I have an object detection model that I've created in https://customvision.ai. If I export it as a TensorFlow Lite model, I get a model that expects FLOAT32 [1, 416, 416, 3]
as input and returns FLOAT32 [1, 13, 13, 35]
as output (as per TensorFlow Lite's visualize.py
).
I would like to use that model in an Android app. I've tried to load the .tflite
model file into the TensorFlow Lite object detection sample app, however it expects a different format. I get the following exception when running the app. java.lang.IllegalArgumentException: Cannot copy between a TensorFlowLite tensor with shape [1, 13, 13, 35] and a Java object with shape [1, 10, 4].
Is it feasible to adapt the sample app to use the model from customvision.ai?
How should I interpret the shape [1, 13, 13, 35]
?
Thanks in advance!