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| let featureValue = try MLFeatureValue(cgImage: image.cgImage!, constraint: imageConstraint, options: nil) |
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| let imageConstraint = model?.modelDescription.inputDescriptionsByName["image"]!.imageConstraint! |
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| let updateTask = try MLUpdateTask(forModelAt: updatableModelURL, trainingData: trainingData, configuration: model.configuration, completionHandler: { context in | |
| } | |
| updateTask.resume() |
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| private func loadModel(url: URL) -> MLModel? { | |
| do { | |
| let config = MLModelConfiguration() | |
| config.computeUnits = .all | |
| return try MLModel(contentsOf: url, configuration: config) | |
| } catch { | |
| print("Error loading model: \(error)") | |
| return nil | |
| } | |
| } |
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| func predict(image: UIImage) -> Animal? { | |
| let imageConstraint = model.modelDescription.inputDescriptionsByName["image"]!.imageConstraint! | |
| do{ | |
| let imageOptions: [MLFeatureValue.ImageOption: Any] = [ | |
| .cropAndScale: VNImageCropAndScaleOption.scaleFill.rawValue | |
| ] | |
| let featureValue = try MLFeatureValue(cgImage: image.cgImage!, constraint: imageConstraint, options: imageOptions) |
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| private func batchProvider() -> MLArrayBatchProvider | |
| { | |
| var batchInputs: [MLFeatureProvider] = [] | |
| let imageOptions: [MLFeatureValue.ImageOption: Any] = [ | |
| .cropAndScale: VNImageCropAndScaleOption.scaleFill.rawValue | |
| ] | |
| for (image,label) in imageLabelDictionary { | |
| do{ | |
| let featureValue = try MLFeatureValue(cgImage: image.cgImage!, constraint: imageConstraint, options: imageOptions) |
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| let fileManager = FileManager.default | |
| let documentDirectory = try fileManager.url(for: .documentDirectory, in: .userDomainMask, appropriateFor:nil, create:true) | |
| let modelURL = documentDirectory.appendingPathComponent("CatDog.mlmodelc") |
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| let config = UIImage.SymbolConfiguration(textStyle: .largeTitle) | |
| UIImage(systemName: "paperplane", withConfiguration : config) |
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