Hey everyone, I want to add an if statement that would do something along the lines of this: if confidence = 100% { } How could I do this? I already have a createML model. Thank you, Oliver

I would like to make use of create ML to classify a motion. However, it seems it requires 2 classes at least to train or test it. What should I do as I only has 1 class (the target motion). Also, how to interpret the 'Recall' and 'F1 Score'

We are using VNRecognizeTextRequest to detect text in documents, and we have noticed that even in some very clear and well-formatted documents, there are still instances where text blocks are missed. the live text also have the same issue.

When using CoreML for VAE model prediction, the prediction result shows a distorted display with no error messages. How can this issue be addressed?

In this thread, I asked about adding parameters to App Shortcuts. The conclusion that I've drawn so far is that for App Shortcuts, there cannot be any parameters in the prompt, otherwise the system cannot find the AppShortcutsProvider. While this is fine for Shortcuts and non-voice interaction, I'd like to find a way to add parameters to the prompt. Here is the scenario: My app controls a device that displays some content on "pages." The pages are defined in an AppEnum, which I use for Shortcuts integration via App Intents. The App Intent functions as expected, and is able to change the page based on the user selection within Shortcuts (or prompted if using the App Shortcut). What I'd like to do is allow the user to be able to say "Siri, open with ." So far, The closest I've come to understanding how this works is through the .intentsdefinition file you can create (and SiriKit in general), however the part that really confused me there is a button in the File Editor that says "Convert to App Intent." To me, this means that I should be able to use the app intent I've already authored and hook that into Siri, rather than making an entirely new function/code-block that does exactly the same thing. Ideally, that's what I want to do. What's the right way to define this behavior? p.s. If I had to pick an intent schema in the context of AssistantSchemas, I'd say it's closest to the "Open File" one, if that helps. I'd ultimately like to make the "pages" user-customizable so in the long run, that would be what I'd do.

I've been following along with "App Shortcuts" development but cannot get Siri to run my Intent. The intent on its own works in Shortcuts, along with a couple others that aren't in the AppShortcutsProvder structure. I keep getting the following two errors, but cannot figure out why this is occurring with documentation or other forum posts. No ConnectionContext found for 12909953344 Attempted to fetch App Shortcuts, but couldn't find the AppShortcutsProvider. Here are the relevant snippets of code - (1) The AppIntent definition struct SetBrightnessIntent: AppIntent { static var title = LocalizedStringResource("Set Brightness") static var description = IntentDescription("Set Glass Display Brightness") @Parameter(title: "Level") var level: Int? static var parameterSummary: some ParameterSummary { Summary("Set Brightness to \(\.$level)%") } func perform() async throws -> some IntentResult { guard let level = level else { throw $level.needsValueError("Please provide a brightness value") } if level > 100 || level <= 0 { throw $level.needsValueError("Brightness must be between 1 and 100") } // do stuff with level return .result() } } (2) The AppShortcutsProvider (defined in my iOS app target, there are no other targets) struct MyAppShortcuts: AppShortcutsProvider { static var shortcutTileColor: ShortcutTileColor = .grayBlue @AppShortcutsBuilder static var appShortcuts: [AppShortcut] { AppShortcut( intent: SetBrightnessIntent(), phrases: [ "set \(.applicationName) brightness to \(\.$level)", "set \(.applicationName) brightness to \(\.$level) percent" ], shortTitle: LocalizedStringResource("Set Glass Brightness"), systemImageName: "sun.max" ) } } Does anything here look wrong? Is there some magical key that I need to specify in Info.plist to get Siri to recognize the AppShortcutsProvider? On Xcode 16.2 and iOS 18.2 (non-beta).

Note: I posted this to the feedback assistant but haven't gotten a response for 3months =( FB13482199 I am trying to train a large image classifier. I have a training run for ~300000 images. Each image has a folder and the file names within the folders are somewhat random. 381 classes. I am on an M2 Pro, Sonoma 14.0 running CreateML Version 5.0 (121.1). I would prefer not to pursue the pytorch/HF -> coremltools route. CreateML seems to consistently crash ~25000-30000 images in during the feature extraction phase with "Unexpected Error". It does not seem to be due to an out of memory issue. I am looking for some guidance since it seems impossible to debug why this is consistently crashing. My initial assumption was that it could be due to blank/corrupt files. I do not think that is the case. I also checked if there were any special characters in the data/folders. I wasn't able to go through all, but did try some programatic regex. Don't think this is the case either. I attached the sysdiagnose results in feedback assistant after the crash happened. I did notice when going into /var/logs there was some write issue saying that Mac had written too much to disk. Note: I also tried Xcode 15.2-beta this time and the associated CoreML version. My questions: How can I fix this? How should I go about debugging CreateML errors in the future? 'Unexpected Error' - where can I go about getting the exact createml logs on my device? This is far too broad of an error statement Please let me know. As a note, I did successfully train a past model on ~100000 images. I am planning to 10-15x that if this run is successful. Please help, spent a lot of time gathering the extra data and to date have been an occasional power user of createml. Haven't heard back from Apple since December =/. I assume I'm not the only one with this problem, so looking for any instructions to hands on debug and help others. Thx!

