I’ve created a model using Keras which I am looking to use with Tensorflow Lite. I specifically wanted to pick out keypoints in an image, and I used this very good documentation as a guide: Keypoint Detection with Transfer Learning
I’ve therefore got a model which takes in an image and produces a series of keypoints, and I’ve used TFLite’s convertor function to convert it to a .tflite file. However when I load the .tflite model in my Android project, it tells me “Input tensor has type kTfLiteFloat32: it requires specifying NormalizationOptions metadata to preprocess input images.” which appears to mean I need to add annotations to the .tflite file.
I’ve found a few examples of annotations for various models, and have the general idea that it’s a json file which specifies what the input and output formats should be, however I haven’t been able to find anything detailing specifically the various different fields and values for this file, so I am not sure how to specify in the annotations that the model outputs a number of keypoints.
Can anyone point me to such documentation or otherwise fill me in on how to specify this?