Hi! I'd like to ask why after training an action classifier model using CreateML, I consistently fail to detect my wrist joint while using the live preview feature, while other joints are detected correctly. What could be causing this result? Thank you to anyone for providing answers. Training Data Sources: YouTube videos, searching keyword: "20min workout at home" All videos display the full body. Training Data Quantity: Model 1: Target action: 1 video / Irrelevant action: 1 video Model 2: Target action: 6 videos / Irrelevant action: 40 videos Both Model 1 and Model 2 fail to detect the wrist joint during live preview.

Following this guide https://developer.apple.com/documentation/CreateML/creating-a-multi-label-image-classifier Has anyone been able to export a CoreML model, specifically according to the documentation below? Since there isn't any runnable examples, just snippets, perhaps documentation error? If anyone is already familiar with these pipeline generics, is there something that jumps out about the example transformer used that fails conformance or just factually incorrect? Export the model to use with Vision After you train the model, you can export it as a Core ML model. // Export to Core ML let modelURL = URL(filePath: "/path/to/model") try model.export(to: modelURL)

Hello everyone, I am new to using Create ML, but am running up against a problem where the error is not descriptive, and I can not figure out what might be causing it. I am fairly sure my data is formatted properly, as in the CreateML software, it detects the images and shows me a bar graph of how many images belong to each label. But when it comes to actually training, the moment I press the "Train" button, it shows an error with the message: "Unexpected Error". I have also attempted to create and train the model programmatically, and that actually works! The framework requires that the JSON be named "annotations.json" instead of "annotation.json" and that the key representing the name of image be changed to "filename" from "image", but other than that, the data is the same. I tried to use the software with the changes I made to the JSON for use in the framework, but if I try that, it won't even parse the data, so I am fairly sure that my data is formatted correctly. I would prefer to use the app rather than do everything programmatically, because it presents the data in a much more digestible way. Has anyone else come up against this issue or a similar issue. I should note that I am running the latest Beta of MacOS Sonoma and Xcode.

hey if i wanted to create an app that takes screenshots from an apple device (and any app within) to give context to an ai so the ai can then respond. Then the app parses the response then executes commands on behalf of the ai/user, how would I do so with the rule that "screenshots/captures are not allowed within other apps"? Want to stay within bounds of the rules in place. Possibilities: Ai assistant, Ai pals, passive automation

Hey all, we are currently training a Hand Pose model with the current release of CreateML, and during the feature extraction phase, we get the following error: Assertion failed: (/AppleInternal/Library/BuildRoots/d9889869-120b-11ee-b796-7a03568b17ac/Library/Caches/com.apple.xbs/Sources/TuriCore/turicreate_oss/src/core/storage/DataTable_data/DataColumn_v2_block_manager.cpp:105): seg->blocks.size()>column_id [0 > 0] We have tried to search this online and mitigate the issue, but we are getting nowhere - has anyone else experienced this issue?

Hey, Are there any limits to the windowDuration property of the AudioFeaturePrint transformer such as the minimum value or maximum value? If we create a model with the Create ML UI App, upon selecting the AudioFeaturePrint as the feature extractor, we cannot go below 0.5 seconds for the window duration. Is the limit same if we programmatically create a model using the AudioFeaturePrint?

Is it possible to create an updatable sound classifier model which uses Apple's built in MLSoundClassifier available via Create ML that can be trained/personalized on device using Core ML? I tried to look up in quite a few places for a long while, however, I know that when on-device training was initially announced in 2019, updatable models were only restricted to non built-in classifiers, but any additional information that may have come out after 2019 in this regard has been hard to find.

Hello, I am a student and I am doing a search for my thesis on create ML and shape recognition and image processing, so for this subject I want to find the details of the steps used in create ML for this, such as the techniques used for pre-processing, and the methods of extracting characteristics, and the filters applied, ect...

Hello, I am reaching out for some assistance regarding integrating a CoreML action classifier into a SwiftUI app. Specifically, I am trying to implement this classifier to work with the live camera of the device. I have been doing some research, but unfortunately, I have not been able to find any relevant information on this topic. I was wondering if you could provide me with any examples, resources, or information that could help me achieve this integration? Any guidance you can offer would be greatly appreciated. Thank you in advance for your help and support.

does anyone know if the CreateML app has a way to build Support Vector Machine models for tabular regression? I see only the attached options. xcode14.2

Hi everyone! I’m trying to train an activity classification model with 3 classes. The problem is that only one class has precision and recall > 0 after training. Even with 2 classes result is the same First I’d thought that there is a problem with my data but when I switched “left” label to “right” and vice versa the results were the same: only “left”-labeled data get non-zero precision and recall.

