Hello everyone,
I am training a FasterRCNN model for detecting objects belonging to two classes (excluding background). These classes are not encoded 1 and 2 but 7 and 22. Is it advisable in this case to re-encode the classes as 1 and 2, and set the number of classes (num_classes) of FastRCNNPredictor to 3 (the two classes + background)?
Otherwise I have to set the number of classes of FastRCNNPredictor to 23 (max encoding + 1 for background), which does not seem ideal.
Thanks