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Error running trained, converted darknet yolov3-tiny model on NCS2

We successfully trained a custom yolov3-tiny model on darknet (tested in darknet and confirmed to detect our single class). We successfully converted the weights to a .pb and then .bin and .xml files. The issue comes when trying to run this model on our modified version of the the openvino_tiny-yolov3_multiStick_test.py. We have all the config stuff set up to yolov3-tiny (classes = 1, num = 6, LABELS = "our_object"). When we run it, we get an index out of range error in predict_async
cnt,dev = heapq.heappop(self.heap_request)
HOWEVER if we change num=3 it runs but the output boxes labeled detections is garbage data. Any ideas how to fix this?

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