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Programming language: Jupyter Notebook
License: MIT License
Tags:
Machine Learning
CoreML-samples alternatives and similar libraries
Based on the "Machine Learning" category.
Alternatively, view CoreML-samples alternatives based on common mentions on social networks and blogs.
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Awesome-Mobile-Machine-Learning
A curated list of awesome mobile machine learning resources for iOS, Android, and edge devices. -
AIToolbox
A toolbox of AI modules written in Swift: Graphs/Trees, Linear Regression, Support Vector Machines, Neural Networks, PCA, KMeans, Genetic Algorithms, MDP, Mixture of Gaussians. -
Swift-Brain
Artificial Intelligence/Machine Learning data structures and Swift algorithms for future iOS development. Bayes theorem, Neural Networks, and more AI. -
TensorSwift
A lightweight library to calculate tensors in Swift, which has similar APIs to TensorFlow's. -
SwiftCoreMLTools
A Swift library for creating and exporting CoreML Models in Swift. -
DL4S
Deep Learning for Swift: Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift. -
Revolver
A framework for building fast genetic algorithms in Swift. Comes with modular architecture, pre-implemented operators and loads of examples. -
Tensorflow-iOS
The official Google-built powerful neural network library port for iOS.
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* Code Quality Rankings and insights are calculated and provided by Lumnify.
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Do you think we are missing an alternative of CoreML-samples or a related project?
README
CoreML-samples
This is the sample code for Core ML using ResNet50 provided by Apple.
ResNet50 can categorize the input image to 1000 pre-trained categories.
What's more, this includes a sample code for coremltools converting keras model to mlmodel.
Source Code for the prediction
guard let image = imageView.image, let ref = image.buffer() else {
return
}
do {
// predict
let output = try model.prediction(image: ref)
print(output.classLabel)
print(output.classLabelProbs)
} catch {
print(error)
}