Hello, I am exploring real-time object detection, and its replacement/overlay with another shape, on live video streams for an iOS app using Core ML and Vision frameworks. My target is to achieve high-speed, real-time detection without noticeable latency, similar to what’s possible with PageFault handling and Associative Caching in OS, but applied to video processing. Given that this requires consistent, real-time model inference, I’m curious about how well the Neural Engine or GPU can handle such tasks on A-series chips in iPhones versus M-series chips (specifically M1 Pro and possibly M4) in MacBooks. Here are a few specific points I’d like insight on: Hardware Suitability: How feasible is it to perform real-time object detection with Core ML on the Neural Engine (i.e., can it maintain low latency)? Would the M-series chips (e.g., M1 Pro or newer) offer a tangible benefit for this type of task compared to the A-series in mobile devices? Which A- and M- chips would be minimum feasible recommendation for such task. Performance Expectations: For continuous, live video object detection, what would be the expected frame rate or latency using an optimized Core ML model? Has anyone benchmarked such applications, and is the M-series required to achieve smooth, real-time processing? Differences Across Apple Hardware: How does performance scale between the A-series Neural Engine and M-series GPU and Neural Engine? Is the M-series vastly superior for real-time Core ML tasks like object detection on live video feeds? If anyone has attempted live object detection on these chips, any insights on real-time performance, limitations, or optimizations would be highly appreciated. Please refer: Apple APIs Thank you in advance for your help!

Hello, we're investigating an option to disable writing tools for some customers in our app. I'm aware of the writingToolsBehavior property for UITextView etc, but we would like to have a way to set this globally without having to update all UITextView instances (or future instances). Is there any API to do this? We tried using UITextView.appearance.writingToolsBehavior = .none and it seemed promising on 18.2 beta, however it introduced crashes on devices running 18.1. The crashes look like: *** Terminating app due to uncaught exception 'NSInternalInconsistencyException', reason: 'Have you sent -setWritingToolsBehavior: to <UITextView: 0x14462c000; frame = (0 0; 0 0); text = ''; userInteractionEnabled = NO; gestureRecognizers = <NSArray: 0x30067cb40>; backgroundColor = UIExtendedGrayColorSpace 0 0; layer = <CALayer: 0x3009b1ba0>; contentOffset: {0, 0}; contentSize: {0, 0}; adjustedContentInset: {0, 0, 0, 0}> off the main thread? To verify, look for a complaint in the logs: "Unsupported use of UIKit…", and fix the problem if you find it. If your use is main-thread only please file a radar on UIKit, and attach this log. exercisedImplementations = { "setWritingToolsBehavior:" = ( ); }' Similarly, even on 18.2 beta if we used UITextField.appearance.writingToolsBehavior = .none we would see crashes for any search fields like: *** Terminating app due to uncaught exception 'NSInternalInconsistencyException', reason: 'Have you sent -setWritingToolsBehavior: to <UISearchBarTextField: 0x141c04a00; frame = (0 0; 0 0); text = ''; opaque = NO; gestureRecognizers = <NSArray: 0x301fe15c0>; placeholder = Search Leads; borderStyle = RoundedRect; background = <_UITextFieldSystemBackgroundProvider: 0x3015de960: backgroundView=<_UISearchBarSearchFieldBackgroundView: 0x141c60200; frame = (0 0; 0 0); opaque = NO; autoresize = W+H; userInteractionEnabled = NO; layer = <CALayer: 0x3015de8e0>>, fillColor=(null), textfield=<UISearchBarTextField: 0x141c04a00>>; layer = <CALayer: 0x3015de240>> off the main thread? To verify, look for a complaint in the logs: "Unsupported use of UIKit…", and fix the problem if you find it. If your use is main-thread only please file a radar on UIKit, and attach this log. exercisedImplementations = { "setWritingToolsBehavior:" = ( ); }' Is it possible to set this globally?

