Capturing more than one display is no longer working with macOS Sequoia. We have a product that allows users to capture up to 2 displays/screens. Our application is using gstreamer which in turn is based on AVFoundation. I found a quick way to replicate the issue by just running 2 captures from separate terminals. Assuming display 1 has device index 0, and display 2 has device index 1, here are the steps: install gstreamer with brew install gstreamer Then open 2 terminal windows and launch the following processes: terminal 1 (device-index:0): gst-launch-1.0 avfvideosrc -e device-index=0 capture-screen=true ! queue ! videoscale ! video/x-raw,width=640,height=360 ! videoconvert ! osxvideosink terminal 2 (device-index:1): gst-launch-1.0 avfvideosrc -e device-index=1 capture-screen=true ! queue ! videoscale ! video/x-raw,width=640,height=360 ! videoconvert ! osxvideosink The first process that is launched will show the screen, the second process launched will not. Testing this on macOS Ventura and Sonoma works as expected, showing both screens. I submitted the same issue on Feedback Assistant: FB15900976

Is it possible to stream video from a UVC (USB Video Class) camera on an iPhone 15? If so, are there any specific hardware or software requirements to enable this functionality?

I am trying to achieve an animated gradient effect that changes values over time based on the current seconds. I am also using AVPlayer and AVMutableVideoComposition along with custom instruction and class to generate the effect. I didn't want to load any video file, but rather generate a custom video with my own set of instructions. I used Metal Compute shaders to generate the effects and make the video to be 20 seconds. However, when I run the code, I get a frozen player with the gradient applied, but when I try to play the video, I get this warning in the console :- Visual isTranslatable: NO; reason: observation failure: noObservations Here is the screenshot :- My entire code :- import AVFoundation import Metal class GradientVideoCompositorTest: NSObject, AVVideoCompositing { var sourcePixelBufferAttributes: [String: Any]? = [ kCVPixelBufferPixelFormatTypeKey as String: kCVPixelFormatType_32BGRA ] var requiredPixelBufferAttributesForRenderContext: [String: Any] = [ kCVPixelBufferPixelFormatTypeKey as String: kCVPixelFormatType_32BGRA ] private var renderContext: AVVideoCompositionRenderContext? private var metalDevice: MTLDevice! private var metalCommandQueue: MTLCommandQueue! private var metalLibrary: MTLLibrary! private var metalPipeline: MTLComputePipelineState! override init() { super.init() setupMetal() } func setupMetal() { guard let device = MTLCreateSystemDefaultDevice(), let queue = device.makeCommandQueue(), let library = try? device.makeDefaultLibrary(), let function = library.makeFunction(name: "gradientShader") else { fatalError("Metal setup failed") } self.metalDevice = device self.metalCommandQueue = queue self.metalLibrary = library self.metalPipeline = try? device.makeComputePipelineState(function: function) } func renderContextChanged(_ newRenderContext: AVVideoCompositionRenderContext) { renderContext = newRenderContext } func startRequest(_ request: AVAsynchronousVideoCompositionRequest) { guard let outputPixelBuffer = renderContext?.newPixelBuffer(), let metalTexture = createMetalTexture(from: outputPixelBuffer) else { request.finish(with: NSError(domain: "com.example.gradient", code: -1, userInfo: nil)) return } var time = Float(request.compositionTime.seconds) renderGradient(to: metalTexture, time: time) request.finish(withComposedVideoFrame: outputPixelBuffer) } private func createMetalTexture(from pixelBuffer: CVPixelBuffer) -> MTLTexture? { var texture: MTLTexture? let width = CVPixelBufferGetWidth(pixelBuffer) let height = CVPixelBufferGetHeight(pixelBuffer) let textureDescriptor = MTLTextureDescriptor.texture2DDescriptor( pixelFormat: .bgra8Unorm, width: width, height: height, mipmapped: false ) textureDescriptor.usage = [.shaderWrite, .shaderRead] CVPixelBufferLockBaseAddress(pixelBuffer, .readOnly) if let textureCache = createTextureCache(), let cvTexture = createCVMetalTexture(from: pixelBuffer, cache: textureCache) { texture = CVMetalTextureGetTexture(cvTexture) } CVPixelBufferUnlockBaseAddress(pixelBuffer, .readOnly) return texture } private func renderGradient(to texture: MTLTexture, time: Float) { guard let commandBuffer = metalCommandQueue.makeCommandBuffer(), let commandEncoder = commandBuffer.makeComputeCommandEncoder() else { return } commandEncoder.setComputePipelineState(metalPipeline) commandEncoder.setTexture(texture, index: 0) var mutableTime = time commandEncoder.setBytes(&mutableTime, length: MemoryLayout<Float>.size, index: 0) let threadsPerGroup = MTLSize(width: 16, height: 16, depth: 1) let threadGroups = MTLSize( width: (texture.width + 15) / 16, height: (texture.height + 15) / 16, depth: 1 ) commandEncoder.dispatchThreadgroups(threadGroups, threadsPerThreadgroup: threadsPerGroup) commandEncoder.endEncoding() commandBuffer.commit() } private func createTextureCache() -> CVMetalTextureCache? { var cache: CVMetalTextureCache? CVMetalTextureCacheCreate(kCFAllocatorDefault, nil, metalDevice, nil, &cache) return cache } private func createCVMetalTexture(from pixelBuffer: CVPixelBuffer, cache: CVMetalTextureCache) -> CVMetalTexture? { var cvTexture: CVMetalTexture? let width = CVPixelBufferGetWidth(pixelBuffer) let height = CVPixelBufferGetHeight(pixelBuffer) CVMetalTextureCacheCreateTextureFromImage( kCFAllocatorDefault, cache, pixelBuffer, nil, .bgra8Unorm, width, height, 0, &cvTexture ) return cvTexture } } class GradientCompositionInstructionTest: NSObject, AVVideoCompositionInstructionProtocol { var timeRange: CMTimeRange var enablePostProcessing: Bool = true var containsTweening: Bool = true var requiredSourceTrackIDs: [NSValue]? = nil var passthroughTrackID: CMPersistentTrackID = kCMPersistentTrackID_Invalid init(timeRange: CMTimeRange) { self.timeRange = timeRange } } func createGradientVideoComposition(duration: CMTime, size: CGSize) -> AVMutableVideoComposition { let composition = AVMutableComposition() let instruction = GradientCompositionInstructionTest(timeRange: CMTimeRange(start: .zero, duration: duration)) let videoComposition = AVMutableVideoComposition() videoComposition.customVideoCompositorClass = GradientVideoCompositorTest.self videoComposition.renderSize = size videoComposition.frameDuration = CMTime(value: 1, timescale: 30) // 30 FPS videoComposition.instructions = [instruction] return videoComposition } #include <metal_stdlib> using namespace metal; kernel void gradientShader(texture2d<float, access::write> output [[texture(0)]], constant float &time [[buffer(0)]], uint2 id [[thread_position_in_grid]]) { float2 uv = float2(id) / float2(output.get_width(), output.get_height()); // Animated colors based on time float3 color1 = float3(sin(time) * 0.8 + 0.1, 0.6, 1.0); float3 color2 = float3(0.12, 0.99, cos(time) * 0.9 + 0.3); // Linear interpolation for gradient float3 gradientColor = mix(color1, color2, uv.y); output.write(float4(gradientColor, 1.0), id); }

The app registers a periodic time observer to the AVPlayer when the playback starts and it works fine. When switching to AirPlay during playback, the periodic time observation continues working as expected. However, when switching back to local playback, the periodic time observer does not fire anymore until a seek is performed. The app removes the periodic time observer only when the playback stops. I can see that when switching back to local playback, the timeControlStatus successively changes to .waitingToPlayAtSpecifiedRate (reason: .evaluatingBufferingRate) then to .waitingToPlayAtSpecifiedRate (reason: .toMinimizeStalls) and finally to .playing But the time observation does not work anymore. Also, the issue is systematic with Live and VOD streams providing a program date (with HLS property #EXT-X-PROGRAM-DATE-TIME), with or without any DRM, and is never reproduced with other VOD streams.

