How to Check Output Object Names Regarding Classes


I have a tflite model with 14 classes that was created via TFLite modelmaker for object detection. It was created with the default parameter values. TFLite model output shows the 4 outputs but I can not decide which output is which class related. The netron output is below for the end tree:

I wonder what this outputs do and how could I decide my android source scripts parameters regarding these.

Any reply would be appreciated. Thank you in advance.

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It is kinda confusing since it has not info about the arrays and the dimensions of each class.
It is stating the explnation for each output and only “float32” value.
Are you sure everything has worked properly during the training?
Have you verified that the tflite model is working with the Python API before you go into android?

When I analyzed tflite’s TFLite_Detection_PostProcess flatbuffers binary two years ago, what I found was that the following four things were the output.

  1. bounding_boxes
  2. class_labels
  3. class_confidences
  4. num_of_boxes

However, it is very difficult to know which output OP corresponds to which output name because the output order of tflite output OPs generated from TensorFlow Model Maker and TF OD API cannot be controlled by user operation.

Yes it works on Python API and there is no trick for the issue on that side. Actually, it seems ok on training but I am not sure if it worked proper during the training. I have also had training with int32 value but it was still confusing that nothing was exact because model maker has no controllable parameters. Trying to check it on the output of the script, it gives outputs but they are confusing, as well. I was trying each object output and it is not regular for each class. An example one class detected and it gives an output but any other object in the classes provides the same output. That’s what I am trying to solve. I am going to try array size approach which you indicated at your reply. Thank you.

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What I need here is to have coordinates and sizes but another problem here is that my aim is to detect 14 classes objects but a lot of them have the same size. If anyone could recommend some other approaches it’d be great :interrobang:

Finally I found the problem. I have 14 classes and trying to use it with image classification. But it is saying that image classification on tflite provides one output. That’s what I learnt thank you for all your replies.

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