I noticed that the ChatGPT is listed as an "Extension" in the Apple Intelligence settings on iOS 18.2 beta. Does this mean developers will be able to create their own extensions? Or will this be limited to larger companies to incorporate their own models into Apple Intelligence?

Hi everyone, Could someone confirm if it's currently possible, or if there are any plans, to restrict users from enabling Apple Intelligence altogether? I understand that we can block individual features using MDM, but I'm interested in knowing if we can prevent users from toggling Apple Intelligence on and off in System Settings entirely. Thanks! Kind Regards, Filipe Nogueira

Hi everyone, I'm working on integrating object recognition from live video feeds into my existing app by following Apple's sample code. My original project captures video and records it successfully. However, after integrating the Vision-based object detection components (VNCoreMLRequest), no detections occur, and the callback for the request is never triggered. To debug this issue, I’ve added the following functionality: Set up AVCaptureVideoDataOutput for processing video frames. Created a VNCoreMLRequest using my Core ML model. The video recording functionality works as expected, but no object detection happens. I’d like to know: How to debug this further? Which key debug points or logs could help identify where the issue lies? Have I missed any key configurations? Below is a diff of the modifications I’ve made to my project for the new feature. Diff of Changes: (Attach the diff provided above) Specific Observations: The captureOutput method is invoked correctly, but there is no output or error from the Vision request callback. Print statements in my setup function setForVideoClassify() show that the setup executes without errors. Questions: Could this be due to issues with my Core ML model compatibility or configuration? Is the VNCoreMLRequest setup incorrect, or do I need to ensure specific image formats for processing? Platform: Xcode 16.1, iOS 18.1, Swift 5, SwiftUI, iPhone 11, Darwin MacBook-Pro.local 24.1.0 Darwin Kernel Version 24.1.0: Thu Oct 10 21:02:27 PDT 2024; root:xnu-11215.41.3~2/RELEASE_X86_64 x86_64 Any guidance or advice is appreciated! Thanks in advance.

Hi, The most recent version of tensorflow-metal is only available for macosx 12.0 and python up to version 3.11. Is there any chance it could be updated with wheels for macos 15 and Python 3.12 (which is the default version supported for tensrofllow 2.17+)? I'd note that even downgrading to Python 3.11 would not be sufficient, as the wheels only work for macos 12. Thanks.

Hey, has anyone figured out how the “Persons” list in Genmoji/Playground actually works? I’ve had a strange experience so far. When I first got access during Beta 2, the list randomly included about 10–15 people, even though my photo library contains many more recognizable faces. To try fixing this, I started naming faces in the Photos app, hoping they’d be added to the Genmoji/Playground list, but nothing changed. Then, after updating to Beta 3, it added just 2–3 of the people I had named. Encouraged, I spent about an hour naming all the faces in my library. But a few hours later, the list unexpectedly removed around 10 people, leaving me with fewer than I had initially. I’ve also read that leaving the phone locked and plugged into power should help sort people in the library, but that hasn’t worked for me yet. Anyone else experienced this or found a way to make it work? Thanks!

Itself been 4-5 days my Image playground has showing the “Downloading Support for Image Playground “

I tried this: struct CarShortcutsProvider: AppShortcutsProvider { @AppShortcutsBuilder static var appShortcuts: [AppShortcut] { AppShortcut( intent: LockCarIntent(), phrases: ["Lock my car with \(.applicationName)", "Lock my \(\.$car) with \(.applicationName)"], shortTitle: LocalizedStringResource("Lock Car"), systemImageName: "lock.fill" ) AppShortcut( intent: UnlockCarIntent(), phrases: ["Unlock my car with \(.applicationName)", "Unlock my \(\.$car) with \(.applicationName)"], shortTitle: LocalizedStringResource("Unlock Car"), systemImageName: "lock.open.fill" ) } } but Siri only understands "unlock my car ", not with the placeholder. Siri asks me then for the car, and it understands it, but not in one sentence. Is there something wrong with my code? Also I tried it without applicationName first, and then it didn't work at all with Siri. Is this a general limitation of app intents? I thought the goal was to reduce friction. If the user has to mention the app name all the time, it adds friction.

