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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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CoreML-Models
Largest list of models for Core ML (for iOS 11+) -
Bender
Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood. -
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, Support Vector Machines, Neural Networks, PCA, K-Means, Genetic Algorithms -
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
Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift - from watchOS to Linux -
Serrano
A Swift deep learning library with Accelerate and Metal support. -
Revolver
A framework for building fast genetic algorithms in Swift. -
Tensorflow-iOS
The official Google-built powerful neural network library port for iOS.
Appwrite - The open-source backend cloud platform
The open-source backend cloud platform for developing Web, Mobile, and Flutter applications. You can set up your backend faster with real-time APIs for authentication, databases, file storage, cloud functions, and much more!
Promo
appwrite.io
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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)
}