It appears that there is a size limit when training the Tabular Classification model in CreatML. When the training data is small, the training process completes smoothly after a specified period. However, as the data volume increases, the following issues occur: initially, the training process indicates that it is in progress, but after approximately 24 hours, it is automatically terminated after an hour. I am certain that this is not a manual termination by myself or others, but rather an automatic termination by the machine. This issue persists despite numerous attempts, and the only message displayed is “Training Canceled.” I would appreciate it if someone could explain the reason behind this behavior and provide a solution. Thank you for your assistance.

Some of my users are experiencing crashes on instantiation of a CoreML model I've bundled with my app. I haven't been able to reproduce the crash on any of my devices. Crashes happen across all iOS 18 releases. Seems like something internal in CoreML is causing an issue. Full stack trace: 6646631296fb42128ddc340b2d4322f7-symbolicated.crash

Hi, I want to develop an app which makes use of Image Playground. However, I am located in Europe which makes it impossible for me as Image Playground is not available for me. Even if I would like to distribute the app in the US. Nor the simulator, nor a physical device will always return that support for ImagePlayground is not supported (@Environment(.supportsImagePlayground) private var supportsImagePlayground) How to set my environment such that I can test the feature in my iOS application

I'm trying to use the Spatial model to perform Object Tracking on a .usdz file that I create. After loading the file, which I can view correctly in the console, I start the training. Initially, I notice that the disk usage on my PC increases. After several GB, the usage stops, but the training progress remains for hours at 0.00% with the message "About 8hr." How can I understand what the issue is? Has anyone else experienced the same problem? Thanks Diego

I'm using Numbers to build a spreadsheet that I'm exporting as a CSV. I then import this file into Create ML to train a word tagger model. Everything has been working fine for all the models I've trained so far, but now I'm coming across a use case that has been breaking the import process: commas within the training data. This is a case that none of Apple's examples show. My project takes Navajo text that has been tokenized by syllables and labels the parts-of-speech. Case that works... Raw text: Naaltsoos yídéeshtah. Tokens column: Naal,tsoos, ,yí,déesh,tah,. Labels column: NObj,NObj,Space,Verb,Verb,VStem,Punct Case that breaks... Raw text: óola, béésh łigaii, tłʼoh naadą́ą́ʼ, wáin, akʼah, dóó á,shįįh Tokens column with tokenized text (commas quoted): óo,la,",", ,béésh, ,łi,gaii,",", ,tłʼoh, ,naa,dą́ą́ʼ,",", ,wáin,",", ,a,kʼah,",", ,dóó, ,á,shįįh (Create ML reports mismatched columns) Tokens column with tokenized text (commas escaped): óo,la,\,, ,béésh, ,łi,gaii,\,, ,tłʼoh, ,naa,dą́ą́ʼ,\,, ,wáin,\,, ,a,kʼah,\,, ,dóó, ,á,shįįh (Create ML reports mismatched columns) Tokens column with tokenized text (commas escape-quoted): óo,la,\",\", ,béésh, ,łi,gaii,\",\", ,tłʼoh, ,naa,dą́ą́ʼ,\",\", ,wáin,\",\", ,a,kʼah,\",\", ,dóó, ,á,shįįh (record not detected by Create ML) Tokens column with tokenized text (commas escape-quoted): óo,la,"","", ,béésh, ,łi,gaii,"","", ,tłʼoh, ,naa,dą́ą́ʼ,"","", ,wáin,"","", ,a,kʼah,"","", ,dóó, ,á,shįįh (Create ML reports mismatched columns) Labels column: NSub,NSub,Punct,Space,NSub,Space,NSub,NSub,Punct,Space,NSub,Space,NSub,NSub,Punct,Space,NSub,Punct,Space,NSub,NSub,Punct,Space,Conj,Space,NSub,NSub Sample From Spreadsheet Solution Needed It's simple enough to escape commas within CSV files, but the format needed by Create ML essentially combines entire CSV records into single columns, so I'm ending up needing a CSV record that contains a mixture of commas to use for parsing and ones to use as character literals. That's where this gets complicated. For this particular use case (which seems like it would frequently arise when training a word tagger model), how should I properly escape a comma literal?

