Hello
I am developing with reference to the pytorch object detection example.
I am trying to detect an object using pytorch model in android.
It receives an image in real time, receives this image as a bitmap, and displays a specific object as the result.
However, the TensorImageUtils.bitmapToFloat32Tensor function is time consuming and very slow compared to live images.
bitmap = Bitmap.createBitmap(bmp, 0, 0, bmp.width, bmp.height, matrix, true)
        var resizedBitmap = Bitmap.createScaledBitmap(bitmap,PrePostProcessor.mInputWidth,PrePostProcessor.mInputHeight,true)
        inputTensor = TensorImageUtils.bitmapToFloat32Tensor(resizedBitmap,PrePostProcessor.NO_MEAN_RGB,PrePostProcessor.NO_STD_RGB)
        outputTuple  = mModule!!.forward(IValue.from(inputTensor)).toTuple()
        outputTensor = (outputTuple as Array<out IValue>?)?.get(0)!!.toTensor()
        output = outputTensor!!.dataAsFloatArray

Is there any way to solve this? Should I force it to use the gpu? If so, how?