memory issue: realtime eye localization - swift

Question

I'm currently working on a iOS-application, which should be able to detect the localization. I've created an tflite which comprises some CNN layers. In order to use the tflite in XCode/Swift I've created a helper class in which the tflite calculates the output. Whenever I run the predict-function once, it works. But apparently the predict function doesn't work in real-time camera-thread.
After about 7 seconds, XCode is throwing the following error:
Thread 1: EXC_BAD_ACCESS (code=1, address=0x123424001). This error must be evoken by looping through the image. Since I need each pixel value I'm using the solution suggested by Firebase.But apparently this solution is not waterproofed. Can anybody help to resolve this memory issue?
func creatInputForCNN(resizedImage: UIImage?) -> Data{
// In this section of the code I loop through the image (150,200,3)
// in order to fetch each pixel value (RGB).
let image: CGImage = resizedImage.cgImage!
guard let context = CGContext(
data: nil,
width: image.width, height: image.height,
bitsPerComponent: 8, bytesPerRow: image.width * 4,
space: CGColorSpaceCreateDeviceRGB(),
bitmapInfo: CGImageAlphaInfo.noneSkipFirst.rawValue
) else {return nil}
context.draw(image, in: CGRect(x: 0, y: 0, width: image.width, height: image.height))
guard let imageData = context.data else {return nil}
let size_w = 150
let size_H = 200
var inputData:Data?
inputData = Data()
for row in 0 ..< size_H{
for col in 0 ..< size_w {
let offset = 4 * (row * context.width + col)
// (Ignore offset 0, the unused alpha channel)
let red = imageData.load(fromByteOffset: offset+1, as: UInt8.self)
let green = imageData.load(fromByteOffset: offset+2, as: UInt8.self)
let blue = imageData.load(fromByteOffset: offset+3, as: UInt8.self)
// Normalize channel values to [0.0, 1.0]. This requirement varies
// by model. For example, some models might require values to be
// normalized to the range [-1.0, 1.0] instead, and others might
// require fixed-point values or the original bytes.
var normalizedRed:Float32 = Float32(red) / 255
var normalizedGreen:Float32 = (Float32(green) / 255
var normalizedBlue:Float32 = Float32(blue) / 255
// Append normalized values to Data object in RGB order.
let elementSize = MemoryLayout.size(ofValue: normalizedRed)
var bytes = [UInt8](repeating: 0, count: elementSize)
memcpy(&bytes, &normalizedRed, elementSize)
inputData!.append(&bytes, count: elementSize)
memcpy(&bytes, &normalizedGreen, elementSize)
inputData!.append(&bytes, count: elementSize)
memcpy(&bytes, &normalizedBlue, elementSize)
inputData!.append(&bytes, count: elementSize)
return inputData
}
This is the code