neonankiti

init {
    imgData = ByteBuffer.allocateDirect(
        DIM_BATCH_SIZE
            * imageSizeX
            * imageSizeY
            * DIM_PIXEL_SIZE // 3 
            * numBytesPerChannel
    )
    imgData!!.order(ByteOrder.nativeOrder())
}

neonankiti

fun setDrawPoint(
    point: Array<FloatArray>,
    ratio: Float
  ) {
    var tempX: Float
    var tempY: Float
    for (i in 0..13) {
      tempX = point[0][i] /  ratio / mRatioX
      tempY = point[1][i] / ratio / mRatioY
      mDrawPoint.add(PointF(tempX, tempY))

neonankiti

override fun runInference() {
  val tempArray = FloatArray(outputW * outputH)
  val outTempArray = FloatArray(outputW * outputH)
  for (i in 0..13) {   
    // doing filtering and getting maximum possibility for key points. 
    mPrintPointArray!![0][i] = maxX
    mPrintPointArray!![1][i] = maxY
  }
}

neonankiti

override fun runInference() {
  tflite?.run(imgData!!, heatMapArray)
  mPrintPointArray = Array(2) { FloatArray(14) }
  // Gaussian Filter 5*5
  mMat = Mat(outputW, outputH, CvType.CV_32F)
  val tempArray = FloatArray(outputW * outputH)
  val outTempArray = FloatArray(outputW * outputH)
}

neonankiti

fun addPixelValue(pixelValue: Int) {
  val red = (pixelValue and 0x00FF0000 shr 16) / 255f * 2.0f - 1.0f
  val green = (pixelValue and 0x0000FF00 shr 8) / 255f * 2.0f - 1.0f
  val blue = (pixelValue and 0x000000FF) / 255f * 2.0f - 1.0f
}

neonankiti

fun addPixelValue(pixelValue: Int) {
  //bgr
  imgData!!.putFloat((pixelValue and 0xFF).toFloat())
  imgData!!.putFloat((pixelValue shr 8 and 0xFF).toFloat())
  imgData!!.putFloat((pixelValue shr 16 and 0xFF).toFloat())
}

neonankiti

/** Writes Image data into a `ByteBuffer`.  */
private fun convertBitmapToByteBuffer(bitmap: Bitmap) {
  imgData!!.rewind()
  // intValues are input image size memory like IntArray(bitmap.width * bitmap.height)
  bitmap.getPixels(intValues, 0, bitmap.width, 0, 0, bitmap.width, bitmap.height)
  // Convert the image to floating point.
  var pixel = 0
  for (i in 0 until imageSizeX) {
    for (j in 0 until imageSizeY) {
      val v = intValues[pixel++]

neonankiti

  @Throws(IOException::class)
  private fun loadModelFile(activity: Activity): MappedByteBuffer {
    // modelPath would be something like "image_classifier.tflite"
    val fileDescriptor = activity.assets.openFd(modelPath)
    val inputStream = FileInputStream(fileDescriptor.fileDescriptor)
    val fileChannel = inputStream.channel
    val startOffset = fileDescriptor.startOffset
    val declaredLength = fileDescriptor.declaredLength
    return fileChannel.map(MapMode.READ_ONLY, startOffset, declaredLength)
  }

neonankiti

fun create(
      activity: Activity,
      imageSizeX: Int = 192,
      imageSizeY: Int = 192,
      outputW: Int = 96,
      outputH: Int = 96,
      modelPath: String = "model.tflite",
      numBytesPerChannel: Int = 4
    ): ImageClassifierFloatInception =
      ImageClassifierFloatInception(

neonankiti

private fun classifyFrame() {
    // Get a bitmap with requested width and height. 
    // Also, this bitmap uses ARGB_8888 format. 
    val bitmap = textureView!!.getBitmap(classifier!!.imageSizeX, classifier!!.imageSizeY)
    // This classifier's function internally has the byte data converted from this bitmap. 
    classifier!!.classifyFrame(bitmap)
    bitmap.recycle()
    // mPrintPointArray is the output(results) of inference from input(byte data above)
    drawView!!.setDrawPoint(classifier!!.mPrintPointArray!!, 0.5f)
}