Awesome

ImageClassification-CoreML

Requirements

• Xcode 9.2+
• iOS 11.0+, 11.2+, 12.0+
• Swift 4

Model

Model Size, Minimum iOS Version, Download Link

Infernece Time (ms)

Infernece Time (ms)

Total Time (ms)

FPS

Build & Run

1. Prerequisites

1.1 Import the Core ML model

Once you import the model, compiler generates model helper class on build path automatically. You can access the model through model helper class by creating an instance, not through build path.

1.2 Add permission in info.plist for device's camera access

2. Dependencies

No external library yet.

3. Code

3.1 Import Vision framework

import Vision

3.2 Define properties for Core ML

// MARK - Core ML model
typealias ClassificationModel = MobileNet
var coremlModel: ClassificationModel? = nil

// MARK: - Vision Properties
var request: VNCoreMLRequest?
var visionModel: VNCoreMLModel?

3.3 Configure and prepare the model

override func viewDidLoad() {
    super.viewDidLoad()

	if let visionModel = try? VNCoreMLModel(for: ClassificationModel().model) {
        self.visionModel = visionModel
        request = VNCoreMLRequest(model: visionModel, completionHandler: visionRequestDidComplete)
        request?.imageCropAndScaleOption = .scaleFill
    } else {
        fatalError()
    }
}

func visionRequestDidComplete(request: VNRequest, error: Error?) {
    /* ------------------------------------------------------ */
    /* something postprocessing what you want after inference */
    /* ------------------------------------------------------ */
}

3.4 Inference 🏃‍♂️

guard let request = request else { fatalError() }
let handler = VNImageRequestHandler(cvPixelBuffer: pixelBuffer)
try? handler.perform([request])