iOS On-Device Machine Learning Rehberi

1import CoreML
2 
3// Core ML model yukleme ve tahmin
4class MLPredictor {
5    private var model: MLModel?
6 
7    init() {
8        // Model yukleme - lazy initialization
9        do {
10            let config = MLModelConfiguration()
11            config.computeUnits = .all // CPU + GPU + Neural Engine
12            self.model = try ImageClassifier(configuration: config).model
13        } catch {
14            print("Model yuklenemedi: \(error.localizedDescription)")
15        }
16    }
17 
18    func predict(image: CVPixelBuffer) async throws -> String {
19        guard let model = model else {
20            throw MLError.modelNotLoaded
21        }
22 
23        let input = try MLDictionaryFeatureProvider(
24            dictionary: ["image": MLFeatureValue(pixelBuffer: image)]
25        )
26 
27        let output = try await model.prediction(from: input)
28 
29        guard let result = output.featureValue(for: "classLabel")?.stringValue else {
30            throw MLError.predictionFailed
31        }
32 
33        return result
34    }
35}
36 
37enum MLError: Error {
38    case modelNotLoaded
39    case predictionFailed
40}

1let config = MLModelConfiguration()
2 
3// Sadece CPU - en yavas, en uyumlu
4config.computeUnits = .cpuOnly
5 
6// CPU + GPU - iyi performans
7config.computeUnits = .cpuAndGPU
8 
9// CPU + GPU + Neural Engine - en hizli (varsayilan)
10config.computeUnits = .all

1// Swift'te model bilgilerini okuma
2import CoreML
3 
4func inspectModel() throws {
5    let modelURL = Bundle.main.url(forResource: "MyModel", withExtension: "mlmodelc")!
6    let model = try MLModel(contentsOf: modelURL)
7 
8    let description = model.modelDescription
9 
10    // Input bilgileri
11    for (name, feature) in description.inputDescriptionsByName {
12        print("Input: \(name), Type: \(feature.type.rawValue)")
13    }
14 
15    // Output bilgileri
16    for (name, feature) in description.outputDescriptionsByName {
17        print("Output: \(name), Type: \(feature.type.rawValue)")
18    }
19 
20    // Metadata
21    if let metadata = description.metadata[.description] as? String {
22        print("Aciklama: \(metadata)")
23    }
24}

1import SwiftUI
2import CoreML
3import Vision
4 
5struct ImageClassifierView: View {
6    @State private var classificationResult = "Henuz siniflandirilmadi"
7    @State private var confidence: Double = 0.0
8    @State private var selectedImage: UIImage?
9    @State private var isProcessing = false
10 
11    var body: some View {
12        VStack(spacing: 20) {
13            if let image = selectedImage {
14                Image(uiImage: image)
15                    .resizable()
16                    .scaledToFit()
17                    .frame(height: 300)
18                    .cornerRadius(12)
19            }
20 
21            if isProcessing {
22                ProgressView("Analiz ediliyor...")
23            } else {
24                Text(classificationResult)
25                    .font(.title2)
26                    .fontWeight(.bold)
27 
28                if confidence > 0 {
29                    Text("Guven: %\(Int(confidence * 100))")
30                        .foregroundColor(.secondary)
31                }
32            }
33 
34            Button("Fotograf Sec") {
35                // PhotoPicker acilir
36            }
37            .buttonStyle(.borderedProminent)
38        }
39        .padding()
40    }
41 
42    func classifyImage(_ image: UIImage) async {
43        isProcessing = true
44        defer { isProcessing = false }
45 
46        guard let ciImage = CIImage(image: image) else { return }
47 
48        do {
49            let config = MLModelConfiguration()
50            config.computeUnits = .all
51            let classifier = try MobileNetV2(configuration: config)
52 
53            let handler = VNImageRequestHandler(ciImage: ciImage)
54            let request = VNCoreMLRequest(model: try VNCoreMLModel(for: classifier.model))
55 
56            try handler.perform([request])
57 
58            if let results = request.results as? [VNClassificationObservation],
59               let topResult = results.first {
60                classificationResult = topResult.identifier
61                confidence = Double(topResult.confidence)
62            }
63        } catch {
64            classificationResult = "Hata: \(error.localizedDescription)"
65        }
66    }
67}