My current app implements a custom video player, based on a AVSampleBufferRenderSynchronizer synchronising two renderers: an AVSampleBufferDisplayLayer receiving decoded CVPixelBuffer-based video CMSampleBuffers, and an AVSampleBufferAudioRenderer receiving decoded lpcm-based audio CMSampleBuffers. The AVSampleBufferRenderSynchronizer is started when the first image (in presentation order) is decoded and enqueued, using avSynchronizer.setRate(_ rate: Float, time: CMTime), with rate = 1 and time the presentation timestamp of the first decoded image. Presentation timestamps of video and audio sample buffers are consistent, and on most streams, the audio and video are correctly synchronized. However on some network streams, on iOS, the audio and video aren't synchronized, with a time difference that seems to increase with time. On the other hand, with the same player code and network streams on macOS, the synchronization always works fine. This reminds me of something I've read, about cases where an AVSampleBufferRenderSynchronizer could not synchronize audio and video, causing them to run with independent and potentially drifting clocks, but I cannot find it again. So, any help / hints on this sync problem will be greatly appreciated! :)

Hello! I have been following the UsingAVFoundationToPlayAndPersistHTTPLiveStreams sample code in order to test persisting streams to disk. In addition to support for m3u8, I have noticed in testing that this also seems to work for MP3 Audio, simply by changing the plist entries to point to remote URLs with audio/mpeg content. Is this expected, or are there caveats that I should be aware of? Thanks you!

Environment→ ・Device: iPad 10th generation ・OS：**iOS18.3.2 I'm using AVAudioSession to record sound in my application. But I recently came to realize that when the app starts a recording session on a tablet, OS automatically sets the tablet volume to 50% and when after recording ends, it doesn't change back to the previous volume level before starting the recording. So I would like to know whether this is an OS default behavior or a bug? If it's a default behavior, I much appreciate if I can get a link to the documentation.

We are currently working on a CarPlay navigation app and so far everything is working well except for speaking turn notifications. Our TTS implementation works fine on the phone and works fine on CarPlay if the voice is spoken over the speaker in the car. If users connect a BT headset to the car and listen through that headset, then the voice commands are chopped up / stutter. Why would users use BT headset? Well, we are working on a motorcycle app, and there are no speakers usually on a motorcycle. It sounds like the BT channel is opened and closed repeatedly for every character / word spoken. This happens on different CarPlay devices and different Bluetooth headsets, we have reports from multiple users that they find this behavior annoying and that other apps work fine. Is this a known issue? Are there possible workaround?

I’m building a professional camera app where users can customize the video recording format and color grading. In the func captureOutput(_ output: AVCaptureOutput, didOutput sampleBuffer: CMSampleBuffer, from connection: AVCaptureConnection) method, I handle video frames and use Metal for real-time color grading. This works well when device.activeColorSpace is sRGB or P3, and the results are great. However, when the color space is HLG_BT2020 or appleLog, the MTKTextureLoader.newTexture(cgImage: cgImage, options: options) method throws an error. After researching, I found that the video frame in these color spaces has a bit-per-channel (bpc) greater than 8 after being converted to CGImage, causing the texture creation to fail. I tried converting the CGImage to a lower bpc to successfully create the texture, but the final output image is garbled and not as expected. Is there a solution to this issue?

