I'm looking for a solution to take a picture or point the camera at a piece of clothing and match that image with an image the user has stored in my app. I'm storing the data in a Core Data database as a Binary Data object. Since the user also takes the pictures they store in the database I think I cannot use pre-trained Core ML models. I would like the matching to be done on device if possible instead of going to an external service. That will probably describe the item based on what the AI sees, but then I cannot match the item with the stored images in the app. Does anyone know if this is possible with frameworks as Vision or VisionKit?

I want to implement AppIntent in my framework which is created and choose Objective-C as language, but when I new a swift file and implement AppIntent. then import to my project. the AppIntent didn't work. but I can use AppIntent directly in project.

I am developing an iPhone application. When I start testing in a simulator or on an actual device, I get the following message depending on the model. I don't see any problem with the actual operation of the app, but I don't know how to resolve this error. #FactoryInstall Unable to query results, error: 5 Unable to list voice folder Unable to list voice folder Unable to list voice folder Unable to list voice folder Unable to list voice folder I have tried to resolve the problem by following the steps below, but it hasn’t had any affect on the error. Is it OK to leave this error as it is? If you know how to resolve it, please let me know. Clear the Xcode cache: Go to the path of the DerivedData folder and delete all of its contents. Clean Build folder: Select "Product" -> "Clean Build Folder" from the Xcode menu. Restart: Restart Xcode and the simulator. Software update: Make sure you are using the latest version of Xcode and macOS. Reinstallation: Uninstall Xcode once and reinstall it. Reset the simulator

Hello! I've noticed that adding localizations for AppShortcuts triggers the following warnings in Xcode 15.3: warning: missing the definition of zh-Hans # variables.1.definitions warning: missing the definition of zh-Hans # variables.2.definitions This occurs with both legacy strings files and String Catalogs. Example project: https://github.com/gongzhang/AppShortcutsLocalizationWarningExample

After watching the What's new in App Intents session I'm attempting to create an intent conforming to URLRepresentableIntent. The video states that so long as my AppEntity conforms to URLRepresentableEntity I should not have to provide a perform method . My application will be launched automatically and passed the appropriate URL. This seems to work in that my application is launched and is passed a URL, but the URL is in the form: FeatureEntity/{id}. Am I missing something, or is there a trick that enables it to pass along the URL specified in the AppEntity itself? struct MyExampleIntent: OpenIntent, URLRepresentableIntent { static let title: LocalizedStringResource = "Open Feature" static var parameterSummary: some ParameterSummary { Summary("Open \(\.$target)") } @Parameter(title: "My feature", description: "The feature to open.") var target: FeatureEntity } struct FeatureEntity: AppEntity { // ... } extension FeatureEntity: URLRepresentableEntity { static var urlRepresentation: URLRepresentation { "https://myurl.com/\(.id)" } }

I just downgraded from iOS 18 to iOS 17.5.1 and Siri not working anymore i cannot even setup i have already make reset the phone and not working:(

I noticed the code snippets are missing from the wwdc2024 10210 video titled Bring your app’s core features to users with App Intents https://developer.apple.com/videos/play/wwdc2024/10210/ It would be useful if those could be added. I also noticed the transcript is missing from the web version but it is in the Developer app, that is odd.

The documentation for translationTask(source:target:action:) says it should translate when content appears, but this isn't happening. I’m only able to translate when I manually associate that task with a configuration, and instantiate the configuration. Here’s the complete source code: import SwiftUI import Translation struct ContentView: View { @State private var originalText = "The orange fox jumps over the lazy dog" @State private var translationTaskResult = "" @State private var translationTaskResult2 = "" @State private var configuration: TranslationSession.Configuration? var body: some View { List { // THIS DOES NOT WORK Section { Text(translationTaskResult) .translationTask { session in Task { @MainActor in do { let response = try await session.translate(originalText) translationTaskResult = response.targetText } catch { print(error) } } } } // THIS WORKS Section { Text(translationTaskResult2) .translationTask(configuration) { session in Task { @MainActor in do { let response = try await session.translate(originalText) translationTaskResult2 = response.targetText } catch { print(error) } } } Button(action: { if configuration == nil { configuration = TranslationSession.Configuration() return } configuration?.invalidate() }) { Text("Translate") } } } } } How can I automatically translate a given text when it appears using the new translationTask API?

