Toggle flash in ios swift - ios

Question

I am building an image clasifier app. On camera screen I have a switch button which I want to use to toggle flash so that user can switch on flash in low light.
Here is my code:
import UIKit
import AVFoundation
import Vision
// controlling the pace of the machine vision analysis
var lastAnalysis: TimeInterval = 0
var pace: TimeInterval = 0.33 // in seconds, classification will not repeat faster than this value
// performance tracking
let trackPerformance = false // use "true" for performance logging
var frameCount = 0
let framesPerSample = 10
var startDate = NSDate.timeIntervalSinceReferenceDate
var flash=0
class ImageDetectionViewController: UIViewController {
var callBackImageDetection :(State)->Void = { state in
}
#IBOutlet weak var previewView: UIView!
#IBOutlet weak var stackView: UIStackView!
#IBOutlet weak var lowerView: UIView!
#IBAction func swithch(_ sender: UISwitch) {
if(sender.isOn == true)
{
stopActiveSession();
let captureSession=AVCaptureSession()
let captureDevice: AVCaptureDevice?
setupCamera(flash: 1)
}
}
var previewLayer: AVCaptureVideoPreviewLayer!
let bubbleLayer = BubbleLayer(string: "")
let queue = DispatchQueue(label: "videoQueue")
var captureSession = AVCaptureSession()
var captureDevice: AVCaptureDevice?
let videoOutput = AVCaptureVideoDataOutput()
var unknownCounter = 0 // used to track how many unclassified images in a row
let confidence: Float = 0.8
// MARK: Load the Model
let targetImageSize = CGSize(width: 227, height: 227) // must match model data input
lazy var classificationRequest: [VNRequest] = {
do {
// Load the Custom Vision model.
// To add a new model, drag it to the Xcode project browser making sure that the "Target Membership" is checked.
// Then update the following line with the name of your new model.
// let model = try VNCoreMLModel(for: Fruit().model)
let model = try VNCoreMLModel(for: CodigocubeAI().model)
let classificationRequest = VNCoreMLRequest(model: model, completionHandler: self.handleClassification)
return [ classificationRequest ]
} catch {
fatalError("Can't load Vision ML model: \(error)")
}
}()
// MARK: Handle image classification results
func handleClassification(request: VNRequest, error: Error?) {
guard let observations = request.results as? [VNClassificationObservation]
else { fatalError("unexpected result type from VNCoreMLRequest") }
guard let best = observations.first else {
fatalError("classification didn't return any results")
}
// Use results to update user interface (includes basic filtering)
print("\(best.identifier): \(best.confidence)")
if best.identifier.starts(with: "Unknown") || best.confidence < confidence {
if self.unknownCounter < 3 { // a bit of a low-pass filter to avoid flickering
self.unknownCounter += 1
} else {
self.unknownCounter = 0
DispatchQueue.main.async {
self.bubbleLayer.string = nil
}
}
} else {
self.unknownCounter = 0
DispatchQueue.main.async {[weak self] in
guard let strongSelf = self
else
{
return
}
// Trimming labels because they sometimes have unexpected line endings which show up in the GUI
let identifierString = best.identifier.trimmingCharacters(in: CharacterSet.whitespacesAndNewlines)
strongSelf.bubbleLayer.string = identifierString
let state : State = strongSelf.getState(identifierStr: identifierString)
strongSelf.stopActiveSession()
strongSelf.navigationController?.popViewController(animated: true)
strongSelf.callBackImageDetection(state)
}
}
}
func getState(identifierStr:String)->State
{
var state :State = .none
if identifierStr == "entertainment"
{
state = .entertainment
}
else if identifierStr == "geography"
{
state = .geography
}
else if identifierStr == "history"
{
state = .history
}
else if identifierStr == "knowledge"
{
state = .education
}
else if identifierStr == "science"
{
state = .science
}
else if identifierStr == "sports"
{
state = .sports
}
else
{
state = .none
}
return state