In our app we use CoreML. But ever since macOS 15.x was released we started to get a great bunch of crashes like this: Incident Identifier: 424041c3-884b-4e50-bb5a-429a83c3e1c8 CrashReporter Key: B914246B-1291-4D44-984D-EDF84B52310E Hardware Model: Mac14,12 Process: <REMOVED> [1509] Path: /Applications/<REMOVED> Identifier: com.<REMOVED> Version: <REMOVED> Code Type: arm64 Parent Process: launchd [1] Date/Time: 2024-11-13T13:23:06.999Z Launch Time: 2024-11-13T13:22:19Z OS Version: Mac OS X 15.1.0 (24B83) Report Version: 104 Exception Type: SIGABRT Exception Codes: #0 at 0x189042600 Crashed Thread: 36 Thread 36 Crashed: 0 libsystem_kernel.dylib 0x0000000189042600 __pthread_kill + 8 1 libsystem_c.dylib 0x0000000188f87908 abort + 124 2 libsystem_c.dylib 0x0000000188f86c1c __assert_rtn + 280 3 Metal 0x0000000193fdd870 MTLReportFailure.cold.1 + 44 4 Metal 0x0000000193fb9198 MTLReportFailure + 444 5 MetalPerformanceShadersGraph 0x0000000222f78c80 -[MPSGraphExecutable initWithMPSGraphPackageAtURL:compilationDescriptor:] + 296 6 Espresso 0x00000001a290ae3c E5RT::SharedResourceFactory::GetMPSGraphExecutable(std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> > const&, NSDictionary*) + 932 . . . 43 CoreML 0x0000000192d263bc -[MLModelAsset modelWithConfiguration:error:] + 120 44 CoreML 0x0000000192da96d0 +[MLModel modelWithContentsOfURL:configuration:error:] + 176 45 <REMOVED> 0x000000010497b758 -[<REMOVED> <REMOVED>] (<REMOVED>) No similar crashes on macOS 12-14! MetalPerformanceShadersGraph.log Any clue what is causing this? Thanks! :)

I have followed https://apple.github.io/coremltools/docs-guides/source/installing-coremltools.html but failed. Looks like the doc is too outdated.

Hi Everyone, I'm currently facing an issue where TensorFlow is unable to detect the GPU on my M1 Mac for model training. When I run the following code to check for available GPUs: import tensorflow as tf print("Num GPUs Available: ", len(tf.config.list_physical_devices('GPU'))) Num GPUs Available: 0 I have already applied the steps mentioned in the developer apple document. https://developer.apple.com/metal/tensorflow-plugin/ System Information: Device: M1 Mac Pro Max Python Version: 3.12.2 TensorFlow Version: 2.17.0 OS: macOS Sequoia (15.1) Questions: Is there any additional configuration required to enable GPU support on M1 Macs? Are there specific TensorFlow versions that I should be using for better compatibility? Has anyone else faced this issue, and how did you resolve it?

Hi, I am trying to create a multi label image classifier model using CreateML (the one included in Xcode 16.1). However, my annoations.json file won't get accepted by the app. I get the following error: annotations.json file contains field "Index 0" that is not of type String Here is a JSON example which results in said error: [ { "image": "image1.jpg", "annotations": [ { "label": "car-license-plate", "coordinates": { "x": 160, "y": 108, "width": 190, "height": 200 } } ] }, { "image": "image2.jpg", "annotations": [ { "label": "car-license-plate", "coordinates": { "x": 250, "y": 150, "width": 100, "height": 98 } } ] } ]

