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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!

jonasb
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