Using App Shortcuts with app intents, Siri only responds to the first shortcut defined in the app shortcut below. struct MementoShortcuts: AppShortcutsProvider { u/AppShortcutsBuilder static var appShortcuts: [AppShortcut] { AppShortcut( intent: SaveLinkIntent(), phrases: ["Add a link to \(.applicationName)", "Add \(\.$url) to \(.applicationName)", "Make a new link in \(.applicationName)", "Create a new link in \(.applicationName) from \(\.$url)"], shortTitle: "Add Link", systemImageName: "link.badge.plus" ) AppShortcut( intent: LinkViewedIntent(), phrases: [ "Mark a link I saved in \(.applicationName) as viewed", "Mark \(\.$link) as viewed in \(.applicationName)", "Set link in \(.applicationName) to viewed", "Change status of \(\.$link) to viewed in \(.applicationName)", ], shortTitle: "Mark Link as Viewed", systemImageName: "book" ) } } I have tried switching the order and she always uses the one that comes first. Both show up in the shortcuts app as an app shortcut, but only one shortcut is recognized by Siri even if I say the other one's phrase.

Hi everyone, I was wondering, on how accurate is the Hand Classification ML? For Example: Is it possible to understand the different letters of the Sign Language Alphabet or is it only capable of recognizing simple poses like a thumbs up?

When in Safari, you can say something like, "Siri, text this link to mom" or "Siri, save this link to reminders" and it will do it with the currently viewed link. Shortcuts also has a "Get what's on screen" action that can be added. How do I expose the user's current context to my App Intent?

I'm playing with the new Vision API for iOS18, specifically with the new CalculateImageAestheticsScoresRequest API. When I try to perform the image observation request I get this error: internalError("Error Domain=NSOSStatusErrorDomain Code=-1 \"Failed to create espresso context.\" UserInfo={NSLocalizedDescription=Failed to create espresso context.}") The code is pretty straightforward: if let image = image { let request = CalculateImageAestheticsScoresRequest() Task { do { let cgImg = image.cgImage! let observations = try await request.perform(on: cgImg) let description = observations.description let score = observations.overallScore print(description) print(score) } catch { print(error) } } } I'm running it on a M2 using the simulator. Is it a bug? What's wrong?

I consistently receive corrupted results from tf.signal.fft3d() when it is within a function that has a @tf.function decorator. The results are all zero (0.) for entries after a certain x index (see image). Surprisingly, the issue depends on the matrix size. For example, (1023, 1023, 287) works but (1023, 1023, 575) does not. The issue is problematic because it occurs silently and not for all matrix sizes, i.e. can easily slip through tests. The error occurs only when tensorflow-metal is installed. The Tensorflow version is 2.16.1. My hardware is a Macbook Pro M3 Max with 40 GPU cores, 128 GB RAM running MacOS Sonoma version 14.5 (23F79). A Python environment to reproduce the bug can be created as follows: conda create --name tfmetalbug python=3.11.9 conda activate tfmetalbug pip install tensorflow tensorflow-metal conda install matplotlib The following code reproduces the issue: import tensorflow as tf import numpy as np import matplotlib.pyplot as plt # Wrap fft3d with tf.function @tf.function def fft3d_wrapper_function(x): return tf.signal.fft3d(x) # Generate a 3D image img = tf.random.normal(shape=(1023, 1023, 575), stddev=1., dtype=float) # generate random 3d image img = tf.dtypes.cast(img, tf.complex64) # convert to complex values # Compute the 3D FFT img_fft = fft3d_wrapper_function(img) # Visualize the 3D FFT plt.imshow(np.real(img_fft)[:, img_fft.shape[1]//2+10, :], cmap="gray", vmin=-0.001, vmax=0.001) plt.savefig("fft3d_wrapper_function.png") For me, removing the @tf.function decorator has resolved the issue.