According to the documentation (https://developer.apple.com/documentation/avfoundation/avplayeritem/externalmetadata), AVPlayerItem should have an externalMetadata property. However it does not appear to be visible to my app. When I try, I get: Value of type 'AVPlayerItem' has no member 'externalMetadata' Documentation states iOS 12.2+; I am building with a minimum deployment target of iOS 18. Code snippet: import Foundation import AVFoundation /// ... in function ... // create metadata as described in https://developer.apple.com/videos/play/wwdc2022/110338 var title = AVMutableMetadataItem() title.identifier = .commonIdentifierAlbumName title.value = "My Title" as NSString? title.extendedLanguageTag = "und" var playerItem = await AVPlayerItem(asset: composition) playerItem.externalMetadata = [ title ]

I have a memory leak, when using AVAudioPlayer. I managed to narrow down the issue into a very simple app, which code I paste in at the end. The memory leak start immediately when I start playing sound, but only in the emylator. On the real iPhone there is no memory leak. The memory leak on the Simulator looks like this: import SwiftUI import AVFoundation struct ContentView_Audio: View { var sound: AVAudioPlayer? init() { guard let path = Bundle.main.path(forResource: "cd201", ofType: "mp3") else { return } let url = URL(fileURLWithPath: path) do { try AVAudioSession.sharedInstance().setCategory(.playback, mode: .default, options: [.mixWithOthers]) } catch { return } do { try AVAudioSession.sharedInstance().setActive(true) } catch { return } do { sound = try AVAudioPlayer(contentsOf: url) } catch { return } } var body: some View { HStack { Button { playSound() } label: { ZStack { Circle() .fill(.mint.opacity(0.3)) .frame(width: 44, height: 44) .shadow(radius: 8) Image(systemName: "play.fill") .resizable() .frame(width: 20, height: 20) } } .padding() Button { stopSound() } label: { ZStack { Circle() .fill(.mint.opacity(0.3)) .frame(width: 44, height: 44) .shadow(radius: 8) Image(systemName: "stop.fill") .resizable() .frame(width: 20, height: 20) } } .padding() } } private func playSound() { guard sound != nil else { return } sound?.volume = 1 // sound?.numberOfLoops = -1 sound?.play() } func stopSound() { sound?.stop() } }

I'm able to get text to speech to audio file using the following code for iOS 12 iPhone 8 to create a car file: audioFile = try AVAudioFile( forWriting: saveToURL, settings: pcmBuffer.format.settings, commonFormat: .pcmFormatInt16, interleaved: false) where pcmBuffer.format.settings is: [AVAudioFileTypeKey: kAudioFileMP3Type, AVSampleRateKey: 48000, AVEncoderBitRateKey: 128000, AVNumberOfChannelsKey: 2, AVFormatIDKey: kAudioFormatLinearPCM] However, this code does not work when I run the app in iOS 18 on iPhone 13 Pro Max. The audio file is created, but it doesn't sound right. It has a lot of static and it seems the speech is very low pitch. Can anyone give me a hint or an answer?

