| import CoreML |
| import Foundation |
| import ImageIO |
|
|
| guard CommandLine.arguments.count == 3 else { |
| fatalError("Usage: encode model.mlpackage image.jpg (image must already be 448×448 RGB)") |
| } |
| let package = URL(fileURLWithPath: CommandLine.arguments[1]) |
| let imageURL = URL(fileURLWithPath: CommandLine.arguments[2]) |
| let compiled = try MLModel.compileModel(at: package) |
| let configuration = MLModelConfiguration() |
| configuration.computeUnits = .all |
| let model = try MLModel(contentsOf: compiled, configuration: configuration) |
| guard let source = CGImageSourceCreateWithURL(imageURL as CFURL, nil), |
| let image = CGImageSourceCreateImageAtIndex(source, 0, nil), |
| let constraint = model.modelDescription.inputDescriptionsByName["image"]?.imageConstraint, |
| image.width == constraint.pixelsWide, image.height == constraint.pixelsHigh else { |
| fatalError("Provide an orientation-corrected RGB image resized to the model's input dimensions") |
| } |
| let input = try MLFeatureValue(cgImage: image, constraint: constraint, options: nil) |
| let output = try model.prediction(from: MLDictionaryFeatureProvider(dictionary: ["image": input])) |
| guard let array = output.featureValue(for: "embedding")?.multiArrayValue, |
| array.count == 768, array.dataType == .float32 else { |
| fatalError("Unexpected model output") |
| } |
| let vector = Array(UnsafeBufferPointer(start: array.dataPointer.assumingMemoryBound(to: Float.self), count: array.count)) |
| print("\(vector.count) values, L2 norm \(sqrt(vector.reduce(0) { $0 + $1 * $1 }))") |
|
|
