AutoML TfLite Android Edge Device Tutorial: BufferOverflowException

[tvanfossen]

AutoML TfLite Android Edge Device Tutorial: BufferOverflowException

[rabingaire]

I have also faced the same issue, I changed the putFloat into put and typecasted the value passed into (byte) imgData.put((byte) ((((val >> 16) & 0xFF)-IMAGE_MEAN)/IMAGE_STD)); App stopped crashing but the output model predicts is very very wrong.

[tvanfossen]

I used this tutorial instead: https://www.tensorflow.org/lite/models/image_classification/android

And it works no problem, just swap the tflite and txt file exported from AutoML into the assets folder again and change the ClassifierQuantizedModel to point to the custom file instead of the pregenerated ones.