}
// MARK: Lifecycle
override func viewDidLoad() {
super.viewDidLoad()
previewLayer = AVCaptureVideoPreviewLayer(session: captureSession)
previewView.layer.addSublayer(previewLayer)
}
override func viewDidAppear(_ animated: Bool) {
self.edgesForExtendedLayout = UIRectEdge.init(rawValue: 0)
bubbleLayer.opacity = 0.0
bubbleLayer.position.x = self.view.frame.width / 2.0
bubbleLayer.position.y = lowerView.frame.height / 2
lowerView.layer.addSublayer(bubbleLayer)
setupCamera(flash:2)
}
override func viewDidLayoutSubviews() {
super.viewDidLayoutSubviews()
previewLayer.frame = previewView.bounds;
}
// MARK: Camera handling
func setupCamera(flash :Int) {
let deviceDiscovery = AVCaptureDevice.DiscoverySession(deviceTypes: [.builtInWideAngleCamera], mediaType: .video, position: .back)
if let device = deviceDiscovery.devices.last {
if(flash == 1)
{
if (device.hasTorch) {
do {
try device.lockForConfiguration()
if (device.isTorchAvailable) {
do {
try device.setTorchModeOn(level:0.2 )
}
catch
{
print(error)
}
device.unlockForConfiguration()
}
}
catch
{
print(error)
}
}
}
captureDevice = device
beginSession()
}
}
func beginSession() {
do {
videoOutput.videoSettings = [((kCVPixelBufferPixelFormatTypeKey as NSString) as String) : (NSNumber(value: kCVPixelFormatType_32BGRA) as! UInt32)]
videoOutput.alwaysDiscardsLateVideoFrames = true
videoOutput.setSampleBufferDelegate(self, queue: queue)
captureSession.sessionPreset = .hd1920x1080
captureSession.addOutput(videoOutput)
let input = try AVCaptureDeviceInput(device: captureDevice!)
captureSession.addInput(input)
captureSession.startRunning()
} catch {
print("error connecting to capture device")
}
}
func stopActiveSession()
{
if captureSession.isRunning == true
{
captureSession.stopRunning()
}
}
override func viewWillDisappear(_ animated: Bool) {
self.stopActiveSession()
}
deinit {
print("deinit called")
}
}
// MARK: Video Data Delegate
extension ImageDetectionViewController: AVCaptureVideoDataOutputSampleBufferDelegate {
// called for each frame of video
func captureOutput(_ captureOutput: AVCaptureOutput, didOutput sampleBuffer: CMSampleBuffer, from connection: AVCaptureConnection) {
let currentDate = NSDate.timeIntervalSinceReferenceDate
// control the pace of the machine vision to protect battery life
if currentDate - lastAnalysis >= pace {
lastAnalysis = currentDate
} else {
return // don't run the classifier more often than we need
}
// keep track of performance and log the frame rate
if trackPerformance {
frameCount = frameCount + 1
if frameCount % framesPerSample == 0 {
let diff = currentDate - startDate
if (diff > 0) {
if pace > 0.0 {
print("WARNING: Frame rate of image classification is being limited by \"pace\" setting. Set to 0.0 for fastest possible rate.")
}
print("\(String.localizedStringWithFormat("%0.2f", (diff/Double(framesPerSample))))s per frame (average)")
}
startDate = currentDate
}
}
// Crop and resize the image data.
// Note, this uses a Core Image pipeline that could be appended with other pre-processing.
// If we don't want to do anything custom, we can remove this step and let the Vision framework handle
// crop and resize as long as we are careful to pass the orientation properly.
guard let croppedBuffer = croppedSampleBuffer(sampleBuffer, targetSize: targetImageSize) else {
return
}
do {
let classifierRequestHandler = VNImageRequestHandler(cvPixelBuffer: croppedBuffer, options: [:])
try classifierRequestHandler.perform(classificationRequest)
} catch {
print(error)
}
}
}
let context = CIContext()
var rotateTransform: CGAffineTransform?
var scaleTransform: CGAffineTransform?
var cropTransform: CGAffineTransform?
var resultBuffer: CVPixelBuffer?
func croppedSampleBuffer(_ sampleBuffer: CMSampleBuffer, targetSize: CGSize) -> CVPixelBuffer? {
guard let imageBuffer: CVImageBuffer = CMSampleBufferGetImageBuffer(sampleBuffer) else {
fatalError("Can't convert to CVImageBuffer.")
