Hello. I'm attempting to use a different dataset with the AttentionRPN. The evaluation script uses the pickled dataframe of the 10-shot novel classes, so when I evaluate, it detects only novel classes.
If I create a 10-shot support DF of the base classes and use that, I am able to detect the same. Is this the intended way of evaluating the base classes or have I done something incorrectly? I presume in the final evaluation of novel+base, another support DF needs to be created?
Also - there are places where the no. of ways are fixed to 2 and this is asserted. Is it safe to remove those assertions?
Hello. I'm attempting to use a different dataset with the AttentionRPN. The evaluation script uses the pickled dataframe of the 10-shot novel classes, so when I evaluate, it detects only novel classes.
If I create a 10-shot support DF of the base classes and use that, I am able to detect the same. Is this the intended way of evaluating the base classes or have I done something incorrectly? I presume in the final evaluation of novel+base, another support DF needs to be created?
Also - there are places where the no. of ways are fixed to 2 and this is asserted. Is it safe to remove those assertions?