I have trained a tiny yolo3 model with custom data on Keras and want to deploy the model onto a Raspberry Pi. I have converted the Keras .h5 model to a int-quantized .tflite model and wanted to do inference with tflite_support.task, which is only for SSD networks it seems, so that doesn't work for yolo, raises error that it requires a metadata.
So my question now is what would be the best way to deploy a .h5 Keras model onto a Raspberry Pi, I have also tried to convert it to a frozen .pb and use opencv dnn but the conversion doesn't seem to work even following this: How to export Keras .h5 to tensorflow .pb?
Running Keras on a Raspberry Pi can't be really an option, since it would require the full tensorflow installation. Is there a lightweight way for deployment using opencv.dnn or tflite interpreter?