I'm encountering errors while using AVAudioEngine with voice processing enabled (setVoiceProcessingEnabled(true)) in scenarios where the input and output audio devices are not the same. This issue arises specifically with mismatched devices, preventing the application from functioning as expected. Works: Paired devices (e.g., MacBook Pro mic → MacBook Pro speakers) Fails: Mismatched devices (e.g., AirPods mic → MacBook Pro speakers) When using paired input and output devices: The setup works as expected. Example: MacBook Pro microphone → MacBook Pro speakers. When using mismatched devices: AVAudioEngine setup fails during aggregate device construction. Example: AirPods microphone → MacBook Pro speakers. Error logs indicate a channel count mismatch. Here are the partial logs. Due to the content limit, I cannot post the entire logs. AUVPAggregate.cpp:1000 client-side input and output formats do not match (err=-10875) AUVPAggregate.cpp:1036 err=-10875 AVAEInternal.h:109 [AVAudioEngineGraph.mm:1344:Initialize: (err = PerformCommand(*outputNode, kAUInitialize, NULL, 0)): error -10875 AggregateDevice.mm:329 Failed expectation of constructed aggregate (312): mInput.streamChannelCounts == inputStreamChannelCounts AggregateDevice.mm:331 Failed expectation of constructed aggregate (312): mInput.totalChannelCount == std::accumulate(inputStreamChannelCounts.begin(), inputStreamChannelCounts.end(), 0U) AggregateDevice.mm:182 error fetching default pair AggregateDevice.mm:329 Failed expectation of constructed aggregate (336): mInput.streamChannelCounts == inputStreamChannelCounts AggregateDevice.mm:331 Failed expectation of constructed aggregate (336): mInput.totalChannelCount == std::accumulate(inputStreamChannelCounts.begin(), inputStreamChannelCounts.end(), 0U) AUHAL.cpp:1782 ca_verify_noerr: [AudioDeviceSetProperty(mDeviceID, NULL, 0, isInput, kAudioDevicePropertyIOProcStreamUsage, theSize, theStreamUsage), 560227702] AudioHardware-mac-imp.cpp:3484 AudioDeviceSetProperty: no device with given ID AUHAL.cpp:1782 ca_verify_noerr: [AudioDeviceSetProperty(mDeviceID, NULL, 0, isInput, kAudioDevicePropertyIOProcStreamUsage, theSize, theStreamUsage), 560227702] AggregateDevice.mm:182 error fetching default pair AggregateDevice.mm:329 Failed expectation of constructed aggregate (348): mInput.streamChannelCounts == inputStreamChannelCounts AggregateDevice.mm:331 Failed expectation of constructed aggregate (348): mInput.totalChannelCount == std::accumulate(inputStreamChannelCounts.begin(), inputStreamChannelCounts.end(), 0U) Is it possible to use voice processing with different input/output devices? If yes, are there any specific configurations required to handle mismatched devices? How can we resolve channel count mismatch errors during aggregate device construction? Are there settings or API adjustments to enforce compatibility between input/output devices? Are there any workarounds or alternative approaches to achieve voice processing functionality with mismatched devices? For instance, can we force an intermediate channel configuration or downmix input/output formats?

Hi all, with my app ScreenFloat, you can record your screen, along with system- and microphone audio. Those two audio feeds are recorded into separate audio tracks in order to individually remove or edit them later on. Now, these recordings you create with ScreenFloat can be drag-and-dropped to other apps instantly. So far, so good, but some apps, like Slack, or VLC, or even websites like YouTube, do not play back multiple audio tracks, just one. So what I'm trying to do is, on dragging the video recording file out of ScreenFloat, instantly baking together the two individual audio tracks into one, and offering that new file as the drag and drop file, so that all audio is played in the target app. But it's slow. I mean, it's actually quite fast, but for drag and drop, it's slow. My approach is this: "Bake together" the two audio tracks into a one-track m4a audio file using AVMutableAudioMix and AVAssetExportSession Take the video track, add the new audio file as an audio track to it, and render that out using AVAssetExportSession For a quick benchmark, a 3'40'' movie, step 1 takes ~1.7 seconds, and step two adds another ~1.5 seconds, so we're at ~3.2 seconds. That's an eternity for a drag and drop, where the user might cancel if there's no immediate feedback. I could also do it in one step, but then I couldn't use the AV*Passthrough preset, and that makes it take around 32 seconds then, because I assume it touches the video data (which is unnecessary in this case, so I think the two-step approach here is the fastest). So, my question is, is there a faster way? The best idea I can come up with right now is, when initially recording the screen with system- and microphone audio as separate tracks, to also record both of them into a third, muted, "hidden" track I could use later on, basically eliminating the need for step one and just ripping the two single audio tracks out of the movie and only have the video and the "hidden" track (then unmuted), but I'd still have a ~1.5 second delay there. Also, there's the processing and data overhead (basically doubling the movie's audio data). All this would be great for an export operation (where one expects it to take a little time), but for a drag-and-drop operation, it's not ideal. I've discarded the idea of doing a promise file drag, because many apps do not accept those, and I want to keep wide compatibility with all sorts of apps. I'd appreciate any ideas or pointers. Thank you kindly, Matthias

