Tensorflow Lite Model: Incompatible shapes for input and output array - tensorflow

Question

I'm currently working on a Tensorflow Lite image classifier app that can recognice UNO cards. But when I'm running the float model in the class ImageClassifier, something is wrong.
The error is the next one:
java.lang.IllegalArgumentException: Cannot copy from a TensorFlowLite tensor (Identity) with shape [1, 10647, 4] to a Java object with shape [1, 15].
Here's the code that throw that error:
tflite.run(imgData, labelProbArray);
And this is how I have created imgData and labelProbArray:
private static final int DIM_BATCH_SIZE = 1;
private static final int DIM_PIXEL_SIZE = 3; //r+g+b = 1+1+1
static final int DIM_IMG_SIZE_X = 416;
static final int DIM_IMG_SIZE_Y = 416;
imgData = ByteBuffer.allocateDirect(DIM_BATCH_SIZE * DIM_IMG_SIZE_X * DIM_IMG_SIZE_Y * DIM_PIXEL_SIZE * 4); //The last value because size of float is 4
labelProbArray = new float[1][labelList.size()]; // {1, 15}
You can chech the inputs and ouputs of the .tflite file. Source.
I know you should create a buffer for the output values, but I tried to import this and didn't work:
import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
Any ideas? Thank you so much for read me^^
Edit v2:
Thanks to yyoon I realise that I didn't populate my model with metadata, so I run this line in my cmd:
python ./metadata_writer_for_image_classifier_uno.py \ --model_file=./model_without_metadata/custom.tflite \ --label_file=./model_without_metadata/labels.txt \ --export_directory=model_with_metadata
Before that, I modified this file with my data:
_MODEL_INFO = {
"custom.tflite":
ModelSpecificInfo(
name="UNO image classifier",
version="v1",
image_width=416,
image_height=416,
image_min=0,
image_max=255,
mean=[127.5],
std=[127.5],
num_classes=15)
}
And another error appeared:
ValueError: The number of output tensors (2) should match the number of output tensor metadata (1)
Idk why my model have 2 tensors outputs...