Use Core ML Library in swift 3 (for iOS 11)

Core ML

Core ML provide the Various facility which is based on Machine learning , Here We are implementing related to Image , with the help of this we can search the image name or can get the name of product.

Here is Link:

https://developer.apple.com/machine-learning/

For configuring in App , here we are taking the example of camera and after taking the image CoreML will provide the prediction name of image.

1: Take the permission in info.plist

To access your camera and photo library, there is still one last thing you must do. Go to your Info.plist and two entries: Privacy – Camera Usage Description and Privacy – Photo Library Usage Description. Starting from iOS 10, you will need to specify the reason why your app needs to access the camera and photo library.

2: Now go to this Sites:

https://developer.apple.com/machine-learning/

and Download “Inception v3” Model

3: Now drag and copy to target folder.

4: let’s add the model in our code. Go back to ViewController.swift. First, import the CoreML framework at the very beginning:

var model: Inceptionv3!
 
override func viewWillAppear(_ animated: Bool) {
    model = Inceptionv3()
}

var model: Inceptionv3!

override func viewWillAppear(_ animated: Bool) {

model = Inceptionv3()

}

5: Now create outlet of Image View and label where we show the messages:

    @IBOutlet weak var imageView: UIImageView!
    @IBOutlet weak var classifier: UILabel!

1 2	@IBOutlet weak var imageView: UIImageView! @IBOutlet weak var classifier: UILabel!

6: Now on click the button:

 @IBAction func camera(_ sender: Any) {
        
        if !UIImagePickerController.isSourceTypeAvailable(.camera) {
            return
        }
        
        let cameraPicker = UIImagePickerController()
        cameraPicker.delegate = self
        cameraPicker.sourceType = .camera
        cameraPicker.allowsEditing = false
        
        present(cameraPicker, animated: true)
    }

@IBAction func camera(_ sender: Any) {

if !UIImagePickerController.isSourceTypeAvailable(.camera) {

return

}

let cameraPicker = UIImagePickerController()

cameraPicker.delegate = self

cameraPicker.sourceType = .camera

cameraPicker.allowsEditing = false

present(cameraPicker, animated: true)

}

7: On Select Image there delegate method will call:

extension ViewController: UIImagePickerControllerDelegate {
    func imagePickerControllerDidCancel(_ picker: UIImagePickerController) {
        dismiss(animated: true, completion: nil)
    }
    
    func imagePickerController(_ picker: UIImagePickerController, didFinishPickingMediaWithInfo info: [String : Any]) {
        
        picker.dismiss(animated: true)
        classifier.text = "Analyzing Image..."
        guard let image = info["UIImagePickerControllerOriginalImage"] as? UIImage else {
            return
        } //1
        
        UIGraphicsBeginImageContextWithOptions(CGSize(width: 299, height: 299), true, 2.0)
        image.draw(in: CGRect(x: 0, y: 0, width: 299, height: 299))
        let newImage = UIGraphicsGetImageFromCurrentImageContext()!
        UIGraphicsEndImageContext()
        
        let attrs = [kCVPixelBufferCGImageCompatibilityKey: kCFBooleanTrue, kCVPixelBufferCGBitmapContextCompatibilityKey: kCFBooleanTrue] as CFDictionary
        var pixelBuffer : CVPixelBuffer?
        let status = CVPixelBufferCreate(kCFAllocatorDefault, Int(newImage.size.width), Int(newImage.size.height), kCVPixelFormatType_32ARGB, attrs, &pixelBuffer)
        guard (status == kCVReturnSuccess) else {
            return
        }
        
        CVPixelBufferLockBaseAddress(pixelBuffer!, CVPixelBufferLockFlags(rawValue: 0))
        let pixelData = CVPixelBufferGetBaseAddress(pixelBuffer!)
        
        let rgbColorSpace = CGColorSpaceCreateDeviceRGB()
        let context = CGContext(data: pixelData, width: Int(newImage.size.width), height: Int(newImage.size.height), bitsPerComponent: 8, bytesPerRow: CVPixelBufferGetBytesPerRow(pixelBuffer!), space: rgbColorSpace, bitmapInfo: CGImageAlphaInfo.noneSkipFirst.rawValue) //3
        
        context?.translateBy(x: 0, y: newImage.size.height)
        context?.scaleBy(x: 1.0, y: -1.0)
        
        UIGraphicsPushContext(context!)
        newImage.draw(in: CGRect(x: 0, y: 0, width: newImage.size.width, height: newImage.size.height))
        UIGraphicsPopContext()
        CVPixelBufferUnlockBaseAddress(pixelBuffer!, CVPixelBufferLockFlags(rawValue: 0))
        imageView.image = newImage
        
        // Core ML
        guard let prediction = try? model.prediction(image: pixelBuffer!) else {
            return
        }
        
        classifier.text = "I think this is a \(prediction.classLabel)."
        
        
    }
}

extension ViewController: UIImagePickerControllerDelegate {

func imagePickerControllerDidCancel(_ picker: UIImagePickerController) {

dismiss(animated: true, completion: nil)

}

func imagePickerController(_ picker: UIImagePickerController, didFinishPickingMediaWithInfo info: [String : Any]) {

picker.dismiss(animated: true)

classifier.text = "Analyzing Image..."

guard let image = info["UIImagePickerControllerOriginalImage"] as? UIImage else {

return

} //1

UIGraphicsBeginImageContextWithOptions(CGSize(width: 299, height: 299), true, 2.0)

image.draw(in: CGRect(x: 0, y: 0, width: 299, height: 299))

let newImage = UIGraphicsGetImageFromCurrentImageContext()!

UIGraphicsEndImageContext()

let attrs = [kCVPixelBufferCGImageCompatibilityKey: kCFBooleanTrue, kCVPixelBufferCGBitmapContextCompatibilityKey: kCFBooleanTrue] as CFDictionary

var pixelBuffer : CVPixelBuffer?

let status = CVPixelBufferCreate(kCFAllocatorDefault, Int(newImage.size.width), Int(newImage.size.height), kCVPixelFormatType_32ARGB, attrs, &pixelBuffer)

guard (status == kCVReturnSuccess) else {

return

}

CVPixelBufferLockBaseAddress(pixelBuffer!, CVPixelBufferLockFlags(rawValue: 0))

let pixelData = CVPixelBufferGetBaseAddress(pixelBuffer!)

let rgbColorSpace = CGColorSpaceCreateDeviceRGB()

let context = CGContext(data: pixelData, width: Int(newImage.size.width), height: Int(newImage.size.height), bitsPerComponent: 8, bytesPerRow: CVPixelBufferGetBytesPerRow(pixelBuffer!), space: rgbColorSpace, bitmapInfo: CGImageAlphaInfo.noneSkipFirst.rawValue) //3

context?.translateBy(x: 0, y: newImage.size.height)

context?.scaleBy(x: 1.0, y: -1.0)

UIGraphicsPushContext(context!)

newImage.draw(in: CGRect(x: 0, y: 0, width: newImage.size.width, height: newImage.size.height))

UIGraphicsPopContext()

CVPixelBufferUnlockBaseAddress(pixelBuffer!, CVPixelBufferLockFlags(rawValue: 0))

imageView.image = newImage

// Core ML

guard let prediction = try? model.prediction(image: pixelBuffer!) else {

return

}

classifier.text = "I think this is a \(prediction.classLabel)."

}

8: Here “prediction.classLabel” this will return the prediction name of image.

kunal prasad 26 October 2021

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Use Core ML Library in swift 3 (for iOS 11)

Core ML

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