I am trying to stream audio from local filesystem. For that, I am trying to use an AVAssetResourceLoaderDelegate for an AVURLAsset. However, Content-Length is not known at the start. To overcome this, I tried several methods: Set content length as nil, in the AVAssetResourceLoadingContentInformationRequest Set content length to -1, in the ContentInformationRequest Both of these cause the AVPlayerItem to fail with an error. I also tried setting Content-Length as INT_MAX, and setting a renewalDate = Date(timeIntervalSinceNow: 5). However, that seems to be buggy. Even after updating the Content-Length to the correct value (e.g. X bytes) and finishing that loading request, the resource loader keeps getting requests with requestedOffset = X with dataRequest.requestsAllDataToEndOfResource = true. These requests keep coming indefinitely, and as a result it seems that the next item in the queue does not get played. Also, .AVPlayerItemDidPlayToEndTime notification does not get called. I wanted to check if this is an expected behavior or is there a bug in this implementation. Also, what is the recommended way to stream audio of unknown initial length from local file system? Thanks!

FairPlay-Protected HLS Files Not Transferred via Quick Start I have an iOS app that downloads HLS files, which are protected by FairPlay. These files are stored locally, and their locations are managed using Core Data. When playing these tracks, I use AVURLAsset to access the stored file paths. Recently, a client upgraded to a new iPhone and used Quick Start to transfer data from his old device. While all other app data was successfully transferred, including Core Data records and UserDefaults, the actual HLS files were missing. As a result, the app retained metadata about the downloaded content, but the files themselves were gone, causing playback failures. Does Quick Start exclude certain types of locally stored files, especially DRM-protected HLS downloads, or is the issue related to how FairPlay-protected content is handled during the transfer of locally stored files?

I noticed that AVSampleBufferDisplayLayerContentLayer is not released when the AVSampleBufferDisplayLayer is removed and released. It is possible to reproduce the issue with the simple code: import AVFoundation import UIKit class ViewController: UIViewController { var displayBufferLayer: AVSampleBufferDisplayLayer? override func viewDidLoad() { super.viewDidLoad() let displayBufferLayer = AVSampleBufferDisplayLayer() displayBufferLayer.videoGravity = .resizeAspectFill displayBufferLayer.frame = view.bounds view.layer.insertSublayer(displayBufferLayer, at: 0) self.displayBufferLayer = displayBufferLayer DispatchQueue.main.asyncAfter(deadline: .now() + 1) { self.displayBufferLayer?.flush() self.displayBufferLayer?.removeFromSuperlayer() self.displayBufferLayer = nil } } } In my real project I have mutliple AVSampleBufferDisplayLayer created and removed in different view controllers, this is problematic because the amount of leaked AVSampleBufferDisplayLayerContentLayer keeps increasing. I wonder that maybe I should use a pool of AVSampleBufferDisplayLayer and reuse them, however I'm slightly afraid that this can also lead to strange bugs. Edit: It doesn't cause leaks on iOS 18 device but leaks on iPad Pro, iOS 17.5.1

