Is it possible to change the folder where .blob are stocked when we training a model ? I trying to train a model to track an object, and I'm limited to the extraordinary 256Gb of my 2024 Mac ! :(

In the WWDC24 What’s New In Create ML at 6:03 the presenter introduced TimeSeriesClassifier as a new component of Create ML Components. Where are documentation and code examples for this feature? My app captures accelerometer time series data that I want to classify. Thank you so much!

The What’s New in Create ML session in WWDC24 went into great depth with time-series forecasting models (beginning at: 15:14) and mentioned these new models, capabilities, and tools for iOS 18. So, far, all I can find is API documentation. I don’t see any other session in WWDC24 covering these new time-series forecasting Create ML features. Is there more substance/documentation on how to use these with Create ML? Maybe I am looking in the wrong place but I am fairly new with ML. Are there any food truck / donut shop demo/sample code like in the video? It is of great interest to get ahead of the curve on this within business applications that may take advantage of this with inventory / ordering data.

I'm training an activity classifier with CreateML and when I add samples to the Preview tab, the length of the sample it displays does not match its actual length. I have set prediction window size to 15 and sample rate to 10. The activity is roughly 1.5 seconds. When I put a 1.49 second sample into preview, it says it is 00:00.06 seconds: and when I put a 12.91 second sample into preview, it says it is 00:00.52 seconds: Here is the code I am using to print out sensor data in csv format: if motionManager.isDeviceMotionAvailable { motionManager.deviceMotionUpdateInterval = 0.1 motionManager.startDeviceMotionUpdates(to: .main) { data, error in guard let data = data, let startTime = self.startTime else { return } let timestamp = Date().timeIntervalSince(startTime) let xAcc = data.userAcceleration.x let yAcc = data.userAcceleration.y let zAcc = data.userAcceleration.z let xRotRate = data.rotationRate.x let yRotRate = data.rotationRate.y let zRotRate = data.rotationRate.z let roll = data.attitude.roll let pitch = data.attitude.pitch let yaw = data.attitude.yaw let row = "\(timestamp),\(xAcc),\(yAcc),\(zAcc),\(xRotRate),\(yRotRate),\(zRotRate),\(roll),\(pitch),\(yaw)" print(row) } } And here is the data for the 1.49 second sample mentioned above:

For example: we use DocKit for birdwatching, so we have an unknown field distance and direction. Distance = ? Direction = ? For example, the rock from which the observation is made. The task is to recognize the number of birds caught in the frame, add a detection frame and collect statistics. Question: What is the maximum number of frames processed with custom object recognition? If not enough, can I do the calculations myself and transfer to DokKit for fast movement?

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!

Where can I find CreateML logs? I'd like to inspect log lines if they exist to diagnose what kind of error the app encounters when I provide it training data for a multi-label image classifier and the UI displays "Data Analysis stopped". I do see some crash reports for "MLRecipeExecutionService" in the Console app which seem related, but I haven't spotted anything useful there yet.

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)

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.

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.

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?

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