@Alex_Seguin
Can you try running it on a computer in Python?
I believe it is a problem with the model itself, not the runtime environment that it is running on. Would be very interested to learn otherwise.
Let me know!
Here is a handy script to test a .tflite model on any computer running Python
import numpy as np
import tensorflow as tf
import cv2

img = cv2.imread("test.jpeg")
new_img = cv2.resize(img, (320,320))

# Load the TFLite model and allocate tensors.
interpreter = tf.lite.Interpreter(model_path="model.tflite")
interpreter.allocate_tensors()

# Get input and output tensors.
input_details = interpreter.get_input_details()
output_details = interpreter.get_output_details()

# Test the model on random input data.
interpreter.set_tensor(input_details[0]['index'], [new_img])

interpreter.invoke()

# Show the scores
scores = interpreter.get_tensor(output_details[2]['index'])
print(scores)