I am doing something similar to this post Within an AVCaptureDataOutputSynchronizerDelegate method, I create a pixelBuffer using CVPixelBufferCreate with the following attributes: kCVPixelBufferIOSurfacePropertiesKey as String: true, kCVPixelBufferIOSurfaceOpenGLESTextureCompatibilityKey as String: true When I copy the data from the vImagePixelBuffer "rotatedImageBuffer", I get the following error: Thread 10: EXC_BAD_ACCESS (code=1, address=0x14caa8000) I get the same error with memcpy and data.copyBytes (not running them at the same time obviously). If I use CVPixelBufferCreateWithBytes, I do not get this error. However, CVPixelBufferCreateWithBytes does not let you include attributes (see linked post above). I am using vImage because I need the original CVPixelBuffer from the camera output and a rotated version with a different color scheme. // Copy to pixel buffer let attributes: NSDictionary = [ true : kCVPixelBufferIOSurfacePropertiesKey, true : kCVPixelBufferIOSurfaceOpenGLESTextureCompatibilityKey, ] var colorBuffer: CVPixelBuffer? let status = CVPixelBufferCreate(kCFAllocatorDefault, Int(rotatedImageBuffer.width), Int(rotatedImageBuffer.height), kCVPixelFormatType_32BGRA, attributes, &colorBuffer) //let status = CVPixelBufferCreateWithBytes(kCFAllocatorDefault, Int(rotatedImageBuffer.width), Int(rotatedImageBuffer.height), kCVPixelFormatType_32BGRA, rotatedImageBuffer.data, rotatedImageBuffer.rowBytes, nil, nil, attributes as CFDictionary, &colorBuffer) // does NOT produce error, but also does not have attributes guard status == kCVReturnSuccess, let colorBuffer = colorBuffer else { print("Failed to create buffer") return } let lockFlags = CVPixelBufferLockFlags(rawValue: 0) guard kCVReturnSuccess == CVPixelBufferLockBaseAddress(colorBuffer, lockFlags) else { print("Failed to lock base address") return } let colorBufferMemory = CVPixelBufferGetBaseAddress(colorBuffer)! let data = Data(bytes: rotatedImageBuffer.data, count: rotatedImageBuffer.rowBytes * Int(rotatedImageBuffer.height)) data.copyBytes(to: colorBufferMemory.assumingMemoryBound(to: UInt8.self), count: data.count) // Fails here //memcpy(colorBufferMemory, rotatedImageBuffer.data, rotatedImageBuffer.rowBytes * Int(rotatedImageBuffer.height)) // Also produces the same error CVPixelBufferUnlockBaseAddress(colorBuffer, lockFlags)

Short summary When setting exposureMode to .locked or .custom the brightness of a video stream still changes depending on the composition and contrast of the visible scene. These changes seem to come from contrast enhancements or dynamic range optimizations and totally break any analysis of the image that requires to assess absolute luminance. While exposure lock seems to indeed lock the physical exposure parameters of the camera (shutter speed and ISO), I cannot find any way to control these "soft" modifiers. Details Background I am the developer of the app "phyphox", an educational app that makes the phone's sensors accessible to students as measurement tools in science experiments. Currently I am working on implementing photometric measurements through the camera and one very important aspect of it is luminance measurements. This is particularly relevant since the light sensor of the phone has no publicly accessible API and the camera could to some extend make experiments available to Apple users that are otherwise only possible on Android devices. Implementation The app uses AVFoundation and explicitly picks individual cameras since camera groups do not support custom exposure settings. This means that it handles camera switching during zoom by itself and even implements its own auto exposure routines to optimize for the use in experiments. Therefore it always stays in custom exposure mode. The app uses YUV420 color space and the individual frames are analyzed in Metal using compute shaders. However, the effects discussed here still occur if I remove all code to control the camera and replace it with a simple sequence of setting the exposure mode to custom, setting custom exposure values, setting a fixed white balance and then setting the exposure mode to locked as suggested on stackoverflow. This neither helps on an iPhone 14 Pro nor on an iPhone 8 despite a report on the developer forums that it would resolve the issue for older devices. The app is open source, so the code can be seen in our current development branch (without the changes for the tests here, though) on github. The videos below use the implementation with the suggestion from stackoverflow, but they can be reproduced in the same way with "professional" camera apps that promise manual control over the camera (like the Blackmagic cam to quote a reputable company) as well as the stock camera app after pressing and holding on the preview to enable AE/AF lock. Demonstration These examples were captured on an iPhone 14 Pro. The central part of the image (highlighted by the app using metal shaders after capture) should not change with fixed exposure settings, but significant changes are noticable if there are changes at the edge of the frame when I move a black piece of cardboard in from above: https://share.icloud.com/photos/0b1f_3IB6yAQG-qSH27pm6oDQ The graph above the camera preview is the average luminance (gamma corrected and weighted based on sRGB) across the highlighted central area and as mentioned before it should not change because of something happening at the side of the frame (worst case it should get a bit darker because of the cardboard's shadow). In my opinion, the iPhone changes its mind on the ideal contrast as soon as it has a different exposure histogram because of the dark image part from the cardboard, but that's just me guessing. For completeness here is the same effect in the stock camera app with AE/AF lock enabled: https://share.icloud.com/photos/0cd7QM8ucBZKwPwE9mybnEowg Here you can also see that the iPhone "ramps" the changes. The brightness of the gray area does not change immediately but transitions smoothly, so this is clearly deliberate postprocessing. So... Any suggestion on how to prevent this behavior would be highly appreciated.

