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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.
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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
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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?
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I am working on the neural network classifier provided on the coremltools.readme.io in the updatable->neural network section(https://coremltools.readme.io/docs/updatable-neural-network-classifier-on-mnist-dataset).
I am using the same code but I get an error saying that the coremltools.converters.keras.convert does not exist. But this I know can be coreml version issue. Right know I am using coremltools version 6.2. I converted this model to mlmodel with .convert only. It got converted successfully.
But I face an error in the make_updatable function saying the loss layer must be softmax output. Even the coremlt package API reference there I found its because the layer name is softmaxND but it should be softmax.
Now the problem is when I convert the model from Keras sequential model to coreml model. the layer name and type change. And the softmax changes to softmaxND.
Does anyone faced this issue?
if I execute this builder.inspect_layers(last=4)
I get this output
[Id: 32], Name: sequential/dense_1/Softmax (Type: softmaxND)
Updatable: False
Input blobs: ['sequential/dense_1/MatMul']
Output blobs: ['Identity']
[Id: 31], Name: sequential/dense_1/MatMul (Type: batchedMatmul)
Updatable: False
Input blobs: ['sequential/dense/Relu']
Output blobs: ['sequential/dense_1/MatMul']
[Id: 30], Name: sequential/dense/Relu (Type: activation)
Updatable: False
Input blobs: ['sequential/dense/MatMul']
Output blobs: ['sequential/dense/Relu']
In the make_updatable function when I execute
builder.set_categorical_cross_entropy_loss(name='lossLayer', input='Identity')
I get this error
ValueError: Categorical Cross Entropy loss layer input (Identity) must be a softmax layer output.