Does the new Image Playground API allow programmatically generating images? Can the app generate and use them without the API's UI or would that require using another generative image model?

Hello. Where can I find some examples on creating custom genmojis in Swift and reusing it in an App?

Hei Sir is not working in ios beta 18

Hellooo, I’m looking to implement an OpenAI assistant using APIs but I want to do this locally on a group of files. I want to be able to train a GPT on the contents of a folder for example. Does anyone have any experience in this? It seems OpenAI needs a lot of uploading on each request if I were to do this with their API after playing around (but this feels like I’m missing something). It’s also quite costly to use. I was hoping to use local machine learning and models but this is quite limited in what it can do (eg Lumachain)

My App has several resources that I'd like to spring open through App Intents. For example a series of Dictionaries. These resources however in the app are behind a log in (for security) and are entitlements that are purchased. They may own 4 of 7 dictionaries. If I want to have an intent that says, "Open Dictionary: (Dict Name)" how do I best handle situations where the user may no longer be logged in or have the entitlement for that specific dictionary? Thanks

I have a Shortcuts action via an App Intent that I want only for active subscribers to use. I have a shared class that handles all the subcription related things. But for some reason my code only works if the app is active in the background. Once the app is quitted and the user performs the Shortcut, the not subscribed error is thrown – even though the user is subscribed. How can I ensure that my subscription check is done correctly, if the app isn’t open in the background? My Code App Intent excerpt: @MainActor func perform() async throws -> some IntentResult & ReturnsValue<MeterIntentEntity> { // Validate that the user is subscribed. // Cancels action with error message if not subscribed. if SubscriptionManager.shared.userIsSubscribed == false { throw IntentError.notSubscribed } // More Code … // Finish and pass created value as result. return .result(value: something) } Subscription Manager excerpt: class SubscriptionManager: ObservableObject { // A singleton for our entire app to use static let shared = SubscriptionManager() let productIds = ["my_sub1", "my_sub2"] @Published private(set) var availableSubscriptions: [Product] @Published private(set) var purchasedSubscriptions: [Product] = [] public var userIsSubscribed: Bool { return !self.purchasedSubscriptions.isEmpty } init() { // Initialize empty products, and then do a product request asynchronously to fill them in. availableSubscriptions = [] Task { await updatePurchasedProducts() } } @MainActor func updatePurchasedProducts() async { for await result in Transaction.currentEntitlements { do { let transaction = try checkVerified(result) if let subscription = availableSubscriptions.first(where: { $0.id == transaction.productID }) { purchasedSubscriptions.append(subscription) } } catch { Logger.subscription.error("Error loading users user's purchased products.") } } }

Hi, this is the 3rd time I'm trying to post this on the forum, apple moderators ignoring it. I'm a deep learning expert with a specialization of image processing. I want to know why I have hundreds of AI models on my Mac that are indexing everything on my computer while it is idle, using programs like neuralhash that I can't find any information about. I can understand if they are being used to enhance the user experience on Spotlight, Siri, Photos, and other applications, but I couldn't find the necessary information on the web. Usually, (spyware) software like this uses them to classify files in an X/Y coordinate system. This feels like a more advanced version of stuxnet. find / -type f -name "*.weights" > ai_models.txt find / -type f -name "*labels*.txt" > ai_model_labels.txt Some of the classes from the files; file_name: SCL_v0.3.1_9c7zcipfrc_558001-labels-v3.txt document_boarding_pass document_check_or_checkbook document_currency_or_bill document_driving_license document_office_badge document_passport document_receipt document_social_security_number hier_curation hier_document hier_negative curation_meme file_name: SceneNet5_detection_labels-v8d.txt CVML_UNKNOWN_999999 aircraft automobile bicycle bird bottle bus canine consumer_electronics feline fruit furniture headgear kite fish computer_monitor motorcycle musical_instrument document people food sign watersport train ungulates watercraft flower appliance sports_equipment tool