I am working on a project for macOS where I am taking an AVCaptureSession's CVPixelBuffer and I need to convert it into a MTLTexture for rendering. On macOS the pixel format is 2vuy, there does not seem to be a clear format conversion while converting to a metal texture. I have been able to convert it to a texture but the color space seems to be off as it is rendering distorted colors with a double image. I believe 2vuy is a single pane color space and I have tried to account for that, but I am unaware of what is off. I have attached The CVPixelBuffer and The distorted MTLTexture along with a laundry list of errors. On iOS my conversions are fine, it is only the macOS 2vuy pixel format that seems to have issues. My code for the conversion is also attached. If there are any suggestions or guidance on how to properly convert a 2vuy CVPixelBuffer to a MTLTexture I would greatly appreciate it. Many Thanks Conversion_Logs.txt ConversionCode.swift

I am working on a project for macOS where I am taking an AVCaptureSession's CVPixelBuffer and I need to convert it into a MTLTexture for rendering. On macOS the pixel format is 2vuy, there does not seem to be a clear format conversion while converting to a metal texture. I have been able to convert it to a texture but the color space seems to be off as it is rendering distorted colors with a double image. I believe 2vuy is a single pane color space and I have tried to account for that, but I am unaware of what is off. I have attached The CVPixelBuffer and The distorted MTLTexture along with a laundry list of errors. On iOS my conversions are fine, it is only the macOS 2vuy pixel format that seems to have issues. My code for the conversion is also attached. If there are any suggestions or guidance on how to properly convert a 2vuy CVPixelBuffer to a MTLTexture I would greatly appreciate it. Many Thanks Conversion_Logs.txt ConversionCode.swift

Hi, I have a problem when I want to attach my grayscale depth map image into the real image. The produced depth map doesn't have the cameraCalibration value which should responsible to align the depth data to the image. How do I align the depth map? I saw an article about it but it is not really detailed so I might be missing some process. I tried to: convert my depth map into pixel buffer create image destination ref and add the image there. add the auxData (depth map dict) This is the output: There is some black space there and my RGB image colour changes

Hello Apple Community, We are working on a real-time streaming feature where we receive chunks of raw MP4 data through a custom protocol and store them in a buffer (array). Our goal is to use these data chunks to play a continuous video stream in AVPlayer. What We've Tried: Custom URL Scheme with AVAssetResourceLoaderDelegate: We implemented a custom URL scheme (customscheme://) to serve the buffered data using AVAssetResourceLoaderDelegate. The method shouldWaitForLoadingOfRequestedResource is called only during the initial allocation. It doesn't get triggered when new chunks are appended to the buffer. Despite appending new data to the buffer, AVPlayer doesn’t request further chunks from the delegate. What We Need: We are looking for a solution where: The player continuously fetches data from the buffer as new chunks are added. The playback remains smooth and uninterrupted, even with real-time data being appended. Ideally, this solution works with AVPlayer while adhering to HLS-like behavior without implementing an HLS server. Questions: Is AVAssetResourceLoaderDelegate the right approach for this use case? If so, how can we ensure shouldWaitForLoadingOfRequestedResource is called whenever new data is available in the buffer? Are there alternative APIs or recommended patterns for playing real-time MP4 data chunks in AVPlayer? Would implementing a custom FFmpeg-based player be necessary, or can this be achieved using AVPlayer and its APIs? We appreciate any guidance, suggestions, or examples that can help us achieve this. Thank you!

Hi everyone, I'm developing a customization tool in which our customer can upload a mp3 or mp4 file that will be scannable through our AR application. On desktop and Android, this is working perfectly. For some reason however, on iPhone we're unable to load most of the video files. I've checked the clips, and they are .mov/h.264 files which are supported by iPhone. We're currently not sure how we can fix this issue to allow customers that own an iPhone to upload clips to our website. Any tips in the right direction are more than welcome. thanks in advance!