Hi, I am looking for a good way to play sounds at a high frequency. At the moment I am using the AVAudioEngine, and create a couple AVAudioPlayerNode and for each sound I need to play I create a AVAudioPCMBuffer. When the app needs to play a sound, I get the correct AVAudioPCMBuffer for the sound and use the first available AVAudioPlayerNode and feed it to the buffer. The timing for a metronome app has to be very precise because if it's of by about 16ms the user can hear that it is not playing had the right interval. For low speeds this is working without any problems, but at high speeds it is getting worse. Maybe anyone has an idea on how I can improve my method. Its a Plugin for Flutter. import AVFoundation class FastSoundPlayer { private var audioPlayers: [SoundPlayer?] = [] private var sounds: [String: Sound] = [:] private var engine = AVAudioEngine() let session = AVAudioSession.sharedInstance() init() { do { try session.setCategory(AVAudioSession.Category.playback, mode: AVAudioSession.Mode.default, options: [AVAudioSession.CategoryOptions.mixWithOthers]) try session.setActive(true) createSoundPlayers(count: 20) try engine.start() } catch { print("Error starting audio engine: \(error.localizedDescription)") } } // Selector method to handle applicationDidBecomeActiveNotification func applicationDidBecomeActive() { // Reinitialize AVAudioEngine and reattach all nodes do { engine.reset() objc_sync_enter(audioPlayers) audioPlayers.removeAll() createSoundPlayers(count: 20) objc_sync_exit(audioPlayers) try engine.start() } catch { print("Error starting audio engine: \(error.localizedDescription)") } } func createSoundPlayers(count: Int) { for _ in 0..<count { let player = SoundPlayer() engine.attach(player.player) engine.connect(player.player, to: engine.mainMixerNode, format: nil) audioPlayers.append(player) } } func load(sound: Data, name: String) { let sound = Sound(soundData: sound) sounds[name] = sound } func play(name: String) { if !engine.isRunning { applicationDidBecomeActive() } guard let sound = sounds[name] else { print("Sound not found") return } if let player = getAvailablePlayer() { player.play(sound: sound) } } func getAvailablePlayer() -> SoundPlayer? { for player in audioPlayers { if !player!.isPlaying { return player } } return nil } } class SoundPlayer { let player = AVAudioPlayerNode() var isPlaying = false init() { player.volume = 1.0 } func play(sound: Sound) { player.scheduleBuffer(sound.sound!, at: nil, options: .interrupts, completionCallbackType: .dataPlayedBack) { _ in self.complete() } if (player.engine != nil && player.engine!.isRunning) { player.play() isPlaying = true } } func complete() { isPlaying = false } } class Sound { var sound: AVAudioPCMBuffer? init(soundData: Data) { do { let temporaryURL = FileManager.default.temporaryDirectory.appendingPathComponent("tempSound.wav") try soundData.write(to: temporaryURL) // Create AVAudioFile from the temporary file URL let audioFile = try AVAudioFile(forReading: temporaryURL) // Define the format for the PCM buffer (44100Hz, stereo) let format = AVAudioFormat(commonFormat: .pcmFormatInt16, sampleRate: 44100, channels: 2, interleaved: false) // Create AVAudioPCMBuffer guard let pcmBuffer = AVAudioPCMBuffer(pcmFormat: format!, frameCapacity: AVAudioFrameCount(audioFile.length)) else { // Failed to create PCM buffer self.sound = nil return } // Read audio file into PCM buffer try audioFile.read(into: pcmBuffer) // Assign the created AVAudioPCMBuffer to the sound property self.sound = pcmBuffer } catch { print("Error loading sound file: \(error.localizedDescription)") self.sound = nil } } } Thanks!

In the past, when using Lightning, many external devices had to go through MFi certification. However, since the iPhone 15 switched from Lightning to USB-C, is MFi certification still required? Our company has developed several UVC devices, and we have confirmed that iPads can read frames from external cameras through the external device type in AVFoundation. However, this is not supported on iPhones. We are currently exploring feasible ways to enable UVC device support on iPhones. Is MFi certification the only option? If so, is the MFi certification process for USB-C the same as it was for Lightning? Does it still require purchasing an MFi chip and manufacturing specially designed USB-C cables?

I'm working on an application that uses the iPhone camera for scientific purposes - and, as a result would like to receive video in as unprocessed format as possible. In particular, I'm interested in getting pixel buffers that contain pretty much the bayer data as the sensor sees it - with the minimum processing of color possible. Currently we configure the AVCaptureDevice to fix the focus and exposure, use a low ISO with no gain and set the white balance gains to 1. AVCaptureVideoDataOutput is using 32BGRA. What I'd like to do is remove any additional color and brightness processing such that the data is effectively processed with a linear transfer function (i.e. gamma function is 1). I thought that this might be down to using the AVCaptureDevice activeColorSpace - we currently use P3_D65 for this. But there only seems to be a few choices (e.g. sRGB, HLG_BT2020) all of which I think affect the gamma. So: is it possible to control or specify the gamma / transfer function when using CaptureVideoDelegate? if not, does one of the color space settings have a defined gamma function that I can effectively reverse it from the pixel data without losing too much information? or is there a better way to capture video-ish speed images (15-30fps) from the camera sensor that skips processing like this? Many thanks for any suggestions.