Hi everyone, I've been struggling for a few weeks to integrate my Core ML Image Classifier model into my .swiftpm project, and I’m hoping someone can help. Here’s what I’ve done so far: I converted my .mlmodel file to .mlmodelc manually via the terminal. In my Package.swift file, I tried both "copy" and "process" options for the resource. The issues I’m facing: When using "process", Xcode gives me the error: "multiple resources named 'coremldata.bin' in target 'AppModule'." When using "copy", the app runs, but the model doesn’t work, and the terminal shows: "A valid manifest does not exist at path: .../Manifest.json." I even tried creating a Manifest.json manually to test, but this led to more errors, such as: "File format version must be in the form of major.minor.patch." "Failed to look up root model." To check if the problem was specific to my model, I tested other Core ML models in the same setup, but none of them worked either. I feel stuck and unsure of how to resolve these issues. Any guidance or suggestions would be greatly appreciated. Thanks in advance! :)

I am currently training a Tabular Classification model in CreatML. The dataset comprises 30 features, including 1,000,000 training data points and 1,000,000 verification data points. Could you please estimate the approximate training time for an M4Max MacBook Pro? During the training process, CreatML has been displaying the “Processing” status, but there is no progress bar. I would like to ascertain whether the training is still ongoing, as I have often suspected that it has ceased.

Hi I'm having a problem with DataScannerViewController, I'm using the volume barcode scanning feature in my app, prior to that I was using an AVCaptureDevice with the UltraWideAngle set. After discovering DataScannerViewController, we planned to replace the previous obsolete code with DataScannerViewController, all together it was ok, when I want to set the ultra wide angle, I don't know how to start. I tried to get the minZoomFactor and I realized that I get 0.0 I tried to set zoomFactor to 1.0 and I found that he is not valid Note: func dataScannerDidZoom(_ dataScanner: DataScannerViewController), when I try to get the minZoomFactor, set the zoomFactor in this proxy method, I find that it is valid! What should I do next, I want to use only DataScannerViewController and implement ultra wide angle Thanks a lot.

When using the imagePlaygroundSheet modifier in SwiftUI, the system presets an image playground in a fixed size. Especially on macOS, this modal is rather small and doesn't utilize the available space efficiently. Is there a way to make the modal bigger, or allow the user to resize the dialog? I tried presentationDetents, but this would need to be applied to the content of the sheet, which is provided by the system... I guess this question applies to other system-provided sheets like the photo picker as well.

I live in EU, Ireland, And I don’t have access to apple intelligence. I have ios18 running on iPhone XR, but please make apple intelligence available on EU

@property (assign,nonatomic) long long experimentalMLE5EngineUsage; //@synthesize experimentalMLE5EngineUsage=_experimentalMLE5EngineUsage - In the implementation block What is it, and why would disabling it fix NMS for a MLProgram? Is there anyway to ****** this flag from model metadata? Is there anyway to ****** or disable from a global, system-level scope? It's extremely easy to reproduce, but do not know how to investigate the drastic regression between toggling this flag let config = MLModelConfiguration() config.setValue(1, forKey: "experimentalMLE5EngineUsage")

Hello, I have a question regarding hybrid execution for deep learning models on Apple's Neural Engine and CPU. I am aware that setting the precision of some layers to 32-bit allows hybrid execution across both the Neural Engine and the CPU. However, I would like to know if it is possible to achieve the same with 16-bit precision. Is there any specific configuration or workaround to enable hybrid execution in this case? Any guidance or documentation references would be greatly appreciated. Thank you!

Hi, I'm working with vision framework to detect barcodes. I tested both ean13 and data matrix detection and both are working fine except for the QuadrilateralProviding values in the returned BarcodeObservation. TopLeft, topRight, bottomRight and bottomLeft coordinates are rotated 90° counter clockwise (physical bottom left of data Matrix, the corner of the "L" is returned as the topLeft point in observation). The same behaviour is happening with EAN13 Barcode. Did someone else experienced the same issue with orientation? Is it normal behaviour or should we expect a fix in next releases of the Vision Framework?