Python is an interpreted, high-level and general-purpose programming language. Python was created in the late 1980s, and first released in 1991, by Guido van Rossum as a successor to the ABC programming language. Mainly Python used for machine learning in data science.
Apple doesn’t support Python directly. TensorFlow provides a next-generation platform for machine learning. TensorFlow provides the framework to Implement interpreted python in ios both Swift & Objective-C. Please visit the TensorFlow website to know more about this framework.
In this blog, I will show you how can match 2 faces using python. To implement this we need a .tflite file where we have already implement python code and compressed it. I will share my blog to create .tflite from TensorFlow.Â
Let’s Start
Swift version: 5.2
iOS version: 14
Xcode: 12.0
First Create a project from Xcode.
File ▸ New ▸ Project…. Choose the iOS ▸ Application ▸ Single View App template and create a new project.
Second, add TensorFlowLiteSwift to your project.
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 pod 'TensorFlowLiteSwift' |
Add MobileFace.tflite in your project. This file I will share below.
Now create a class with the name MobileFace.
import TensorFlowLite in this class.
Now add some variable which is used in our class.
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private var interpreter: Interpreter? private var fileName = "MobileFace" private var fileType = "tflite" private var imageWidth = 128 private var imageHeight = 128 private var size = 192 |
Now initialize the Interpreter object.
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init() { guard let pPath = Bundle.main.path( forResource: fileName, ofType: fileType) else { return } var options = Interpreter.Options() options.threadCount = 4 interpreter = try? Interpreter(modelPath: path, options: options) try? interpreter?.allocateTensors() } |
Add compare method inside our class. Here we will compare 2 images and return compare result.
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func compare(_ image1: UIImage, with image2: UIImage) -> Float { let size = CGSize(width: image_width, height: image_height) let image1 = scaleImage(image: image1, toSize: size) let image2 = scaleImage(image: image2, toSize: size) guard let data = self.data(withProcess: image1, image2: image2) else { return 0 } try? interpreter?.input(at: 0) try? interpreter?.copy(data, toInputAt: 0) try? interpreter?.invoke() var outputTensor = try? interpreter?.output(at: 0) var outputData = try outputTensor?.data as? NSData var output = Array(count: 2 * embeddings_size, elementCreator: Float(0.0)) outputData?.getBytes(&output, length: MemoryLayout<Float>.size * 2 * embeddings_size) Normalize(&output, epsilon: 1e-10) let result = evaluate(&output) return result } |
Now Implement scaleImage method in the class.
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func scaleImage(image : UIImage, toSize:CGSize)->UIImage{ UIGraphicsBeginImageContext(toSize) image.draw(in: CGRect(x:0, y:0, width:toSize.width, height:toSize.height)) let scaledImage = UIGraphicsGetImageFromCurrentImageContext() UIGraphicsEndImageContext() return scaledImage! } |
Now Normalize and evaluate our result.
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func Normalize(_ embeddings: UnsafeMutablePointer<Float>, epsilon: Float) { for i in 0..<2 { var square_sum: Float = 0 for j in 0..<embeddings_size { square_sum += pow(embeddings[i * embeddings_size + j], 2) } let x_inv_norm = sqrt(max(square_sum, epsilon)) for j in 0..<embeddings_size { embeddings[i * embeddings_size + j] = Float(embeddings[i * embeddings_size + j] ) / x_inv_norm } } } func evaluate(_ embeddings: UnsafeMutablePointer<Float>?) -> Float { var dist: Float = 0 for i in 0..<embeddings_size { if let embedding = embeddings?[i], let embedding1 = embeddings?[i + embeddings_size] { dist += pow(embedding - embedding1, 2) } } var same: Float = 0 for i in 0..<400 { let threshold: Float = Float(0.01 * Double((i + 1))) if dist < threshold { same += 1.0 / 400 } } return same } |
This code is enough to compare to face. Now call this compare method.
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let compare = obj.compare(UIImage(named: "image2")!, with: UIImage(named: "image3")!) |
Output:
Conclusion:
We can easily implement Python using swift and it quite easy.
Next blog I will image face detection, crop, and compare using python in swift.
I hope this code will help you better to understand the implementation of Python using swift. If you feel any doubt or query please comment below.
Thank you.
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