Developer documentation and technical notes, but I couldn’t find any specific reference to what Code -15517 signifies in the context of LL-HLS or CoreMedia. Regarding this issue, I have the following questions: What is the specific meaning of this error code (-15517)? Does it relate to missing tags in the HLS manifest, or is it an internal state issue within the AVPlayer stack? Specifically, I would like to know if this is a critical error that disrupts playback, or if it is just a warning that can be safely ignored. Is there any additional logging or debugging tool you would recommend to further investigate "Key not found" issues in LL-HLS? Any insights or guidance from the community or Apple engineers would be greatly appreciated. Thank you in advance for your help.

I just bought a monitor S2725QC from Dell Technologies and isn't fully-integrated with MacOS even though it says on the website it is compatible with MacOS. https://www.dell.com/en-us/shop/all-monitors/sac/monitors/all-monitors/macos-compatible?appliedRefinements=51765 The screen brightness and volume control buttons don't work with the monitors (I have two). What can I do in terms of writing code with Dell Monitor SDK and MacOS Frameworks/Technologies?

Hello everyone, I’m looking for more detailed information regarding UVC (USB Video Class) over MFi within the Apple ecosystem and would appreciate some clarification. I’m interested in developing (or interfacing with) an accessory that transmits video over USB using the UVC standard, and I’d like to better understand how this works within the MFi (Made for iPhone) program. Here are my main questions: 1. Do iOS devices provide native support for UVC over USB-C or Lightning within the MFi framework? 2. Are there any specific firmware or authentication requirements when the accessory is MFi-certified? 3. Does UVC support depend solely on the hardware interface (USB-C vs Lightning), or are there additional software-level requirements? 4. Is there any official documentation outlining the recommended flow for implementing UVC-based video capture accessories on iOS? From what I understand, USB-C iPads appear to offer more direct support for standard UVC devices, but it’s not entirely clear how this integrates with the MFi ecosystem with iOS, especially for commercial product development. If anyone has gone through this process or can point me to relevant technical documentation, I would greatly appreciate the guidance. Thank you!

I want to: Run ARKit on the main rear camera, and while it's running shoot high resolution pictures on the wide camera, without disturbing the AR tracking. Is this possible?

I'm relatively new to Swift development (and native iOS development for that matter) I've got an iOS app that uses the iPhone / iPad built in cameras, and am looking to make this more compatible with macOS. Using the normal AVCaptureDevice.DiscoverySession I seem to get the iPhone Continuity Camera and the in-built MacBook Pro camera but I don't see other input devices that I see in QuickTime Player (for example) such as connected external cameras or Virtual Inputs provided by NDI Virtual Input and OBS. Is there a way to see access these without a specific Mac build (as the rest of the functionality works great, and I'd rather not diverge the codebase too much as it's easier to update one app than two!