I am running Tensorflow Lite on my Raspberry Pi 3b+ with a custom object detection mode. I have tested it on a Google COCO dataset and it works wonderfully but when I test it on my custom trained model it does not work despite the model passing TfLite Model Maker evaluation. When I run it the only error I get in my message is “Segmentation fault”. How can I fix this?
I am not able to upload my model to Stackoverflow but just some info about it. It is only detecting one object, It is Not quantized, it is trained based off the efficientdet_lite1 mode, and I trained it using the official Tensorflow Lite Model Maker Google Colab.
Here is the code used to interpret the model on my Pi.
I added a few print statements aswell to troubleshoot and it stops executing at around line 115.
Does anyone know how to fix this?