}
// Only doing these calculations once for efficiency.
// If the incoming images could change orientation or size during a session, this would need to be reset when that happens.
if rotateTransform == nil {
let imageSize = CVImageBufferGetEncodedSize(imageBuffer)
let rotatedSize = CGSize(width: imageSize.height, height: imageSize.width)
guard targetSize.width < rotatedSize.width, targetSize.height < rotatedSize.height else {
fatalError("Captured image is smaller than image size for model.")
}
let shorterSize = (rotatedSize.width < rotatedSize.height) ? rotatedSize.width : rotatedSize.height
rotateTransform = CGAffineTransform(translationX: imageSize.width / 2.0, y: imageSize.height / 2.0).rotated(by: -CGFloat.pi / 2.0).translatedBy(x: -imageSize.height / 2.0, y: -imageSize.width / 2.0)
let scale = targetSize.width / shorterSize
scaleTransform = CGAffineTransform(scaleX: scale, y: scale)
// Crop input image to output size
let xDiff = rotatedSize.width * scale - targetSize.width
let yDiff = rotatedSize.height * scale - targetSize.height
cropTransform = CGAffineTransform(translationX: xDiff/2.0, y: yDiff/2.0)
}
// Convert to CIImage because it is easier to manipulate
let ciImage = CIImage(cvImageBuffer: imageBuffer)
let rotated = ciImage.transformed(by: rotateTransform!)
let scaled = rotated.transformed(by: scaleTransform!)
let cropped = scaled.transformed(by: cropTransform!)
// Note that the above pipeline could be easily appended with other image manipulations.
// For example, to change the image contrast. It would be most efficient to handle all of
// the image manipulation in a single Core Image pipeline because it can be hardware optimized.
// Only need to create this buffer one time and then we can reuse it for every frame
if resultBuffer == nil {
let result = CVPixelBufferCreate(kCFAllocatorDefault, Int(targetSize.width), Int(targetSize.height), kCVPixelFormatType_32BGRA, nil, &resultBuffer)
guard result == kCVReturnSuccess else {
fatalError("Can't allocate pixel buffer.")
}
}
// Render the Core Image pipeline to the buffer
context.render(cropped, to: resultBuffer!)
// For debugging
// let image = imageBufferToUIImage(resultBuffer!)
// print(image.size) // set breakpoint to see image being provided to CoreML
return resultBuffer
}
// Only used for debugging.
// Turns an image buffer into a UIImage that is easier to display in the UI or debugger.
func imageBufferToUIImage(_ imageBuffer: CVImageBuffer) -> UIImage {
CVPixelBufferLockBaseAddress(imageBuffer, CVPixelBufferLockFlags(rawValue: 0))
let baseAddress = CVPixelBufferGetBaseAddress(imageBuffer)
let bytesPerRow = CVPixelBufferGetBytesPerRow(imageBuffer)
let width = CVPixelBufferGetWidth(imageBuffer)
let height = CVPixelBufferGetHeight(imageBuffer)
let colorSpace = CGColorSpaceCreateDeviceRGB()
let bitmapInfo = CGBitmapInfo(rawValue: CGImageAlphaInfo.noneSkipFirst.rawValue | CGBitmapInfo.byteOrder32Little.rawValue)
let context = CGContext(data: baseAddress, width: width, height: height, bitsPerComponent: 8, bytesPerRow: bytesPerRow, space: colorSpace, bitmapInfo: bitmapInfo.rawValue)
let quartzImage = context!.makeImage()
CVPixelBufferUnlockBaseAddress(imageBuffer, CVPixelBufferLockFlags(rawValue: 0))
let image = UIImage(cgImage: quartzImage!, scale: 1.0, orientation: .right)
return image
}
I am getting error An AVCaptureOutput instance may not be added to more than one session'
Now I want to give user the facility to toggle flash. How to destroy active camera session and open new with flash on?
Can anyone help me also any other way to achieve this?