Hello! I've been trying to run tensorflow on my MBA M3. I previously had an Intel Mac and was able to run tensorflow without any problem. I've been working on a personal project in a directory I made on my previous Mac, that I was running through Jupyter notebook. Now every time I try to run the code, the kernel will die and I'm unsure what to do. I tried following tutorials, but every tutorial I've seen has made me create a new environment to access Jupyter Notebook, but not letting me access notebooks and files that have already been created. I tried to run this following command in terminal and received the subsequent error back. python -m pip install tensorflow-metal ERROR: Could not find a version that satisfies the requirement tensorflow-metal (from versions: none) ERROR: No matching distribution found for tensorflow-metal I've installed miniforge, Xcode, and anaconda onto my computer already and wanted some assistance.

I click Join the Apple Intelligence Waitlist and chose Join Waitlist, but no show Joined list

Attempting to set up ComfyUI-CoreMLSuite on my Mac Studio. ComfyUI starts but no Core nodes are in the add-node-list. cloned both ComfyUI-CoreMLSuite and ml-stable-diffusion into custom_nodes and bounced the ComfyUI server. The startup complains that ml-stable-diffusion has no init.py. FileNotFoundError: [Errno 2] No such file or directory: ... /ComfyUI/custom_nodes/ml-stable-diffusion/init.py' It appears to be a show stopper. What to do?

I just got my new iPhone 16 Pro and upgraded to the 18.2 developer beta 4. I've set both Siri and the device language to English (United States), but the Apple Intelligence feature still doesn’t appear in my settings.

Hi, I'm trying to analyze images in my Photos library with the following code: func analyzeImages(_ inputIDs: [String]) { let manager = PHImageManager.default() let option = PHImageRequestOptions() option.isSynchronous = true option.isNetworkAccessAllowed = true option.resizeMode = .none option.deliveryMode = .highQualityFormat let concurrentTasks=1 let clock = ContinuousClock() let duration = clock.measure { let group = DispatchGroup() let sema = DispatchSemaphore(value: concurrentTasks) for entry in inputIDs { if let asset=PHAsset.fetchAssets(withLocalIdentifiers: [entry], options: nil).firstObject { print("analyzing asset: \(entry)") group.enter() sema.wait() manager.requestImage(for: asset, targetSize: PHImageManagerMaximumSize, contentMode: .aspectFit, options: option) { (result, info) in if let result = result { Task { print("retrieved asset: \(entry)") let aestheticsRequest = CalculateImageAestheticsScoresRequest() let fingerprintRequest = GenerateImageFeaturePrintRequest() let inputImage = result.cgImage! let handler = ImageRequestHandler(inputImage) let (aesthetics,fingerprint) = try await handler.perform(aestheticsRequest, fingerprintRequest) // save Results print("finished asset: \(entry)") sema.signal() group.leave() } } else { group.leave() } } } } group.wait() } print("analyzeImages: Duration \(duration)") } When running this code, only two requests are being processed simultaneously (due to to the semaphore)... However, if I call the function with a large list of images (>100), memory usage balloons over 1.6GB and the app crashes. If I call with a smaller number of images, the loop completes and the memory is freed. When I use instruments to look for memory leaks, it indicates no memory leaks are found, but there are 150+ VM:IOSurfaces allocated by CMPhoto, CoreVideo and CoreGraphics @ 35MB each. Shouldn't each surface be released when the task is complete?

Hi! I recently updated to the latest 18.2 Beta version of iOS on my iPhone 15 Pro Max. Could you please guide me on how to locate and utilize the Image Search feature powered by Apple Intelligence? Just a little detail: I went on YouTube and the instruction was to hold the camera action button on the iPhone 16 and image search appears. So far, I haven’t been able to replicate these results on my iPhone 15 Pro Max. This is a great capability and I’d really like to try it out. “Live long and prosper.” -Spock -Jordan

So when I was on the Settings app. I couldn’t see it, but I updated it and I don’t it why don’t is this a glitch please fix it your friend Isaiah.