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func predictImageUIGraphics(image: UIImage) {
let (pixelBuffer, _) = image.pixelBuffer()
guard let pixels = pixelBuffer else {
self.resetOnError()
return
}
self.lblGender?.text = analyzing
//
// CoreMLExtension.swift
// GenderAge
//
// Created by Daniele on 12/09/17.
// Copyright © 2017 nexor. All rights reserved.
//
import UIKit
import CoreML
//MARK: - UIImagePickerControllerDelegate
func imagePickerControllerDidCancel(_ picker: UIImagePickerController) {
picker.dismiss(animated: true, completion: nil)
}
func imagePickerController(_ picker: UIImagePickerController, didFinishPickingMediaWithInfo info: [String : Any]) {
picker.dismiss(animated: true, completion: nil)
guard let image = info["UIImagePickerControllerOriginalImage"] as? UIImage else {
import UIKit
import CoreML
import Vision
class ViewController: UIViewController, UINavigationControllerDelegate, UIImagePickerControllerDelegate {
@IBAction func camera(_ sender: Any) {
let cameraPicker = UIImagePickerController()
cameraPicker.delegate = self
if cameraMode {
cameraPicker.sourceType = .camera
cameraPicker.allowsEditing = true
cameraPicker.cameraCaptureMode = .photo
cameraPicker.cameraDevice = .rear
cameraPicker.showsCameraControls = true
import coremltools
coreml_modelGender = coremltools.converters.caffe.convert(('gender_net.caffemodel', 'deploy_gender.prototxt', 'mean.binaryproto'), image_input_names='data')
coreml_modelGender.save('Gender.mlmodel')
coreml_modelAge = coremltools.converters.caffe.convert(('age_net.caffemodel', 'deploy_age.prototxt', 'mean.binaryproto'), image_input_names='data')
coreml_modelAge.save('Age.mlmodel')
import coremltools
#https://apple.github.io/coremltools/generated/coremltools.converters.caffe.convert.html
coreml_modelAge = coremltools.converters.caffe.convert(('age_net.caffemodel', 'deploy_age.prototxt', 'mean.binaryproto'), image_input_names='data')
coreml_modelAge.save('Age.mlmodel')
coreml_modelGender = coremltools.converters.caffe.convert(('gender_net.caffemodel', 'deploy_gender.prototxt', 'mean.binaryproto'), image_input_names='data')
coreml_modelGender.save('Gender.mlmodel')