Is it possible to use import CreateML on an iOS project? I'm looking at the code form the "Build dynamic iOS apps with the Create ML framework" video from this link https://developer.apple.com/videos/play/wwdc2021/10037/, but I'm not sure what kind of project I need to create. If I created an iOS project and tried running the code, what inputs would I need?

Im on the recent version of MacOs and I recently trained a Style Transfer model using CreateML. I used the preview tab of CreateML to preview my model with a video (as well as an image), however when I press the button to export or share the result from the neural network none are exported. The modal window appears but doesnt save after the progress bar shows up for the conversion I tried converting the CoreML model file into a CoreML package, however when I tried exporting the preview it crashed and switched tabs to the package information section. I've been having this issue with all three export buttons on the model preview section of both the CreateML application and Xcode. Is this happening to anyone else? Ive also tried using the coremltools package for Python to extract a preview, however documentation for Style Transfer networks doesnt exist for loading videos with that package. The style transfer network only takes an input of images, so its unclear where a video file can be loaded.

What tools are folks using to create the json file needed to train a custom word tagger model? I've tried Doccano, but it exports JSONL which is very different than what CreateML is expecting. (example of the required format here: https://developer.apple.com/documentation/naturallanguage/creating_a_word_tagger_model). Are there standard tools or utilities that export/convert to the CreateML format? Thanks.

Hi everyone, I'm having trouble running a CoreML model in the new Swift Playground app. I trained and exported the model from CreateML, saved it as a .mlmodel file, and then dragged it into the Xcode project of my playground. However, the model class wasn't generated automatically, so I put the model in a different project and copied the class over. Despite this, the model still doesn't run - Xcode can't find the compiled source (mlmodelc). To try and fix this, I compiled the model in another project and then dragged the mlmodelc folder over to the playground project. However, Xcode still couldn't build, saying that there was no available target. I'm not sure what to do next - the model works fine in another normal Xcode project. Any help or advice would be greatly appreciated! Let me know if you need more information. Thanks in advance!

I am working on a project that involves tabular classification using Create ML Components and I'm having trouble getting my model to work correctly. I've been following the official documentation here: https://developer.apple.com/documentation/createmlcomponents/ and also i have followed the wwdc talks. This one seems to be the most relevant one: https://developer.apple.com/wwdc22/10019 In that talk the construction of a tabular regressor is explained(20:23 Tabular regressor) . I tried using BoostedTreeClassifier similar to that. I am having trouble getting it to work though. While training with 5 featureColumns and one annotation columns appears to have worked. i am unsure how to get the label (the categorical value that the model is supposed to return) after calling .predict . This is the last bit of the example from apple (tabular regression) static func predict( type: String, region: String, volume: Double ) async throws -> Double { let model = try task.read(from: parametersURL) let dataFrame: DataFrame = [ "type": [type], "region": [region], "volume": [volume] ] let result = try await model(dataFrame) return result[priceColumnID][0]! } The last line is what i am wondering how to write for a Tabular classifier. It should return a category in my case. Is there a tutorial or example for a tabular classifier code somewhere?

Hello, I have created a data model with Text Classification which contains many garments with the label clothing, technology equipment with the label technology, etc.... . I have inserted it so that when entering for example "T-shirt" the label clothing is output. But I want it so that when I create an equipment category with the clothing, that it suggests me clothing items, which I add. How do I implement this. In the function you can only use"preditction.label". I program with SwiftUI. func textml() {         do {             let model = try DataModel_Symbols_Consilia(configuration: .init())             let prediction = try model.prediction(text: addProjectVM.title)             addProjectVM.symbol = prediction.label         } catch {             modelOutput = "Something went wrong"         }     } Greetings Janik

Hello Everyone, I am trying to train a hand pose classifier. But I stumble upon the problem where if I give training data above certain number (i.e. ~4000 images). Is it a limit imposed by Apple? because I even tried to reduce the size of images and even dimensions but it always gives me error while training whenever I give training data above certain number. Has anyone else stumbled upon this problem?if so, is there any work around for any number of data can be given to CreateML? Thanks

hello, When I used xcode to generate the model encryption key, an error was reported, the error was 'Failed to Generate Encryption Key and Sign in with you Apple ID in the Apple ID pane in System Preferences and retry '.But I have logged in my apple id in the system preferences, and this error still occurs.I reinstalled xcode and re-logged in to my apple id. This error still exists. Xcode Version 12.4 macOS Catalina 10.15.7 thanks

Consider if I'm having this Photo For ML how would i calculate these Measurements like the below image how would it be possible to calculate these measurement for the json file? via direct or indirect methods any suggestion?